@article{moriarty_deploying_2019, title = {Deploying multispectral remote sensing for multi-temporal analysis of archaeological crop stress at {Ravenshall}, {Fife}, {Scotland}}, volume = {26}, copyright = {© 2018 John Wiley \& Sons, Ltd.}, issn = {1099-0763}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1721}, doi = {https://doi.org/10.1002/arp.1721}, abstract = {Diminishing returns of archaeological crop marks in lowland areas from traditional observer-directed visible spectrum aerial survey with standard photographic cameras highlights a need to explore alternative approaches to maintain the effectiveness of survey programmes. Developments in low-cost multispectral remote sensing have in part been driven by the growth of precision agriculture and, whilst contributing to the intensification of land use, these technologies may offer new spectral and temporal capacities for detecting, recording and monitoring historic landscapes. However, there are significant challenges to the deployment of such approaches, not least the costs of data acquisition and uncertainty about the best conditions for data collection. This study assesses the effectiveness of the Parrot Sequoia, a relatively low-cost multispectral sensor recently developed for agricultural applications, for the detection of crop marks to inform archaeological survey. A series of observations were taken with the sensor mounted on an unmanned aerial vehicle (UAV) at Ravenshall, Fife, Scotland, between April and July 2017. The resulting reflectance maps are compared to red, green and blue (RGB) photographs taken with a Nikon D800E digital camera during seven light aircraft surveys, with the aim of testing the sensors' comparative ability to record crop mark developments over time. The contrast in reflectance between vegetation samples growing over buried archaeological remains and the surrounding field was assessed through separability in regional histogram values across different image band combinations. Separable values indicative of crop marks were found in both the multispectral and RGB results from June 2017 onwards. Several vegetation index (VI) maps, particularly the Simple Ratio (SR) and Normalised Difference Vegetation Index (NDVI), were found to be effective for distinguishing crop marks in the multispectral results. The Sequoia is a cost-effective sensor offering improved spectral resolution over the RGB photographs, showing potential for subtle crop mark detection across compact study areas.}, language = {en}, number = {1}, urldate = {2021-05-27}, journal = {Archaeological Prospection}, author = {Moriarty, Charles and Cowley, Dave C. and Wade, Tom and Nichol, Caroline J.}, year = {2019}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1721}, keywords = {aerial photography, agriculture, archaeological survey, multispectral remote sensing, unmanned aerial vehicles (UAVs), vegetation indices}, pages = {33--46}, file = {Full Text:C\:\\Users\\Edify 01\\Zotero\\storage\\L8TE62RK\\Moriarty et al. - 2019 - Deploying multispectral remote sensing for multi-t.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\GVATJPQK\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\KPYKZVYF\\Moriarty et al. - 2019 - Deploying multispectral remote sensing for multi-t.pdf:application/pdf}, } @article{czajlik_cropmarks_2021, title = {Cropmarks in {Aerial} {Archaeology}: {New} {Lessons} from an {Old} {Story}}, volume = {13}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Cropmarks in {Aerial} {Archaeology}}, url = {https://www.mdpi.com/2072-4292/13/6/1126}, doi = {10.3390/rs13061126}, abstract = {Cropmarks are a major factor in the effectiveness of traditional aerial archaeology. Identified almost 100 years ago, the positive and negative features shown by cropmarks are now well understood, as are the role of the different cultivated plants and the importance of precipitation and other elements of the physical environment. Generations of aerial archaeologists are in possession of empirical knowledge, allowing them to find as many cropmarks as possible every year. However, the essential analyses belong mostly to the predigital period, while the significant growth of datasets in the last 30 years could open a new chapter. This is especially true in the case of Hungary, as scholars believe it to be one of the most promising cropmark areas in Europe. The characteristics of soil formed of Late Quaternary alluvial sediments are intimately connected to the young geological/geomorphological background. The predictive soil maps elaborated within the framework of renewed data on Hungarian soil spatial infrastructure use legacy, together with recent remote sensing imagery. Based on the results from three study areas investigated, analyses using statistical methods (the Kolmogorov–Smirnov and Random Forest tests) showed a different relative predominance of pedological variables in each study area. The geomorphological differences between the study areas explain these variations satisfactorily.}, language = {en}, number = {6}, urldate = {2021-07-01}, journal = {Remote Sensing}, author = {Czajlik, Zoltán and Árvai, Mátyás and Mészáros, János and Nagy, Balázs and Rupnik, László and Pásztor, László}, month = jan, year = {2021}, note = {Number: 6 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {alluvial sediments, cropmarks, empirical knowledge, geomorphological/pedological background, soil spatial infrastructure, statistical methods}, pages = {1126}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HPQHT76Z\\Czajlik et al. - 2021 - Cropmarks in Aerial Archaeology New Lessons from .pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\DP9QTWYC\\htm.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\JQNQXKLD\\Czajlik et al. - 2021 - Cropmarks in Aerial Archaeology New Lessons from .pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\U6PKKRDA\\1126.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\QVJHIA3V\\Czajlik et al. - 2021 - Cropmarks in Aerial Archaeology New Lessons from .pdf:application/pdf}, } @incollection{castrignano_chapter_2020, title = {Chapter 3 - {Data} processing}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731000032}, abstract = {An information revolution is currently occurring in agriculture resulting in the production of massive datasets at different spatial and temporal scales; therefore, efficient techniques for processing and summarizing data are crucial for effective precision management. With the profusion and wide diversification of data sources provided by modern technology, such as remote and proximal sensing, sensor datasets could be used as auxiliary information to supplement a sparsely sampled target variable. Remote and proximal sensing data are often massive, taken on different spatial and temporal scales, and subject to measurement error biases. Moreover, differences between the instruments are always present; nevertheless, a data fusion approach could take advantage of their complementary features by combining the sensor datasets in a manner that is statistically robust. It would then be ideal to jointly use (fuse) partial information from the diverse today-available sources so efficiently to achieve a more comprehensive view and knowledge of the processes under study. The chapter investigates the data fusion process in agriculture and introduces the concepts of geostatistical data fusion with applications in remote and proximal sensing.}, language = {en}, urldate = {2021-07-01}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, author = {Castrignanò, Annamaria and Buttafuoco, Gabriele}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.00003-2}, keywords = {Data fusion, Geostatistics, Change of support, Geostatistical data fusion, Multivariate spatial methods}, pages = {139--182}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\Q8IGS4NW\\B9780128183731000032.html:text/html}, } @incollection{naud_chapter_2020, title = {Chapter 4 - {Support} to decision-making}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731000044}, abstract = {Smart farming is about how emerging and evolving technologies support the farmer, and their professional network, in the management of production and of information related to production. Decision support is therefore a core concern. As decision support is actually about making the right decisions and undertaking the right action, it relates to precise functions. From these functions, three themes can be identified, which are developed in this chapter. The first theme concerns building information that can support decisions from spatial data. This includes defining the decision to be supported, including spatial scaling matters, identifying the knowledge management paradigm, the timeliness of decision and action and the criteria involved. The second theme is about optimization and planning. It includes concepts and methods that can be related to decisions taken during the nonproduction periods, such as strategical enterprise objectives and choices of tactics, as well as to decisions taken during the production cycle, which can be simple scheduling of operations or more complex choices aimed at adapting crop management to the specific characteristics of a given year. The third theme is about designing an information system for smart farming. This includes considering the production processes and making models of these and the general framework for design. It also includes elements related to implementation of proposed next-generation databases.}, language = {en}, urldate = {2021-07-01}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, author = {Naud, Olivier and Taylor, James and Colizzi, Lucio and Giroudeau, Rodolphe and Guillaume, Serge and Bourreau, Eric and Crestey, Thomas and Tisseyre, Bruno}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.00004-4}, keywords = {Decision, Decision scale, DSS, Information system, Knowledge, Planning, Smart farming, Smart irrigation, Spatial data}, pages = {183--224}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\XIAC2L4P\\B9780128183731000044.html:text/html}, } @incollection{pedersen_chapter_2020, title = {Chapter 6 - {Economic}, environmental and social impacts}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731000068}, abstract = {Smart farming practices can make a difference regarding economic, environmental and social impact in comparison to conventional techniques. Nowadays, there are several commercially available smart farming technologies (SFT), which can record and map different crop needs and also act on these needs. Such technologies are described in this chapter together with their impact on pricing (where available) and economic benefit from their in-field use – either in reduction of input use or yield increases. Findings from this chapter highlight some of the potential benefits and savings from site-specific application of inputs, including fertilizer and pesticides as well as potential benefits from autosteering and section control. All of these technologies are based on SFT, which requires different sensors, mapping technologies and advanced decision support making. A successful product commercialization needs to follow those systems that have proven a high technology readiness level. This chapter provides a conceptual background description regarding innovation and diffusion of SFT. These descriptions demonstrate the complex interdependencies of positively influencing factors with special attention to the involved actors and their interaction sequences. Furthermore, this chapter presents the process timeline for the development and the implementation of two systems that reached the market effectively. Finally, adoption of SFT and precision farming in particular are discussed, along with how SFT can benefit the environment and how SFT can fit into the common global trends.}, language = {en}, urldate = {2021-07-01}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, author = {Pedersen, S. M. and Pedersen, M. F. and Ørum, J. E. and Fountas, S. and Balafoutis, A. T. and van Evert, F. K. and van Egmond, F. and Knierim, A. and Kernecker, M. and Mouazen, A. M.}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.00006-8}, keywords = {Smart farming, decision making, Economics, environmental impact, farm perception, innovation, policy trends, regulation}, pages = {279--330}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\T4V42HE7\\B9780128183731000068.html:text/html}, } @incollection{dusadeerungsikul_chapter_2020, title = {Chapter 5 - {Smart} action}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731000056}, abstract = {In this chapter, the smart actions for precision agriculture (PA) are presented. With smart actions, resources such as irrigation, fertilizer, pesticides and available time are utilized effectively. The decision support system for smart actions presented in this chapter will support farmers to properly perform agricultural tasks and yield with minimal waste and minimal environmental impacts, better agricultural outputs and outcomes. The chapter is divided into two parts: (Section 5.1) Implementation of Variable Rate Application (VRA) and (Section 5.2) Smart Collaborative Robotics and Cyber-Physical System (CPS) for Smart Precision. In the first one (Section 5.1), the VRA is discussed. The VRA helps to reduce waste from over/underapplication of agricultural input resources by implementing precision application technologies. With VRA, once the status of plants is known, the precision crop need-based actions can be taken properly in real time. For the second part (Section 5.2), Collaborative Control Protocols for Robotics and CPS (CCP-CPS) are presented. The protocols have the objective of synchronizing system agents so that the agents will collaboratively perform agricultural tasks both globally and locally, such as monitoring the status of plants in a greenhouse. The cyber-supported collaboration among agents can enable the system to most effectively utilize available resources. Lastly, smart actions will improve the overall agricultural system performance and will drive us closer to the PA and smart farming, by applying the right amount of resources in the right time at the right place.}, language = {en}, urldate = {2021-07-01}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, author = {Dusadeerungsikul, Puwadol Oak and Liakos, Vasileios and Morari, Francesco and Nof, Shimon Y. and Bechar, Avital}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.00005-6}, keywords = {Sensors, Adaptive search algorithm, Agricultural cyber-physical system (CPS), Collaborative control protocol, Collaborative control theory (CCT), Greenhouse, Prescription map, Site specific}, pages = {225--277}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\XBLM5EN7\\B9780128183731000056.html:text/html}, } @incollection{fastellini_chapter_2020, title = {Chapter 7 - {Precision} farming and {IoT} case studies across the world}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B978012818373100007X}, abstract = {Smart farming is the evolution of precision agriculture, it is based on Internet of Things (IoT), this term was coined by Kevin Ashton in 1999 and it represents data collected from objects or ‘things’, (e.g., devices, implements, sensors) and processed individually or together with algorithms that correlate the information to help the users to take decisions not based only on position, as is in precision agriculture, but also on data ‘enhanced by context and situation awareness, triggered by real-time events’ (Wolfert et al., 2017). Smart farming in Africa was hindered by development of ICT systems around the region. Recent initiatives such as Last Mile Project and other projects that connect sub-Saharan Africa to the world Internet have sparked researchers and other stakeholders in agriculture to make a move on digital agriculture and smart farming in general. These efforts will go so high when Internet costs goes down and becomes accessible to most of the farmers. Farmers in Africa are willing to adopt any technology that would simplify their daily economic activities. That is why mobile money using phones is so popular in Africa and very useful among farming communities.}, language = {en}, urldate = {2021-07-01}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, author = {Fastellini, Guido and Schillaci, Calogero}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.00007-X}, keywords = {Precision agriculture, Africa, Smart farming, Digital agriculture, ICT}, pages = {331--415}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\UZTH89EG\\B978012818373100007X.html:text/html}, } @incollection{colizzi_chapter_2020, title = {Chapter 1 - {Introduction} to agricultural {IoT}}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731000019}, abstract = {Significant challenges will have to be overcome to achieve the level of agricultural productivity necessary to meet the predicted world demand for food, feed, fibre and fuel in 2050. Although agriculture has met significant challenges in the past, targeted increases in productivity will have to be made by 2050, in the face of stringent constraints including limited resources, less skilled labour, limited amount of arable land and changing climate, among others. Currently, agriculture production accounts for over 70\% of freshwater consumption and unsustainable levels of chemical consumption for crop production. In the hyperconnected world, where people, computers and physical objects cooperate to solve complex tasks, a big amount of data and information rises rapidly and a critical aspect is to manage that knowledge to make the right decision at the right time and the right place. Also, farming has to become SMART adopting a new vision of the primary production sector where the development processes are based on the integration of information and communications technologies and Internet of Things technologies in a secure fashion to manage the rural assets and optimization of agronomic inputs such as water, fertilizer, agrochemical or soil tillage and to enhance input use efficiency, output or production and profitability in a sustainable manner. In this vision, the land becomes a substrate where different kinds of sensors could acquire heterogeneous data. Those sensors are connected in a sort of rural network in turn linked to the Internet network. The real-time streaming data are stored in complex database containing all the necessary knowledge about the land characteristics. Intelligent programmes connected with the knowledge base run to make real-time decisions, sending acting messages to the domotic back-end system or suggestions to the farmer.}, language = {en}, urldate = {2021-07-01}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, author = {Colizzi, Lucio and Caivano, Danilo and Ardito, Carmelo and Desolda, Giuseppe and Castrignanò, Annamaria and Matera, Maristella and Khosla, Raj and Moshou, Dimitrios and Hou, Kun-Mean and Pinet, François and Chanet, Jean-Pierre and Hui, Gao and Shi, Hongling}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.00001-9}, keywords = {Sensors, Smart farming, Arduino, Internet of things, Open source platform, Raspberry pi, Smart object}, pages = {1--33}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\SNTEEQL9\\B9780128183731000019.html:text/html;Full Text:C\:\\Users\\Edify 01\\Zotero\\storage\\W3PY59TS\\Colizzi et al. - 2020 - Chapter 1 - Introduction to agricultural IoT.pdf:application/pdf;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HNIDXN9T\\Colizzi et al. - 2020 - Chapter 1 - Introduction to agricultural IoT.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\6KE7N6QT\\B9780128183731000019.html:text/html}, } @incollection{mouazen_chapter_2020, title = {Chapter 2 - {Monitoring}}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731000020}, abstract = {The first requirement for successful implementation of precision agriculture in the plant production sector is to measure and map within-field spatial and temporal variability. This can be achieved by means of two main sensing categories, namely, remote sensing and proximal sensing, for characterizing both soils and crops. Each of these two categories has advantageous and shortcomings. This chapter discusses the potential of different sensing technologies to characterize within-field variability of soils and crops, by providing high sampling resolution data necessary for site-specific management of farm input resources (e.g., fertilizers, water for irrigation, seeds and pesticides). Each of the sensing methods presented are discussed in terms of (1) a brief introduction of a technology, (2) list of properties and associated accuracy and practicality and (3) application case studies for agricultural management.}, language = {en}, urldate = {2021-07-01}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, author = {Mouazen, A. M. and Alexandridis, Thomas and Buddenbaum, Henning and Cohen, Yafit and Moshou, Dimitrios and Mulla, David and Nawar, Said and Sudduth, Kenneth A.}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.00002-0}, keywords = {Soil, Remote sensing, Crop, High sampling resolution, Proximal sensing}, pages = {35--138}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\PFP2PJHR\\B9780128183731000020.html:text/html;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\VX8TAQL3\\B9780128183731000020.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\9QZAMJBJ\\Mouazen et al. - 2020 - Chapter 2 - Monitoring.pdf:application/pdf}, } @article{hunt_what_2018, title = {What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture?}, volume = {39}, issn = {0143-1161}, url = {https://doi.org/10.1080/01431161.2017.1410300}, doi = {10.1080/01431161.2017.1410300}, abstract = {Remote sensing from unmanned aircraft systems (UAS) was expected to be an important new technology to assist farmers with precision agriculture, especially crop nutrient management. There are three advantages using UAS platforms compared to manned aircraft platforms with the same sensor for precision agriculture: (1) smaller ground sample distances, (2) incident light sensors for image calibration, and (3) canopy height models created from structure-from-motion point clouds. These developments hold promise for future data products. In order to better match vendor capabilities with farmer requirements, we classify applications into three general niches: (1) scouting for problems, (2) monitoring to prevent yield losses, and (3) planning crop management operations. The three different niches have different requirements for sensor calibration and have different costs of operation. Planning crop management operations may have the most environmental and economic benefits. However, a USDA Economic Research Report showed that only about 20\% of farmers in the USA have adopted variable rate applicators; so, most farmers in the USA may not have the technology to benefit from management plans. In the near-term, monitoring to prevent yield losses from weeds, insects, and diseases may provide the most economic and environmental benefits, but the costs for data acquisition need to be reduced.}, number = {15-16}, urldate = {2021-08-20}, journal = {International Journal of Remote Sensing}, author = {Hunt, E. Raymond and Daughtry, Craig S. T.}, month = aug, year = {2018}, note = {Publisher: Taylor \& Francis \_eprint: https://doi.org/10.1080/01431161.2017.1410300}, pages = {5345--5376}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\X67IR4XV\\Hunt and Daughtry - 2018 - What good are unmanned aircraft systems for agricu.pdf:application/pdf}, } @article{chen_improved_2020, title = {Improved fluid search optimization-based real-time weed mapping}, volume = {7}, issn = {2214-3173}, url = {https://www.sciencedirect.com/science/article/pii/S2214317319301684}, doi = {10.1016/j.inpa.2019.10.002}, abstract = {In the field of agriculture, variable-rate herbicide spraying (VRHS) technology has been used to solve the low efficiency of pesticides and crop chemical residues. The key of VRHS is the quick and precise identification of weeds from field images, which forms a weed map. Fluid search optimization (FSO) was able to simplify the threshold optimization process to create a weed map, which simulated the fluid flowing from high pressure to low pressure, but it is time consuming and often converges prematurely. So, an explosion mechanism and a two-phase optimization were introduced to improve the FSO-based segmentation algorithm. Experiments of segmentation weeds from a corn field at seedling growth stage showed that the IFSO algorithm obtained the best accuracy of 93.3\% and the least running time of 0.019 s, compared with the standard PSO, GA, and FSO algorithms.}, language = {en}, number = {3}, urldate = {2021-08-20}, journal = {Information Processing in Agriculture}, author = {Chen, Chengcheng and Wang, Shengsheng and Wang, Xianchang and Yu, Helong and Dong, Ruyi}, month = sep, year = {2020}, keywords = {Fluid search optimization algorithm, Otsu, Variable-rate herbicide spraying, Weed map}, pages = {403--417}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\D7Y3HM5H\\Chen et al. - 2020 - Improved fluid search optimization-based real-time.pdf:application/pdf}, } @article{krahmer_weed_2020, title = {Weed surveys and weed mapping in {Europe}: {State} of the art and future tasks}, volume = {129}, issn = {0261-2194}, shorttitle = {Weed surveys and weed mapping in {Europe}}, url = {https://www.sciencedirect.com/science/article/pii/S0261219419303564}, doi = {10.1016/j.cropro.2019.105010}, abstract = {Long-term national European weed surveys, large scale classical phytosociological programs and camera-based documentation systems lead to results which can be documented in form of maps. Comparisons of these visual representations of relative weed positions can be used for the prediction of changing weed spectra and of plant biodiversity changes. Statistical methods connected with mapping software are used for the analysis of environmental factors and of farm managing practices influencing the occurrence of weeds. Maps produced by sensor-driven weed detection devices still differ considerably from maps produced via classical phytosociological approaches. Computer algorithms may allow the precise identification of some weeds in camera images. The present technical solutions are, however, still far from those achieved by experienced botanists. Many weed detection tools based on algorithms are not able to distinguish between closely related weeds yet. A few European countries have a long tradition of surveying weeds in major crops by traditional tools. Various software packages are employed for the analysis, documentation and visualisation of survey results. Large scale comprehensive maps including the infestation of crops over different countries are, however, often biased as not every national research group uses the same methods for the assessment of weed infestation. The ranking of the most common species seems, however, to allow comparable conclusions. The recognition of trends in spectrum changes can only be derived from long term studies as we see it. Our review reflects discussions within the Weed Mapping Working Group of the European Weed Research Society over the last ten years. We try to identify new research trends and to respond accordingly with new research projects. What we see today is a shift from traditional mapping approaches towards the use of digital devices as for example in precision farming projects. Another issue of increasing importance is the mapping of herbicide resistant biotypes.}, language = {en}, urldate = {2021-08-20}, journal = {Crop Protection}, author = {Krähmer, Hansjörg and Andreasen, Christian and Economou-Antonaka, Garifalia and Holec, Josef and Kalivas, Dionissios and Kolářová, Michaela and Novák, Robert and Panozzo, Silvia and Pinke, Gyula and Salonen, Jukka and Sattin, Maurizio and Stefanic, Edita and Vanaga, Ineta and Fried, Guillaume}, month = mar, year = {2020}, keywords = {Biodiversity, Arable weeds, Herbicide resistant weeds, Invasive weeds, Mapping methodology, Species distribution}, pages = {105010}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\ZR2EVW4T\\Krähmer et al. - 2020 - Weed surveys and weed mapping in Europe State of .pdf:application/pdf}, } @article{franzen_algorithms_2016, title = {Algorithms for {In}-{Season} {Nutrient} {Management} in {Cereals}}, volume = {108}, issn = {1435-0645}, url = {https://acsess.onlinelibrary.wiley.com/doi/abs/10.2134/agronj2016.01.0041}, doi = {10.2134/agronj2016.01.0041}, abstract = {The demand for improved decision-making products for cereal production systems has placed added emphasis on using plant sensors in-season, and that incorporate real-time, site specific, growing environments. The objectives of this work were to describe validated in-season sensor-based algorithms presently being used in cereal grain production systems for improving nitrogen use efficiency (NUE) and cereal grain yields. A review of research programs in the central Great Plains that have developed sensor-based N recommendations for cereal crops was performed. Algorithms included multiple land-grant university, government, and industry programs. A common thread in this review is the use of active sensors, particularly those using the normalized difference vegetation index (NDVI) for quantifying differences in fertilized and non-fertilized areas, within a specific cropping season. In-season prediction of yield potential over different sites and years is possible using NDVI, planting date, sensing date, cumulative growing degree days (GDD), and rainfall. Other in-season environment-specific inputs have also been used. Early passive sensors have advanced to by-plant N fertilization using active NDVI and by-plant statistical properties. Most recently, sensor-based algorithm research has focused on the development of generalized mathematical models for determining optimal crop N application. The development and promotion of fee-based modeling approaches for nutrient management continues. Nonetheless, several algorithms using active sensors for in-season N management are available from state and government sources at no cost and that have been extensively field tested and can be modified by producers. Core Ideas Normalized difference vegetation index algorithms can improve fertilizer N efficiency. Normalized difference vegetation index sensors currently sold employ these algorithms. Algorithms rely on knowledge that increased yields increase fertilizer N demand. Yield potential and N response are independent. Nitrogen-rich strips help to predict in-season grain yields.}, language = {en}, number = {5}, urldate = {2021-08-11}, journal = {Agronomy Journal}, author = {Franzen, Dave and Kitchen, Newell and Holland, Kyle and Schepers, James and Raun, William}, year = {2016}, note = {\_eprint: https://acsess.onlinelibrary.wiley.com/doi/pdf/10.2134/agronj2016.01.0041}, pages = {1775--1781}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\Q47U9IN5\\Franzen et al. - 2016 - Algorithms for In-Season Nutrient Management in Ce.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\PZ9E2X5Z\\agronj2016.01.html:text/html}, } @article{pena_weed_2013, title = {Weed {Mapping} in {Early}-{Season} {Maize} {Fields} {Using} {Object}-{Based} {Analysis} of {Unmanned} {Aerial} {Vehicle} ({UAV}) {Images}}, volume = {8}, issn = {1932-6203}, url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0077151}, doi = {10.1371/journal.pone.0077151}, abstract = {The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r2=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86\% of overall accuracy. In the experimental field, the area free of weeds was 23\%, and the area with low weed coverage ({\textless}5\% weeds) was 47\%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance.}, language = {en}, number = {10}, urldate = {2021-08-20}, journal = {PLOS ONE}, author = {Peña, José Manuel and Torres-Sánchez, Jorge and Castro, Ana Isabel de and Kelly, Maggi and López-Granados, Francisca}, month = oct, year = {2013}, note = {Publisher: Public Library of Science}, keywords = {Maize, Algorithms, Cereal crops, Crops, Herbicides, Image analysis, Image processing, Weeds}, pages = {e77151}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\RM84BUCK\\article.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\CWD5E29R\\Peña et al. - 2013 - Weed Mapping in Early-Season Maize Fields Using Ob.pdf:application/pdf}, } @article{kashyap_sensing_2021, title = {Sensing {Methodologies} in {Agriculture} for {Monitoring} {Biotic} {Stress} in {Plants} {Due} to {Pathogens} and {Pests}}, volume = {6}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2411-5134/6/2/29}, doi = {10.3390/inventions6020029}, abstract = {Reducing agricultural losses is an effective way to sustainably increase agricultural output efficiency to meet our present and future needs for food, fiber, fodder, and fuel. Our ever-improving understanding of the ways in which plants respond to stress, biotic and abiotic, has led to the development of innovative sensing technologies for detecting crop stresses/stressors and deploying efficient measures. This article aims to present the current state of the methodologies applied in the field of agriculture towards the detection of biotic stress in crops. Key sensing methodologies for plant pathogen (or phytopathogen), as well as herbivorous insects/pests are presented, where the working principles are described, and key recent works discussed. The detection methods overviewed for phytopathogen-related stress identification include nucleic acid-based methods, immunological methods, imaging-based techniques, spectroscopic methods, phytohormone biosensing methods, monitoring methods for plant volatiles, and active remote sensing technologies. Whereas the pest-related sensing techniques include machine-vision-based methods, pest acoustic-emission sensors, and volatile organic compound-based stress monitoring methods. Additionally, Comparisons have been made between different sensing techniques as well as recently reported works, where the strengths and limitations are identified. Finally, the prospective future directions for monitoring biotic stress in crops are discussed.}, language = {en}, number = {2}, urldate = {2021-08-20}, journal = {Inventions}, author = {Kashyap, Bhuwan and Kumar, Ratnesh}, month = jun, year = {2021}, note = {Number: 2 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {remote sensing, acoustic, biosensors, electrochemical, fluorescence, hormones, hyperspectral, spectroscopy, thermography, volatile organic compounds}, pages = {29}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\QBNMYLE5\\Kashyap and Kumar - 2021 - Sensing Methodologies in Agriculture for Monitorin.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\N4UQB3B5\\htm.html:text/html}, } @article{colaco_crop_2018, title = {Do crop sensors promote improved nitrogen management in grain crops?}, volume = {218}, issn = {0378-4290}, url = {https://www.sciencedirect.com/science/article/pii/S0378429017318634}, doi = {10.1016/j.fcr.2018.01.007}, abstract = {Crop sensing technologies to aid nitrogen management in grain crops have been the focus of an important element of Precision/Digital Agriculture research. We review sensor-based application research to explore the outcomes from this technology and provide guidelines for future developments in its application. Most studies report N fertilizer savings of 5–45\% with little effect on grain yield, but a lack of consistent evidence of economic benefits limits adoption by farmers. Reported impacts on profit usually ranged between losses of US\$ 30 ha−1 and profits of US\$ 70 ha−1, with an overall average profit of US\$ 30 ha−1; about 25\% of studies reported economic losses from sensor-based N applications. Sensor-based N applications which reduced environmental impacts were often not profitable compared to current N practices. Some methodological aspects of the research have also made interpretation of the benefits difficult as the value of the information used to recommend N rates and improved agronomy was often confounded with the value of sensor-based variable rate technology itself. Traditional plot experiments adopted in most studies are not the ideal method to evaluate variable rate technologies implemented to accommodate the effects of spatial variability. Neither simple fertilizer redistribution functions nor calibrated sensor algorithms, with or without the use of reference N-rich strips, were necessarily successful across a range of field conditions. New approaches to sensor-based site-specific N management are needed and it is likely the best approaches will arise from the use of multiple sensors.}, language = {en}, urldate = {2021-08-18}, journal = {Field Crops Research}, author = {Colaço, A. F. and Bramley, R. G. V.}, month = apr, year = {2018}, keywords = {Crop Circle, Economic benefits, GreenSeeker, N-rich strip, N-sensor, Site-specific management}, pages = {126--140}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\IT2PV6B9\\S0378429017318634.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HUNJTBS3\\Colaço and Bramley - 2018 - Do crop sensors promote improved nitrogen manageme.pdf:application/pdf}, } @article{ali_leaf_2017, title = {Leaf nitrogen determination using non-destructive techniques–{A} review}, volume = {40}, issn = {0190-4167}, url = {https://doi.org/10.1080/01904167.2016.1143954}, doi = {10.1080/01904167.2016.1143954}, abstract = {The optimisation of plant nitrogen-use-efficiency (NUE) has a direct impact on increasing crop production by optimising use of nitrogen fertiliser. Moreover, it protects environment from negative effects of nitrate leaching and nitrous oxide production. Accordingly, nitrogen (N) management in agriculture systems has been major focus of many researchers. Improvement of NUE can be achieved through several methods including more accurate measurement of foliar N contents of crops during different growth phases. There are two types of methods to diagnose foliar N status: destructive and non-destructive. Destructive methods are expensive and time-consuming, as they require tissue sampling and subsequent laboratory analysis. Thus, many farmers find destructive methods to be less attractive. Non-destructive methods are rapid and less expensive but are usually less accurate. Accordingly, improving the accuracy of non-destructive N estimations has become a common goal of many researchers, and various methods varying in complexity and optimality have been proposed for this purpose. This paper reviews various commonly used non-destructive methods for estimating foliar N status of plants.}, number = {7}, urldate = {2021-08-11}, journal = {Journal of Plant Nutrition}, author = {Ali, M. M. and Al-Ani, Ahmed and Eamus, Derek and Tan, Daniel K. Y.}, month = apr, year = {2017}, note = {Publisher: Taylor \& Francis \_eprint: https://doi.org/10.1080/01904167.2016.1143954}, keywords = {image processing, nitrogen, Non-destructive}, pages = {928--953}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\XZL3Q9SV\\Ali et al. - 2017 - Leaf nitrogen determination using non-destructive .pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\URXZTJA7\\01904167.2016.html:text/html}, } @article{maes_estimating_2012, title = {Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture: a review}, volume = {63}, issn = {0022-0957}, shorttitle = {Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture}, url = {https://doi.org/10.1093/jxb/ers165}, doi = {10.1093/jxb/ers165}, abstract = {As evaporation of water is an energy-demanding process, increasing evapotranspiration rates decrease the surface temperature (Ts) of leaves and plants. Based on this principle, ground-based thermal remote sensing has become one of the most important methods for estimating evapotranspiration and drought stress and for irrigation. This paper reviews its application in agriculture. The review consists of four parts. First, the basics of thermal remote sensing are briefly reviewed. Second, the theoretical relation between Ts and the sensible and latent heat flux is elaborated. A modelling approach was used to evaluate the effect of weather conditions and leaf or vegetation properties on leaf and canopy temperature. Ts increases with increasing air temperature and incoming radiation and with decreasing wind speed and relative humidity. At the leaf level, the leaf angle and leaf dimension have a large influence on Ts; at the vegetation level, Ts is strongly impacted by the roughness length; hence, by canopy height and structure. In the third part, an overview of the different ground-based thermal remote sensing techniques and approaches used to estimate drought stress or evapotranspiration in agriculture is provided. Among other methods, stress time, stress degree day, crop water stress index (CWSI), and stomatal conductance index are discussed. The theoretical models are used to evaluate the performance and sensitivity of the most important methods, corroborating the literature data. In the fourth and final part, a critical view on the future and remaining challenges of ground-based thermal remote sensing is presented.}, number = {13}, urldate = {2021-08-21}, journal = {Journal of Experimental Botany}, author = {Maes, W. H. and Steppe, K.}, month = aug, year = {2012}, pages = {4671--4712}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\G6EVIIGA\\Maes and Steppe - 2012 - Estimating evapotranspiration and drought stress w.pdf:application/pdf}, } @inproceedings{torrejon_valdelomar_big_2016, title = {{BIG} {DATA} {IN} {LANDSCAPE} {ARCHAEOLOGICAL} {PROSPECTION}}, isbn = {978-84-9048-455-5}, url = {http://ocs.editorial.upv.es/index.php/arqueologica20/arqueologica8/paper/view/4200}, doi = {10.4995/arqueologica8.2016.4200}, abstract = {While traditionally archaeological research has mainly been focused on individual cultural heritage monuments or distinct archaeological sites, the Austrian based Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology goes beyond the limitations of discrete sites in order to understand their archaeological context. This is achieved by investigating the space in-between the sites, studying entire archaeological landscapes from the level of individual postholes to the mapping of numerous square kilometres. This large-scale, high-resolution, multi-method prospection approach leads to enormous digital datasets counting many terabytes of data that until recently were technically not manageable. Novel programs and methods of data management had to be developed for data acquisition, processing and archaeological interpretation, in order to permit the extraction of the desired information from the very big amount of data. The analysis of the generated datasets is conducted with the help of semi-automatic algorithms within complex three-, or even four-dimensional geographical information systems. The outcome of landscape archaeological prospection surveys is visually communicated to the scientific community as well as to the general public and stakeholders. In many cases, a visualization of the scientific result and archaeological interpretations can be a powerful and suitable tool to illustrate and communicate even complex contexts to a wide audience. This paper briefly presents the great potential offered by a combination of large-scale non-invasive archaeological prospection methods and standardized workflows for the integration of big data, its interpretation and visualization. The proposed approach provides a context for buried archaeology across entire archaeological landscapes, changing our understanding of known monuments. We address the overcome and remaining challenges with the help of examples taken from outstanding landscape archaeological prospection case studies.}, urldate = {2021-08-17}, booktitle = {Proceedings of the {ARQUEOLÓGICA} 2.0 8th {International} {Congress} on {Archaeology}, {Computer} {Graphics}, {Cultural} {Heritage} and {Innovation}}, publisher = {Universitat Politècnica València}, author = {Torrejón Valdelomar, Juan and Wallner, Mario and Trinks, Immo and Kucera, Matthias and Luznik, Nika and Löcker, Klaus and Neubauer, Wolfgang}, month = sep, year = {2016}, keywords = {landscape, Europe, big data, archeaological prospection}, file = {Full Text:C\:\\Users\\Edify 01\\Zotero\\storage\\SAMZBR5L\\Torrejón Valdelomar et al. - 2016 - BIG DATA IN LANDSCAPE ARCHAEOLOGICAL PROSPECTION.pdf:application/pdf}, } @article{blasch_farmer_2020, title = {Farmer preferences for adopting precision farming technologies: a case study from {Italy}}, issn = {0165-1587}, shorttitle = {Farmer preferences for adopting precision farming technologies}, url = {https://doi.org/10.1093/erae/jbaa031}, doi = {10.1093/erae/jbaa031}, abstract = {Precision farming (PF) technologies can help to mitigate the environmental impact of agriculture by reducing fertiliser use and irrigation while saving cost for the farmer. However, these technologies are not widely adopted in Europe. We study farmers’ willingness to adopt PF technologies based on a choice experiment. Among other determinants, we explore the role of social influence for the valuation of PF technology features. The data are analysed using mixed and latent class logit models. Our results show that knowledge of fellow farmers who adopted the technology positively influences the valuation of PF technology features, stressing the importance of networks.}, number = {jbaa031}, urldate = {2021-08-24}, journal = {European Review of Agricultural Economics}, author = {Blasch, J and van der Kroon, B and van Beukering, P and Munster, R and Fabiani, S and Nino, P and Vanino, S}, month = dec, year = {2020}, keywords = {Precision agriculture, Europe, Economic benefits, Adoption, Farmer preferences, Italy, Survey questionnaire}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\YLYN5NK2\\Blasch et al. - 2020 - Farmer preferences for adopting precision farming .pdf:application/pdf}, } @misc{noauthor_data_nodate, title = {Data lake and data warehouse – know the difference}, url = {https://www.sas.com/en_gb/insights/articles/data-management/data-lake-and-data-warehouse-know-the-difference.html}, abstract = {Data lake – is it just marketing hype or a new name for a data warehouse? Find out what a data lake is, how it works and when you might need one.}, language = {en-GB}, urldate = {2021-08-12}, keywords = {big data, Americas, big data analysis, US}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\YH7LMVF8\\data-lake-and-data-warehouse-know-the-difference.html:text/html}, } @article{lozic_application_2021, title = {Application of {Airborne} {LiDAR} {Data} to the {Archaeology} of {Agrarian} {Land} {Use}. {The} {Case} {Study} of the {Early} {Medieval} {Microregion} of {Bled} ({Slovenia})}, volume = {13}, doi = {10.3390/rs13163228}, abstract = {The use of topographic airborne LiDAR data has become an essential part of archaeological prospection, particularly as a tool for detecting archaeological features in the landscape. However, its use for landscape reconstruction and understanding archaeological sites in their environmental context is still underutilised. To this end, we took an innovative approach to using LiDAR data as a means of discovering, documenting, and interpreting agricultural land use systems by looking for significant environmental variation within a microregion. We combined information from LiDAR-derived DEM derivatives with archaeological, geological, and soil data. We introduced two methodological innovations. The first is the modified wetness index, which combines the LiDAR-derived precision with the accuracy of the effective field capacity of the soil to obtain a very realistic predictor of soil quality. The second is the modified landform classification, a combination of topographic position index and visual geomorphological analysis, which amalgamates two of the most important predictive variables for the distribution of plant species. Our approach is demonstrated by a case study focusing on early medieval settlements in the context of agricultural land use in the subalpine microregion of Bled (Slovenia). It revealed that early medieval settlers were drawn to light soils with high water retention capacity. Such soils were particularly suitable for the cultivation of barley, which is known to have been one of the most important staple crops of the period, especially in colder climate such as subalpine. Soils with lower water retention capacity were not colonized until the eleventh century, which may signify the transition at that time to a higher level of agricultural organisation and wheat as a staple cereal food.}, journal = {Remote Sensing}, author = {Lozić, Edisa}, month = aug, year = {2021}, keywords = {archaeology, airborne LiDAR, agrarian land use, Airborne Laser Scanning, early medieval period, SAGA wetness index, topographic position index}, pages = {3228}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\IJD3W47X\\Lozić - 2021 - Application of Airborne LiDAR Data to the Archaeol.pdf:application/pdf}, } @article{arnold_evaluating_2006, title = {Evaluating the potential of high‐resolution airborne {LiDAR} data in glaciology}, volume = {27}, issn = {0143-1161}, url = {https://doi.org/10.1080/01431160500353817}, doi = {10.1080/01431160500353817}, abstract = {We present the results of an investigation into the capabilities of high‐resolution airborne Light Detection And Ranging (LiDAR) for the study of a small glacier in Svalbard. The data are shown to be capable of producing a digital elevation model (DEM) with a horizontal resolution of 1–2 m and a vertical resolution of 5–15 cm. This degree of resolution is suitable for mass‐balance estimation using repeat data on an annual or semi‐annual basis, but it is also reveals linear surface features such as meltwater channels and crevasses. These have potential for tracking in repeat imagery to deduce the surface flow of the glacier. The intensity of the returned LiDAR pulse can also be used to discriminate snow‐covered parts of the glacier from bare ice.}, number = {6}, urldate = {2021-08-31}, journal = {International Journal of Remote Sensing}, author = {Arnold, N. S. and Rees, W. G. and Devereux, B. J. and Amable, G. S.}, month = mar, year = {2006}, note = {Publisher: Taylor \& Francis \_eprint: https://doi.org/10.1080/01431160500353817}, keywords = {Lidar, Geology}, pages = {1233--1251}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\2W25S87D\\01431160500353817.html:text/html}, } @misc{noauthor_using_2018, title = {Using {Airborne} {Lidar} in {Archaeological} {Survey} {\textbar} {Historic} {England}}, url = {https://historicengland.org.uk/images-books/publications/using-airborne-lidar-in-archaeological-survey/}, abstract = {This guidance is designed to help those intending to use airborne laser scanning (ALS), also known as lidar, for archaeological survey. The aim is to help archaeologists, researchers and those who manage the historic environment to decide first, whether using lidar data will actually be beneficial in terms of their research aims, and second, how the data can be used effectively. The guidance will be most useful to those who have access to data that have already been commissioned, or are planning to commission lidar for a specific purpose. They also provide an introduction to data interpretation in order to separate archaeological and non-archaeological features. Although important themes are introduced, this guidance are not intended as a definitive explanation of the technique or the complexities of acquiring and processing the raw data, particularly as this is a still developing technology. This document is intended to complement 3D Laser Scanning for Heritage, which covers a wider range of uses of laser scanning for heritage purposes (Historic England 2018). This document is a revision of The Light Fantastic: Using Airborne Lidar in Archaeological Survey published by English Heritage in 2010. The text has largely been maintained except for certain areas where major changes have occurred in the ensuing years. This is particularly true with regard to increased access to data and the wide range of visualisation techniques now available. The case studies have also been updated to reflect more recent survey activity and to include examples from outside Historic England. This document has been prepared by Simon Crutchley of Historic England and Peter Crow of Forest Research. This edition published by Historic England July 2018. All images © Historic England unless otherwise stated. Please refer to this document as: Historic England 2018 Using Airborne Lidar in Archaeological Survey: The Light Fantastic. Swindon. Historic England. HistoricEngland.org.uk/research/methods/airborne-remote-sensing/lidar/}, language = {en}, urldate = {2021-08-30}, year = {2018}, keywords = {Archaeology, Aerial archaeology, Europe, Lidar, Feature detection, Guidelines, UK}, file = {using-ea-lidar-data-pdf.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\S57AX3PL\\using-ea-lidar-data-pdf.pdf:application/pdf;heag179-using-airborne-lidar-in-archaeological-survey.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\V8WP3TG3\\heag179-using-airborne-lidar-in-archaeological-survey.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ISKB9682\\using-airborne-lidar-in-archaeological-survey.html:text/html}, } @article{challis_generic_2011, title = {A {Generic} {Toolkit} for the {Visualization} of {Archaeological} {Features} on {Airborne} {LiDAR} {Elevation} {Data}}, volume = {18}, issn = {1099-0763}, url = {https://www.onlinelibrary.wiley.com/doi/abs/10.1002/arp.421}, doi = {10.1002/arp.421}, abstract = {A range of techniques have become established for the visualization and analysis of airborne LiDAR elevation data within the field of archaeology. In this paper we discuss the visualization of test data representing archaeological features in a variety of terrains using a suite of techniques, all available through generic geographical information system or image processing software. These comprise elevation shading using constrained colour ramps, slope analysis, hill-shading, principal component analysis of multi-azimuth hill-shading, local relief models and solar insolation modelling. The strengths and weaknesses of each technique are discussed and a generic toolkit, suited to the visualization of airborne LiDAR data for archaeological purposes, is presented. Copyright © 2011 John Wiley \& Sons, Ltd.}, language = {en}, number = {4}, urldate = {2021-09-01}, journal = {Archaeological Prospection}, author = {Challis, Keith and Forlin, Paolo and Kincey, Mark}, year = {2011}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.421}, keywords = {archaeology, LiDAR, visualization, analytical techniques, toolkit}, pages = {279--289}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\8QAR2BJT\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\MZE3CZJR\\Challis et al. - 2011 - A Generic Toolkit for the Visualization of Archaeo.pdf:application/pdf}, } @article{palazzi_feeding_2019, title = {Feeding the {World} {With} {Microwaves}: {How} {Remote} and {Wireless} {Sensing} {Can} {Help} {Precision} {Agriculture}}, volume = {20}, issn = {1557-9581}, shorttitle = {Feeding the {World} {With} {Microwaves}}, doi = {10.1109/MMM.2019.2941618}, abstract = {Precision agriculture is an increasingly hot topic. The world population is in constant growth [1], which means that global food production needs to rise to keep pace with the projected demand. Although food production has increased by 100\% in the last 30 years, it must rise by another 60\% by 2050 to reduce the risk of malnutrition. This can be achieved only by improving productivity because, globally, the cultivated area is slowly contracting [2], thus drastically reducing the amount of arable land per person.}, number = {12}, journal = {IEEE Microwave Magazine}, author = {Palazzi, Valentina and Bonafoni, Stefania and Alimenti, Federico and Mezzanotte, Paolo and Roselli, Luca}, month = dec, year = {2019}, note = {Conference Name: IEEE Microwave Magazine}, keywords = {Spatial resolution, Sensors, Soil, Remote sensing, Europe, Agriculture, Italy, Precision engineering, Vegetation mapping, wireless sensor networks}, pages = {72--86}, file = {IEEE Xplore Abstract Record:C\:\\Users\\Edify 01\\Zotero\\storage\\ZZGCVQND\\8894635.html:text/html;IEEE Xplore Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\STWYK3IC\\Palazzi et al. - 2019 - Feeding the World With Microwaves How Remote and .pdf:application/pdf;IEEE Xplore Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\6BFF332A\\Palazzi et al. - 2019 - Feeding the World With Microwaves How Remote and .pdf:application/pdf;IEEE Xplore Abstract Record:C\:\\Users\\Edify 01\\Zotero\\storage\\3HH62VXW\\8894635.html:text/html}, } @article{james_thermal_2020, title = {Thermal and {Multispectral} {Remote} {Sensing} for the {Detection} and {Analysis} of {Archaeologically} {Induced} {Crop} {Stress} at a {UK} {Site}}, volume = {4}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2504-446X/4/4/61}, doi = {10.3390/drones4040061}, abstract = {In intensively cultivated landscapes, many archaeological remains are buried under the ploughed soil, and detection depends on crop proxies that express subsurface features. Traditionally these proxies have been documented in visible light as contrasting areas of crop development commonly known as cropmarks. However, it is recognised that reliance on the visible electromagnetic spectrum has inherent limitations on what can be documented, and multispectral and thermal sensors offer the potential to greatly improve our ability to detect buried archaeological features in agricultural fields. The need for this is pressing, as ongoing agricultural practices place many subsurface archaeological features increasingly under threat of destruction. The effective deployment of multispectral and thermal sensors, however, requires a better understanding of when they may be most effective in documenting archaeologically induced responses. This paper presents the first known use of the FLIR Vue Pro-R thermal imager and Red Edge-M for exploring crop response to archaeological features from two UAV surveys flown in May and June 2019 over a known archaeological site. These surveys provided multispectral imagery, which was used to create vegetation index (VI) maps, and thermal maps to assess their effectiveness in detecting crop responses in the temperate Scottish climate. These were visually and statistically analysed using a Mann Whitney test to compare temperature and reflectance values. While the study was compromised by unusually damp conditions which reduced the potential for cropmarking, the VIs (e.g., Normalised Difference Vegetation Index, NDVI) did show potential to detect general crop stress across the study site when they were statistically analysed. This demonstrates the need for further research using multitemporal data collection across case study sites to better understand the interactions of crop responses and sensors, and so define appropriate conditions for large-area data collection. Such a case study-led multitemporal survey approach is an ideal application for UAV-based documentation, especially when \“perfect\” conditions cannot be guaranteed.}, language = {en}, number = {4}, urldate = {2021-08-30}, journal = {Drones}, author = {James, Katherine and Nichol, Caroline J. and Wade, Tom and Cowley, Dave and Gibson Poole, Simon and Gray, Andrew and Gillespie, Jack}, month = dec, year = {2020}, note = {Number: 4 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {archaeology, agriculture, multispectral remote sensing, unmanned aerial vehicles (UAVs), vegetation indices, cropmarks, crop stress, thermal remote sensing}, pages = {61}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\LZMTMACP\\James et al. - 2020 - Thermal and Multispectral Remote Sensing for the D.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\2R93RDU3\\61.html:text/html}, } @misc{noauthor_7_2018, title = {The 7 {R}'s of {Sustainability} • {AeromatiCo}}, url = {https://www.aeromatico.com/the-7-rs-of-sustainability/}, abstract = {The 7 R's of Sustainability define the models necessary to ensure the survival of the human race and planet Earth. These includes ways to slow or reverse pollution, conserve natural resources and protect our environment.}, language = {en-US}, urldate = {2021-08-11}, journal = {AeromatiCo}, month = jul, year = {2018}, note = {Section: Recycling}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\DAKMZIJX\\the-7-rs-of-sustainability.html:text/html}, } @book{trinks_efficient_2016, title = {Efficient mapping of agricultural soils using a novel electromagnetic measurement system}, abstract = {“Despite all our accomplishments, we owe our existence to a six-inch layer of topsoil and the fact that it rains.” – Paul Harvey. Despite the fact, that a farmers most precious good is the soil that he or she cultivates, in most cases actually very little is known about the soils that are being farmed. Agricultural soils are under constant threat through erosion, depletion, pollution and other degrading processes, in particular when considering intensive industrial scale farming. The capability of soils to retain water and soil moisture is of vital importance for their agricultural potential. Detailed knowledge of the physical properties of soils, their types and texture, water content and the depth of the agricultural layer would be of great importance for resource-efficient tillage with sub-area dependent variable depth, and the targeted intelligent application of fertilizers or irrigation. Precision farming, which has seen increasing popularity in the USA as well as Australia, is still in its infancy in Europe. Traditional near-surface geophysical prospection systems for agricultural soil mapping have either been based on earth resistance measurements using electrode-disks that require soil contact, with inherent issues, or electromagnetic induction (EMI) measurements conducted with EMI devices mounted in non-metallic sledges towed several metres behind survey vehicles across the fields. Every farmer passes over the fields several times during each growing season, working the soil and treating the crops. Therefore a novel user-friendly measurement system, the “Topsoil Mapper” (TSM) has been developed, which enables the farmer to simultaneously acquire soil conductivity information and derived soil parameters while anyway passing over the fields using different agricultural implements. The measurement principle of the TSM is electromagnetic induction using a multi-coil array to acquire conductivity information along a vertical profile down to approximately 1.1 m depth. Instead of being towed several metres behind the tractor, as common with traditional EMI systems used in precision farming, the novel device is conveniently mounted on the front hitch of a tractor and operated from a terminal in the driver’s cabin. A major improvement compared with existing EMI systems is the system’s capability to cope with the induced noise from the tractor, through integration of a mechanical shielding mechanism into the sensor housing. Any remaining vehicle induced high-frequency electromagnetic noise is filtered out on-the-fly by the data acquisition software, logging the data and positioning information on a ruggedized small computer. The main purpose of this system is to permit the land owner or farmer the efficient mapping of the electrical soil conductivity across agricultural fields on the scale of the entire acreage. The main objective of the measurements is to obtain detailed information on the long wavelength variability of soil structure, while eliminating short wavelength variations. The calculation of the depth of the agricultural layer, or topsoil thickness, has been implemented by inverting the cumulative response function for all coil configurations. The resulting inverted models of the soil conductivity display the vertical distribution of agriculturally relevant soil parameters and improve the chances to identify different subsoil features. By providing this information on the shallow subsurface in real-time, while passing across the field, permits the agriculturist to variably adjust for instance tillage depth or to control other agricultural implements and machines based to the derived information, rendering the soil cultivation both ecologically as well as economically more efficient. We present the TSM system as well as derived data examples.}, author = {Trinks, Immo and Pregesbauer, Michael}, month = apr, year = {2016}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\4F9CNQQJ\\Trinks and Pregesbauer - 2016 - Efficient mapping of agricultural soils using a no.pdf:application/pdf}, } @misc{noauthor_ag_2021, title = {Ag {Hub}}, url = {https://www.ag.ndsu.edu:8000/agriculture/ag-hub}, abstract = {A one-stop source for information and tools from the NDSU Agricultural Experiment Station and NDSU Extension to help farmers and ranchers make informed decisions that positively impact their business.}, language = {en}, urldate = {2021-08-17}, journal = {NDSU Agriculture and Extension}, month = feb, year = {2021}, note = {Section: Landing Page}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\IY78NFWZ\\ag-hub.html:text/html}, } @article{misopolinos_development_2015, title = {Development of a {UAV} system for {VNIR}-{TIR} acquisitions in precision agriculture}, volume = {9535}, doi = {10.1117/12.2192660}, abstract = {Adoption of precision agriculture techniques requires the development of specialized tools that provide spatially distributed information. Both flying platforms and airborne sensors are being continuously evolved to cover the needs of plant and soil sensing at affordable costs. Due to restrictions in payload, flying platforms are usually limited to carry a single sensor on board. The aim of this work is to present the development of a vertical take-off and landing autonomous unmanned aerial vehicle (VTOL UAV) system for the simultaneous acquisition of high resolution vertical images at the visible, near infrared (VNIR) and thermal infrared (TIR) wavelengths. A system was developed that has the ability to trigger two cameras simultaneously with a fully automated process and no pilot intervention. A commercial unmanned hexacopter UAV platform was optimized to increase reliability, ease of operation and automation. The designed systems communication platform is based on a reduced instruction set computing (RISC) processor running Linux OS with custom developed drivers in an efficient way, while keeping the cost and weight to a minimum. Special software was also developed for the automated image capture, data processing and on board data and metadata storage. The system was tested over a kiwifruit field in northern Greece, at flying heights of 70 and 100m above the ground. The acquired images were mosaicked and geo-corrected. Images from both flying heights were of good quality and revealed unprecedented detail within the field. The normalized difference vegetation index (NDVI) was calculated along with the thermal image in order to provide information on the accurate location of stressors and other parameters related to the crop productivity. Compared to other available sources of data, this system can provide low cost, high resolution and easily repeatable information to cover the requirements of precision agriculture.}, journal = {Proceedings of SPIE - The International Society for Optical Engineering}, author = {Misopolinos, Lazaros and Zalidis, Ch and Liakopoulos, V. and Stavridou, D. and Katsigiannis, Panagiotis and Alexandridis, Thomas and Zalidis, G.}, month = jun, year = {2015}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\FYH62K9C\\Misopolinos et al. - 2015 - Development of a UAV system for VNIR-TIR acquisiti.pdf:application/pdf}, } @article{maes_perspectives_2019, title = {Perspectives for {Remote} {Sensing} with {Unmanned} {Aerial} {Vehicles} in {Precision} {Agriculture}}, volume = {24}, issn = {1360-1385}, url = {https://www.sciencedirect.com/science/article/pii/S1360138518302693}, doi = {10.1016/j.tplants.2018.11.007}, abstract = {Remote sensing with unmanned aerial vehicles (UAVs) is a game-changer in precision agriculture. It offers unprecedented spectral, spatial, and temporal resolution, but can also provide detailed vegetation height data and multiangular observations. In this article, we review the progress of remote sensing with UAVs in drought stress, in weed and pathogen detection, in nutrient status and growth vigor assessment, and in yield prediction. To transfer this knowledge to everyday practice of precision agriculture, future research should focus on exploiting the complementarity of hyperspectral or multispectral data with thermal data, on integrating observations into robust transfer or growth models rather than linear regression models, and on combining UAV products with other spatially explicit information.}, language = {en}, number = {2}, urldate = {2021-08-17}, journal = {Trends in Plant Science}, author = {Maes, Wouter H. and Steppe, Kathy}, month = feb, year = {2019}, keywords = {UAV, agriculture, multispectral, thermal, hyperspectral, drone}, pages = {152--164}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JQUYTXQI\\S1360138518302693.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\3UWL5LK9\\Maes and Steppe - 2019 - Perspectives for Remote Sensing with Unmanned Aeri.pdf:application/pdf}, } @article{ji_simultaneous_2019, title = {Simultaneous measurement of multiple soil properties through proximal sensor data fusion: {A} case study}, volume = {341}, issn = {0016-7061}, shorttitle = {Simultaneous measurement of multiple soil properties through proximal sensor data fusion}, url = {https://www.sciencedirect.com/science/article/pii/S0016706117311217}, doi = {10.1016/j.geoderma.2019.01.006}, abstract = {In this research, proximal soil sensor data fusion was defined as a multifaceted process which integrates geospatially correlated data, or information, from multiple proximal soil sensors to accurately characterize the spatial complexity of soils. This has capability of providing improved understanding of soil heterogeneity for potential applications associated with crop production and natural resource management. To assess the potential of data fusion for the purpose of improving thematic soil mapping over the single sensor approach, data from multiple proximal soil sensors were combined to develop and validate predictive relationships with laboratory-measured soil physical and chemical properties. The work was conducted in an agricultural field with both mineral and organic soils. The integrated data included: topography records obtained using a real-time kinetic (RTK) global navigation satellite system (GNSS) receiver, apparent soil electrical conductivity (ECa) obtained using an electromagnetic induction sensor, and content of several naturally occurring radioisotopes detected using a mobile gamma-ray spectrometer. In addition, the soil profile data were collected using a commercial ruggedized multi-sensor platform carrying a visible and near-infrared (vis-NIR) optical sensor and a galvanic contact soil ECa sensor. The measurements were carried out at predefined field locations covering the entire study area identified from sensor measured a priori information on field elevation, ECa and gamma-ray count. The information was used to predict: soil organic matter (SOM), pH, lime buffer capacity (LBC), as well as concentration of phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and aluminum (Al). Partial least squares regressions (PLSRs) were used to predict soil properties from individual sensors and different sensor combinations (sensor data fusion). By integrating the data from all of the proximal soil sensors, SOM, pH, LBC, Ca, Mg, and Al were predicted simultaneously with R2 {\textgreater} 0.5 (RPD {\textgreater} 1.50). Improved predictions were observed for most soil properties based on sensor data fusion than those based on individual sensors. After choosing the optimal sensor combination for each soil property, the predictive capability was compared using different data mining algorithms, including support vector machines (SVM), random forest (RF), multivariate adaptive regression splines (MARS), and regression trees (CART). Improved predictions for SOM, Ca, Mg, and Al were observed using SVM over PLSR. The predictive capability was followed by RF and MARS, with CART. Predictions of pH and LBC were only feasible using MARS and PLSR, respectively. In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. With large variability in SOM, the field presents a special situation and thus, the result could be specific to the study site. Further research includes an extended number of experimental sites covering different geographic areas around Eastern Canada.}, language = {en}, urldate = {2021-08-17}, journal = {Geoderma}, author = {Ji, Wenjun and Adamchuk, Viacheslav I. and Chen, Songchao and Mat Su, Ahmad S. and Ismail, Ashraf and Gan, Qianjun and Shi, Zhou and Biswas, Asim}, month = may, year = {2019}, keywords = {Data fusion, Apparent electrical conductivity, Data mining algorithms, Gamma-ray, Partial least square regression, Sensor fusion, Vis-NIR spectroscopy}, pages = {111--128}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\NU29S4QD\\S0016706117311217.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\FQ54AYAE\\Ji et al. - 2019 - Simultaneous measurement of multiple soil properti.pdf:application/pdf}, } @article{angelopoulou_remote_2019, title = {Remote {Sensing} {Techniques} for {Soil} {Organic} {Carbon} {Estimation}: {A} {Review}}, volume = {11}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Remote {Sensing} {Techniques} for {Soil} {Organic} {Carbon} {Estimation}}, url = {https://www.mdpi.com/2072-4292/11/6/676}, doi = {10.3390/rs11060676}, abstract = {Towards the need for sustainable development, remote sensing (RS) techniques in the Visible-Near Infrared\–Shortwave Infrared (VNIR\–SWIR, 400\–2500 nm) region could assist in a more direct, cost-effective and rapid manner to estimate important indicators for soil monitoring purposes. Soil reflectance spectroscopy has been applied in various domains apart from laboratory conditions, e.g., sensors mounted on satellites, aircrafts and Unmanned Aerial Systems. The aim of this review is to illustrate the research made for soil organic carbon estimation, with the use of RS techniques, reporting the methodology and results of each study. It also aims to provide a comprehensive introduction in soil spectroscopy for those who are less conversant with the subject. In total, 28 journal articles were selected and further analysed. It was observed that prediction accuracy reduces from Unmanned Aerial Systems (UASs) to satellite platforms, though advances in machine learning techniques could further assist in the generation of better calibration models. There are some challenges concerning atmospheric, radiometric and geometric corrections, vegetation cover, soil moisture and roughness that still need to be addressed. The advantages and disadvantages of each approach are highlighted and future considerations are also discussed at the end.}, language = {en}, number = {6}, urldate = {2021-08-17}, journal = {Remote Sensing}, author = {Angelopoulou, Theodora and Tziolas, Nikolaos and Balafoutis, Athanasios and Zalidis, George and Bochtis, Dionysis}, month = jan, year = {2019}, note = {Number: 6 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {machine learning, earth observation, soil organic carbon, soil spectroscopy, VNIR–SWIR}, pages = {676}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\FN5NMPIM\\676.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\79V28SCY\\Angelopoulou et al. - 2019 - Remote Sensing Techniques for Soil Organic Carbon .pdf:application/pdf}, } @article{mulla_twenty_2013, series = {Special {Issue}: {Sensing} {Technologies} for {Sustainable} {Agriculture}}, title = {Twenty five years of remote sensing in precision agriculture: {Key} advances and remaining knowledge gaps}, volume = {114}, issn = {1537-5110}, shorttitle = {Twenty five years of remote sensing in precision agriculture}, url = {https://www.sciencedirect.com/science/article/pii/S1537511012001419}, doi = {10.1016/j.biosystemseng.2012.08.009}, abstract = {Precision agriculture dates back to the middle of the 1980's. Remote sensing applications in precision agriculture began with sensors for soil organic matter, and have quickly diversified to include satellite, aerial, and hand held or tractor mounted sensors. Wavelengths of electromagnetic radiation initially focused on a few key visible or near infrared bands. Today, electromagnetic wavelengths in use range from the ultraviolet to microwave portions of the spectrum, enabling advanced applications such as light detection and ranging (LiDAR), fluorescence spectroscopy, and thermal spectroscopy, along with more traditional applications in the visible and near infrared portions of the spectrum. Spectral bandwidth has decreased dramatically with the advent of hyperspectral remote sensing, allowing improved analysis of specific compounds, molecular interactions, crop stress, and crop biophysical or biochemical characteristics. A variety of spectral indices now exist for various precision agriculture applications, rather than a focus on only normalised difference vegetation indices. Spatial resolution of aerial and satellite remote sensing imagery has improved from 100's of m to sub-metre accuracy, allowing evaluation of soil and crop properties at fine spatial resolution at the expense of increased data storage and processing requirements. Temporal frequency of remote sensing imagery has also improved dramatically. At present there is considerable interest in collecting remote sensing data at multiple times in order to conduct near real time soil, crop and pest management.}, language = {en}, number = {4}, urldate = {2021-08-15}, journal = {Biosystems Engineering}, author = {Mulla, David J.}, month = apr, year = {2013}, keywords = {remote sensing, precision agriculture}, pages = {358--371}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\SYSPSPSQ\\Mulla - 2013 - Twenty five years of remote sensing in precision a.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\2VZ7NY5C\\S1537511012001419.html:text/html}, } @article{sishodia_applications_2020, title = {Applications of {Remote} {Sensing} in {Precision} {Agriculture}: {A} {Review}}, volume = {12}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Applications of {Remote} {Sensing} in {Precision} {Agriculture}}, url = {https://www.mdpi.com/2072-4292/12/19/3136}, doi = {10.3390/rs12193136}, abstract = {Agriculture provides for the most basic needs of humankind: food and fiber. The introduction of new farming techniques in the past century (e.g., during the Green Revolution) has helped agriculture keep pace with growing demands for food and other agricultural products. However, further increases in food demand, a growing population, and rising income levels are likely to put additional strain on natural resources. With growing recognition of the negative impacts of agriculture on the environment, new techniques and approaches should be able to meet future food demands while maintaining or reducing the environmental footprint of agriculture. Emerging technologies, such as geospatial technologies, Internet of Things (IoT), Big Data analysis, and artificial intelligence (AI), could be utilized to make informed management decisions aimed to increase crop production. Precision agriculture (PA) entails the application of a suite of such technologies to optimize agricultural inputs to increase agricultural production and reduce input losses. Use of remote sensing technologies for PA has increased rapidly during the past few decades. The unprecedented availability of high resolution (spatial, spectral and temporal) satellite images has promoted the use of remote sensing in many PA applications, including crop monitoring, irrigation management, nutrient application, disease and pest management, and yield prediction. In this paper, we provide an overview of remote sensing systems, techniques, and vegetation indices along with their recent (2015\–2020) applications in PA. Remote-sensing-based PA technologies such as variable fertilizer rate application technology in Green Seeker and Crop Circle have already been incorporated in commercial agriculture. Use of unmanned aerial vehicles (UAVs) has increased tremendously during the last decade due to their cost-effectiveness and flexibility in obtaining the high-resolution (cm-scale) images needed for PA applications. At the same time, the availability of a large amount of satellite data has prompted researchers to explore advanced data storage and processing techniques such as cloud computing and machine learning. Given the complexity of image processing and the amount of technical knowledge and expertise needed, it is critical to explore and develop a simple yet reliable workflow for the real-time application of remote sensing in PA. Development of accurate yet easy to use, user-friendly systems is likely to result in broader adoption of remote sensing technologies in commercial and non-commercial PA applications.}, language = {en}, number = {19}, urldate = {2021-08-08}, journal = {Remote Sensing}, author = {Sishodia, Rajendra P. and Ray, Ram L. and Singh, Sudhir K.}, month = jan, year = {2020}, note = {Number: 19 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {UAV, water management, vegetation indices, satellite remote sensing, big data analysis, disease and pest management, nutrient management, Precision Agriculture, Remote Sensing}, pages = {3136}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\KTFH67G3\\Sishodia et al. - 2020 - Applications of Remote Sensing in Precision Agricu.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JQM2JXBL\\3136.html:text/html}, } @incollection{caballero_chapter_2020, series = {Hyperspectral {Imaging}}, title = {Chapter 3.3 - {Hyperspectral} imaging in crop fields: precision agriculture}, volume = {32}, shorttitle = {Chapter 3.3 - {Hyperspectral} imaging in crop fields}, url = {https://www.sciencedirect.com/science/article/pii/B9780444639776000183}, abstract = {Precision agriculture is starting to play a key role in the new generation of modern agricultural revolution. Farmers are increasingly aware of the importance of maintaining direct control of several fundamental aspects such as the state of health of crops, the amount of water or fertilizer, and possible infections that can develop in the field. Hyperspectral imaging (HSI) and multispectral imaging (MSI) have been applied for these matters for some decades. Nevertheless, there are still several technological and practical barriers to face. This chapter provides an overview of some of the relevant scientific literature related to the application of HSI and MSI on crop fields. Some of the applications are related to the detection of contaminants and heavy metals, the control and assessment of water sources, and the detection of the health status of the fields. The main advantages and constraints and the methods to acquire the images (by using satellites or aerial vehicles) are also shown and discussed.}, language = {en}, urldate = {2021-08-30}, booktitle = {Data {Handling} in {Science} and {Technology}}, publisher = {Elsevier}, author = {Caballero, Daniel and Calvini, Rosalba and Amigo, José Manuel}, editor = {Amigo, José Manuel}, month = jan, year = {2020}, doi = {10.1016/B978-0-444-63977-6.00018-3}, keywords = {Precision agriculture, Hyperspectral imaging, Chemometrics, Field programmable gate arrays, Heavy metal pollution, Multispectral images}, pages = {453--473}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\Q4NMIIVV\\B9780444639776000183.html:text/html}, } @article{aneece_hyperspectral_nodate, title = {Hyperspectral {Remote} {Sensing} of {Agriculture} and {Vegetation} 50-{Years} of {Knowledge} {Advances} and {Knowledge} {Gaps}}, language = {en}, author = {Aneece, Itiya and Teluguntla, Pardhasaradhi and Oliphant, Adam and Foley, Daniel}, pages = {60}, file = {Aneece et al. - Hyperspectral Remote Sensing of Agriculture and Ve.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\P9XHMWA7\\Aneece et al. - Hyperspectral Remote Sensing of Agriculture and Ve.pdf:application/pdf}, } @article{adao_hyperspectral_2017, title = {Hyperspectral {Imaging}: {A} {Review} on {UAV}-{Based} {Sensors}, {Data} {Processing} and {Applications} for {Agriculture} and {Forestry}}, volume = {9}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Hyperspectral {Imaging}}, url = {https://www.mdpi.com/2072-4292/9/11/1110}, doi = {10.3390/rs9111110}, abstract = {Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors’ ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestry—wherein the combination of UAV and hyperspectral sensors plays a center role—is presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processing—by isolating the common user from the processes’ mathematical complexity—several available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper’s conclusions.}, language = {en}, number = {11}, urldate = {2021-08-20}, journal = {Remote Sensing}, author = {Adão, Telmo and Hruška, Jonáš and Pádua, Luís and Bessa, José and Peres, Emanuel and Morais, Raul and Sousa, Joaquim João}, month = nov, year = {2017}, note = {Number: 11 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {UAV, forestry, agriculture, hyperspectral sensors, UAS, hyperspectral, agroforestry, hyperspectral data processing}, pages = {1110}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\V7JAN6WQ\\Adão et al. - 2017 - Hyperspectral Imaging A Review on UAV-Based Senso.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\545HIJ8B\\1110.html:text/html}, } @misc{noauthor_agricultural_nodate, title = {Agricultural {Remote} {Sensing} {Basics} — {Publications}}, url = {https://www.ag.ndsu.edu/publications/crops/agricultural-remote-sensing-basics}, urldate = {2021-08-17}, keywords = {remote sensing, agriculture, basics}, file = {Agricultural Remote Sensing Basics — Publications:C\:\\Users\\Edify 01\\Zotero\\storage\\ZD7B69WA\\agricultural-remote-sensing-basics.html:text/html;Agricultural Remote Sensing Basics — Publications.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\Y7LGL5L2\\Agricultural Remote Sensing Basics — Publications.pdf:application/pdf}, } @article{weiss_remote_2020, title = {Remote sensing for agricultural applications: {A} meta-review}, volume = {236}, issn = {0034-4257}, shorttitle = {Remote sensing for agricultural applications}, url = {https://www.sciencedirect.com/science/article/pii/S0034425719304213}, doi = {10.1016/j.rse.2019.111402}, abstract = {Agriculture provides humanity with food, fibers, fuel, and raw materials that are paramount for human livelihood. Today, this role must be satisfied within a context of environmental sustainability and climate change, combined with an unprecedented and still-expanding human population size, while maintaining the viability of agricultural activities to ensure both subsistence and livelihoods. Remote sensing has the capacity to assist the adaptive evolution of agricultural practices in order to face this major challenge, by providing repetitive information on crop status throughout the season at different scales and for different actors. We start this review by making an overview of the current remote sensing techniques relevant for the agricultural context. We present the agronomical variables and plant traits that can be estimated by remote sensing, and we describe the empirical and deterministic approaches to retrieve them. A second part of this review illustrates recent research developments that permit to strengthen applicative capabilities in remote sensing according to specific requirements for different types of stakeholders. Such agricultural applications include crop breeding, agricultural land use monitoring, crop yield forecasting, as well as ecosystem services in relation to soil and water resources or biodiversity loss. Finally, we provide a synthesis of the emerging opportunities that should strengthen the role of remote sensing in providing operational, efficient and long-term services for agricultural applications.}, language = {en}, urldate = {2021-08-17}, journal = {Remote Sensing of Environment}, author = {Weiss, M. and Jacob, F. and Duveiller, G.}, month = jan, year = {2020}, keywords = {Remote sensing, Land use, Agriculture, Crop, Precision farming, Ecosystem services, Machine learning, Yield, Assimilation, Deep learning, Inversion, Land cover, Phenotyping, Radiative transfer model, Review, Traits}, pages = {111402}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\SDAMTV2D\\S0034425719304213.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\IWWMXAKQ\\Weiss et al. - 2020 - Remote sensing for agricultural applications A me.pdf:application/pdf}, } @misc{noauthor_5_2021, title = {5 {Ways} {To} {Use} {Multispectral} {Imagery} in {Agriculture}}, url = {https://coptrz.com/14-ways-to-use-multispectral-imagery-in-agriculture/}, abstract = {The use of new technologies in agriculture is playing a key role in improving the efficiency of farming operations. The specifics on how multispectral imagery improves efficiency are detailed in this blog.}, language = {en-GB}, urldate = {2021-08-08}, journal = {COPTRZ}, month = may, year = {2021}, keywords = {Satellite, Precision Agriculture, Remote Sensing}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\QVRNBURB\\14-ways-to-use-multispectral-imagery-in-agriculture.html:text/html}, } @article{lu_recent_2020, title = {Recent {Advances} of {Hyperspectral} {Imaging} {Technology} and {Applications} in {Agriculture}}, volume = {12}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/12/16/2659}, doi = {10.3390/rs12162659}, abstract = {Remote sensing is a useful tool for monitoring spatio-temporal variations of crop morphological and physiological status and supporting practices in precision farming. In comparison with multispectral imaging, hyperspectral imaging is a more advanced technique that is capable of acquiring a detailed spectral response of target features. Due to limited accessibility outside of the scientific community, hyperspectral images have not been widely used in precision agriculture. In recent years, different mini-sized and low-cost airborne hyperspectral sensors (e.g., Headwall Micro-Hyperspec, Cubert UHD 185-Firefly) have been developed, and advanced spaceborne hyperspectral sensors have also been or will be launched (e.g., PRISMA, DESIS, EnMAP, HyspIRI). Hyperspectral imaging is becoming more widely available to agricultural applications. Meanwhile, the acquisition, processing, and analysis of hyperspectral imagery still remain a challenging research topic (e.g., large data volume, high data dimensionality, and complex information analysis). It is hence beneficial to conduct a thorough and in-depth review of the hyperspectral imaging technology (e.g., different platforms and sensors), methods available for processing and analyzing hyperspectral information, and recent advances of hyperspectral imaging in agricultural applications. Publications over the past 30 years in hyperspectral imaging technology and applications in agriculture were thus reviewed. The imaging platforms and sensors, together with analytic methods used in the literature, were discussed. Performances of hyperspectral imaging for different applications (e.g., crop biophysical and biochemical properties’ mapping, soil characteristics, and crop classification) were also evaluated. This review is intended to assist agricultural researchers and practitioners to better understand the strengths and limitations of hyperspectral imaging to agricultural applications and promote the adoption of this valuable technology. Recommendations for future hyperspectral imaging research for precision agriculture are also presented.}, language = {en}, number = {16}, urldate = {2021-08-30}, journal = {Remote Sensing}, author = {Lu, Bing and Dao, Phuong D. and Liu, Jiangui and He, Yuhong and Shang, Jiali}, month = jan, year = {2020}, note = {Number: 16 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {remote sensing, soil characteristics, precision agriculture, analytical methods, classification of agricultural features, crop properties, hyperspectral imaging, platforms and sensors}, pages = {2659}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\LK7WWDYU\\2659.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\5IVJH6R4\\Lu et al. - 2020 - Recent Advances of Hyperspectral Imaging Technolog.pdf:application/pdf}, } @book{thenkabail_advanced_2018, address = {Boca Raton}, edition = {2}, title = {Advanced {Applications} in {Remote} {Sensing} of {Agricultural} {Crops} and {Natural} {Vegetation}: {Hyperspectral} {Remote} {Sensing} of {Vegetation} {Second} {Edition} {Volume} {IV}}, isbn = {978-0-429-43116-6}, shorttitle = {Advanced {Applications} in {Remote} {Sensing} of {Agricultural} {Crops} and {Natural} {Vegetation}}, abstract = {Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection. It emphasizes the importance of hyperspectral remote sensing tools for studying vegetation processes and functions as well as the appropriate use of hyperspectral data for vegetation management practices. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume IV through the editors’ perspective. Key Features of Volume IV: Guides readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Includes specific applications on agriculture, crop management practices, study of crop stress and diseases, crop characteristics based on inputs (e.g., nitrogen, irrigation), study of vegetation impacted by heavy metals, gross and net primary productivity studies, light use efficiency studies, crop water use and actual evapotranspiration studies, phenology monitoring, land use and land cover studies, global change studies, plant species detection, wetland and forest characterization and mapping, crop productivity and crop water productivity mapping, and modeling. Encompasses hyperspectral or imaging spectroscopy data in narrow wavebands used across visible, red-edge, near-infrared, far-infrared, shortwave infrared, and thermal portions of the spectrum. Explains the implementation of hyperspectral remote sensing data processing mechanisms in a standard, fast, and efficient manner for their applications. Discusses cloud computing to overcome hyperspectral remote sensing massive big data challenges. Provides hyperspectral analysis of rocky surfaces on the earth and other planetary systems.}, publisher = {CRC Press}, editor = {Thenkabail, Prasad S. and Lyon, John G. and Huete, Alfredo}, month = dec, year = {2018}, doi = {10.1201/9780429431166}, file = {Thenkabail et al. - 2018 - Advanced Applications in Remote Sensing of Agricul.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\TM2L3YYY\\Thenkabail et al. - 2018 - Advanced Applications in Remote Sensing of Agricul.pdf:application/pdf}, } @incollection{yu_14_2020, series = {Earth {Observation}}, title = {14 - {Hyperspectral} remote sensing applications in soil: a review}, isbn = {978-0-08-102894-0}, shorttitle = {14 - {Hyperspectral} remote sensing applications in soil}, url = {https://www.sciencedirect.com/science/article/pii/B9780081028940000115}, abstract = {Hyperspectral remote sensing (HRS) enables a precise recording of the spectrum and a detailed analysis of the spectral properties of soil. There is a wealth of published research on HRS applications in soil research from the past 40 years, therefore, a review and illustration of the developments is critical for a better understanding of its opportunities and challenges for future development. This study reviewed the state-of-the-art regarding the applications of HRS for the extraction of soil properties including mineral identification, nutrient, organic carbon, moisture, salinity, and soil texture, then identify the opportunities and challenges and provide suggestions of a new direction for advancing its development. The results obtained provide new insights into the theory and methodology of HRS for studying soil attributes, but there is much work to be done, both experimentally and theoretically, before the physical and chemical processes predicting these soil parameters can full be understood. At the end of the chapter, new directions of studying soil properties using HRS are suggested, for example, new data mining technologies such as deep learning provide opportunities for efficient processing of large amounts of HRS data; the interactional mechanism of vegetation and soil should also be integrated into the construction of HRS monitoring models; the development from the empirical model to physical model will improve the universality and robustness of a given model; more attention should be paid to the application of multivariate models involving multiple parameters, rather than to single-factor models; by combining the temporal and dynamic characteristics of soil attributes with the process of vegetation growth, the accuracy of detecting and monitoring soil attributes will be greatly improved; and multidata fusion and multiscale data assimilation will become another research hotspot in HRS monitoring of soil properties.}, language = {en}, urldate = {2021-08-17}, booktitle = {Hyperspectral {Remote} {Sensing}}, publisher = {Elsevier}, author = {Yu, Huan and Kong, Bo and Wang, Qing and Liu, Xian and Liu, Xiangmeng}, editor = {Pandey, Prem Chandra and Srivastava, Prashant K. and Balzter, Heiko and Bhattacharya, Bimal and Petropoulos, George P.}, month = jan, year = {2020}, doi = {10.1016/B978-0-08-102894-0.00011-5}, keywords = {soil texture, soil organic carbon, Hyperspectral remote sensing, mineral identification, soil moisture, soil nutrient, soil salinity}, pages = {269--291}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\XV52XXLZ\\Yu et al. - 2020 - 14 - Hyperspectral remote sensing applications in .pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\DNWGGKKH\\B9780081028940000115.html:text/html}, } @incollection{singh_08_2020, series = {Earth {Observation}}, title = {08 - {Hyperspectral} remote sensing in precision agriculture: present status, challenges, and future trends}, isbn = {978-0-08-102894-0}, shorttitle = {8 - {Hyperspectral} remote sensing in precision agriculture}, url = {https://www.sciencedirect.com/science/article/pii/B9780081028940000097}, abstract = {The rapid development of remote sensing has made it possible to study environmental processes and changes in agriculture and also to provide important assistance in relevant practices, even operationally. This chapter describes the latest developments in remote sensing for precision agriculture with particular emphasis placed on the use of hyperspectral sensors. This chapter provides practical information regarding the identification of research challenges, limitations, and advantages of different platforms and sensors for precision agriculture. Hyperspectral remote sensing (HRS) is more effective as compared to multispectral remote sensing because it records radiation in narrow contiguous spectral channels reflected from any feature or target. More accurate spectral information retrieved using HRS can be combined with other techniques to retrieve useful information for precision agriculture. The chapter includes information about HRS sensors and also includes a discussion on the advancement and challenges of spaceborne satellites faced during agriculture monitoring. It concludes with summarizing the hurdles faced during agriculture research using hyperspectral data discussing possible pathways in which relevant research should be directed.}, language = {en}, urldate = {2021-08-17}, booktitle = {Hyperspectral {Remote} {Sensing}}, publisher = {Elsevier}, author = {Singh, Prachi and Pandey, Prem Chandra and Petropoulos, George P. and Pavlides, Andrew and Srivastava, Prashant K. and Koutsias, Nikos and Deng, Khidir Abdala Kwal and Bao, Yangson}, editor = {Pandey, Prem Chandra and Srivastava, Prashant K. and Balzter, Heiko and Bhattacharya, Bimal and Petropoulos, George P.}, month = jan, year = {2020}, doi = {10.1016/B978-0-08-102894-0.00009-7}, keywords = {Remote sensing, precision agriculture, hyperspectral remote sensing, unmanned aerial vehicles}, pages = {121--146}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HXVDD6NF\\Singh et al. - 2020 - 8 - Hyperspectral remote sensing in precision agri.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\GFVDRWFC\\B9780081028940000097.html:text/html}, } @article{lambers_integrating_2019, title = {Integrating {Remote} {Sensing}, {Machine} {Learning}, and {Citizen} {Science} in {Dutch} {Archaeological} {Prospection}}, volume = {11}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/11/7/794}, doi = {10.3390/rs11070794}, abstract = {Although the history of automated archaeological object detection in remotely sensed data is short, progress and emerging trends are evident. Among them, the shift from rule-based approaches towards machine learning methods is, at the moment, the cause for high expectations, even though basic problems, such as the lack of suitable archaeological training data are only beginning to be addressed. In a case study in the central Netherlands, we are currently developing novel methods for multi-class archaeological object detection in LiDAR data based on convolutional neural networks (CNNs). This research is embedded in a long-term investigation of the prehistoric landscape of our study region. We here present an innovative integrated workflow that combines machine learning approaches to automated object detection in remotely sensed data with a two-tier citizen science project that allows us to generate and validate detections of hitherto unknown archaeological objects, thereby contributing to the creation of reliable, labeled archaeological training datasets. We motivate our methodological choices in the light of current trends in archaeological prospection, remote sensing, machine learning, and citizen science, and present the first results of the implementation of the workflow in our research area.}, language = {en}, number = {7}, urldate = {2021-08-27}, journal = {Remote Sensing}, author = {Lambers, Karsten and Verschoof-van der Vaart, Wouter B. and Bourgeois, Quentin P. J.}, month = jan, year = {2019}, note = {Number: 7 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {deep learning, airborne laser scanning, archaeological prospection, citizen science, The Netherlands}, pages = {794}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\GK9K4MEN\\794.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\7XHSY49E\\Lambers et al. - 2019 - Integrating Remote Sensing, Machine Learning, and .pdf:application/pdf}, } @article{borie_beyond_2019, title = {Beyond {Site} {Detection}: {The} {Role} of {Satellite} {Remote} {Sensing} in {Analysing} {Archaeological} {Problems}. {A} {Case} {Study} in {Lithic} {Resource} {Procurement} in the {Atacama} {Desert}, {Northern} {Chile}}, volume = {11}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Beyond {Site} {Detection}}, url = {https://www.mdpi.com/2072-4292/11/7/869}, doi = {10.3390/rs11070869}, abstract = {Remote sensing archaeology in recent years has emphasized the use of high-precision and high-accuracy tools to achieve the detailed documentation of archaeological elements (drones, LIDAR, etc.). Satellite remote sensing has also benefited from an increase in the spatial and spectral resolution of the sensors, which is enabling the discovery and documentation of new archaeological features and sites worldwide. While there can be no doubt that a great deal is being gained via such \“site detection\” approaches, there still remains the possibility of further exploring remote sensing methods to analyse archaeological problems. In this paper, this issue is discussed by focusing on one common archaeological topic: the mapping of environmental resources used in the past and, in particular, the procurement of lithic raw material by hunter-gatherer groups. This is illustrated by showing how the combined use of Landsat 8 images and \“ground-truthing\” via focused field studies has allowed the identification of a number of potential chert sources, the major lithic resource used by coastal groups between 11,500\–1,500 cal. BP, in a vast area of the Atacama Desert covering 22,500 km2. Besides discussing the case study, the strength of remote sensing techniques in addressing archaeological questions comprising large spatial scales is highlighted, stressing the key role they can play in the detection and study of specific environmental resources within challenging physical settings.}, language = {en}, number = {7}, urldate = {2021-08-27}, journal = {Remote Sensing}, author = {Borie, César and Parcero-Oubiña, César and Kwon, Youngsang and Salazar, Diego and Flores, Carola and Olguín, Laura and Andrade, Pedro}, month = jan, year = {2019}, note = {Number: 7 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {archaeology, GIS, satellite remote sensing, arid environments, chert sourcing, Landsat 8, lithic procurement, lithological mapping}, pages = {869}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\RL2ZI89S\\Borie et al. - 2019 - Beyond Site Detection The Role of Satellite Remot.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ETKAH8BE\\869.html:text/html}, } @article{guyot_airborne_2019, title = {Airborne {Hyperspectral} {Imaging} for {Submerged} {Archaeological} {Mapping} in {Shallow} {Water} {Environments}}, volume = {11}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/11/19/2237}, doi = {10.3390/rs11192237}, abstract = {Nearshore areas around the world contain a wide variety of archeological structures, including prehistoric remains submerged by sea level rise during the Holocene glacial retreat. While natural processes, such as erosion, rising sea level, and exceptional climatic events have always threatened the integrity of this submerged cultural heritage, the importance of protecting them is becoming increasingly critical with the expanding effects of global climate change and human activities. Aerial archaeology, as a non-invasive technique, contributes greatly to documentation of archaeological remains. In an underwater context, the difficulty of crossing the water column to reach the bottom and its potential archaeological information usually requires active remote-sensing technologies such as airborne LiDAR bathymetry or ship-borne acoustic soundings. More recently, airborne hyperspectral passive sensors have shown potential for accessing water-bottom information in shallow water environments. While hyperspectral imagery has been assessed in terrestrial continental archaeological contexts, this study brings new perspectives for documenting submerged archaeological structures using airborne hyperspectral remote sensing. Airborne hyperspectral data were recorded in the Visible Near Infra-Red (VNIR) spectral range (400–1000 nm) over the submerged megalithic site of Er Lannic (Morbihan, France). The method used to process these data included (i) visualization of submerged anomalous features using a minimum noise fraction transform, (ii) automatic detection of these features using Isolation Forest and the Reed–Xiaoli detector and (iii) morphological and spectral analysis of archaeological structures from water-depth and water-bottom reflectance derived from the inversion of a radiative transfer model of the water column. The results, compared to archaeological reference data collected from in-situ archaeological surveys, showed for the first time the potential of airborne hyperspectral imagery for archaeological mapping in complex shallow water environments.}, language = {en}, number = {19}, urldate = {2021-08-27}, journal = {Remote Sensing}, author = {Guyot, Alexandre and Lennon, Marc and Thomas, Nicolas and Gueguen, Simon and Petit, Tristan and Lorho, Thierry and Cassen, Serge and Hubert-Moy, Laurence}, month = jan, year = {2019}, note = {Number: 19 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {anomaly detection, cultural heritage monitoring, hyperspectral data, MNF, radiative transfer model, submerged areas}, pages = {2237}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\QIK2CBAF\\2237.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\LAGH84RQ\\Guyot et al. - 2019 - Airborne Hyperspectral Imaging for Submerged Archa.pdf:application/pdf}, } @article{raczkowski_power_2020, title = {Power and/or {Penury} of {Visualizations}: {Some} {Thoughts} on {Remote} {Sensing} {Data} and {Products} in {Archaeology}}, volume = {12}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Power and/or {Penury} of {Visualizations}}, url = {https://www.mdpi.com/2072-4292/12/18/2996}, doi = {10.3390/rs12182996}, abstract = {Airborne and spaceborne remote sensing in archaeology generates at least two important issues for discussion: technology and visualization. Technology seems to open new cognitive perspectives for archaeology and keeps researchers increasingly fascinated in its capabilities (archaeological science being a case in point). Acquired data, especially via remote sensing methods, can be studied after processing and visualizing. The paper raises several issues related to the new cognitive situation of archaeologists facing the development of new technologies within remote sensing methods. These issues are discussed from ontological, epistemological, and discursive perspectives, supporting an exploration of the role of technology and visualization. The ontological perspective places the visualization of remote sensing data in the context of understanding Virtual Reality and Jean Baudrillard\’s simulacra. The epistemological perspective generates questions related to visualization as mimesis, the issue of cultural neutrality, and the use of sophisticated classifications and analytical techniques. The level of discursiveness of visualization includes categories such as persuasion, standardization, and aesthetics. This discussion is framed in relation to Martin Heidegger\’s understanding of technology and a dichotomy of naturalism versus antinaturalism.}, language = {en}, number = {18}, urldate = {2021-08-27}, journal = {Remote Sensing}, author = {Rączkowski, Włodzimierz}, month = jan, year = {2020}, note = {Number: 18 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {visualization, remote sensing archaeology, cultural context, Martin Heidegger, mimesis, technology}, pages = {2996}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JSE9VT6W\\2996.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\2FXX6HY8\\Rączkowski - 2020 - Power andor Penury of Visualizations Some Though.pdf:application/pdf}, } @incollection{pandey_21_2020, series = {Earth {Observation}}, title = {21 - {Future} perspectives and challenges in hyperspectral remote sensing}, isbn = {978-0-08-102894-0}, url = {https://www.sciencedirect.com/science/article/pii/B9780081028940000218}, abstract = {Remote sensing (RS) technology has rapidly advanced in terms of radiometric, spatial, and spectral resolution. This trend has led to increasing complexity of data types ranging from low to high spatial and spectral resolutions and data dimensionality. In the chapters of this book, the state of the art has been presented, outlining the advantages of hyperspectral imaging (HSI) systems over multispectral data, and key future challenges and research directions with HSI have been illustrated. This chapter provides a perspective on the evolution of hyperspectral RS methods and applications along with challenges and barriers faced during research and innovation activities. The promise of upcoming missions with higher spatial and spectral resolution sensors in orbit in the near future will increase the utility of hyperspectral data in several research domains and will likely increase the number of users of HSI for soils, forestry, agriculture, urban, and cryosphere research. This chapter is intended as a resource to be aware of challenges and the future potential of hyperspectral RS to current and prospective users of high spectral resolution data to extract meaningful information for their research and applications.}, language = {en}, urldate = {2021-08-17}, booktitle = {Hyperspectral {Remote} {Sensing}}, publisher = {Elsevier}, author = {Pandey, Prem Chandra and Balzter, Heiko and Srivastava, Prashant K. and Petropoulos, George P. and Bhattacharya, Bimal}, editor = {Pandey, Prem Chandra and Srivastava, Prashant K. and Balzter, Heiko and Bhattacharya, Bimal and Petropoulos, George P.}, month = jan, year = {2020}, doi = {10.1016/B978-0-08-102894-0.00021-8}, keywords = {challenges, classification, data dimensionality, endmember extraction, Hyperspectral imaging system, smile effect}, pages = {429--439}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\QSWZ25CX\\B9780081028940000218.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\5NB49NR9\\Pandey et al. - 2020 - 21 - Future perspectives and challenges in hypersp.pdf:application/pdf}, } @article{webber_precision_2019, title = {Precision farming and archaeology}, volume = {11}, issn = {1866-9565}, url = {https://doi.org/10.1007/s12520-017-0564-8}, doi = {10.1007/s12520-017-0564-8}, abstract = {With a significant growth in the agricultural technology industry, a vast amount of agricultural data is now being collected on farms throughout the world. Farmers aim to utilise these technologies to regularly record and manage the variation of crops and soils within their fields, to reduce inputs, increase yields and enhance environmental sustainability. In this paper, we aim to highlight the variety of different data types and methodological processes involved in modern precision farming systems and explore how potentially interconnected these systems are with the archaeological community. At present, no research has studied the effects of archaeological sites on soils in the context of precision farming practices. Yet from modern geophysical, geochemical and remote sensing techniques, a much greater volume of soil- and crop-related mapping is being undertaken, with huge potential for all kinds of archaeological study. From heritage management to archaeological prospection, how will the future of archaeological studies fit into this changing agricultural landscape?}, language = {en}, number = {2}, urldate = {2021-08-21}, journal = {Archaeological and Anthropological Sciences}, author = {Webber, Henry and Heyd, Volker and Horton, Mark and Bell, Martin and Matthews, Wendy and Chadburn, Amanda}, month = feb, year = {2019}, keywords = {Archaeology, Remote sensing, Europe, Precision farming, UK, Geochemistry, Geophysics, Soils}, pages = {727--734}, file = {Springer Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HVWQRS32\\Webber et al. - 2019 - Precision farming and archaeology.pdf:application/pdf}, } @article{sevara_relative_2019, title = {Relative {Radiometric} {Calibration} of {Airborne} {LiDAR} {Data} for {Archaeological} {Applications}}, volume = {11}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/11/8/945}, doi = {10.3390/rs11080945}, abstract = {Airborne laser scanning (ALS) data can provide more than just a topographic data set for archaeological research. During data collection, laser scanning systems also record radiometric information containing object properties, and thus information about archaeological features. Being aware of the physical model of ALS scanning, the radiometric information can be used to calculate material information of the scanned object. The reflectance of an object or material states the amount of energy it reflects for a specific electromagnetic wavelength. However, the collected radiometric data are affected by several factors that cause dissimilar values to be recorded for the same object. Radiometric calibration of such data minimizes these differences in calculated reflectance values of objects, improving their usability for feature detection and visualization purposes. Previous work dealing with calibration of radiometric data in archaeological research has relied on corresponding in-field measurements to acquire calibration values or has only corrected for a limited number of variables. In this paper, we apply a desk-based approach in which radiometric calibration is conducted through the selection of homogenous areas of interest, without the use of in-field measurements. Together with flight and scan parameters, radiometric calibration allows for the estimation of reflectance values for returns of a single full-waveform ALS data collection flight. The resulting data are then processed into a raster reflectance map that approximates a monochromatic illumination-independent true orthoimage at the wavelength of the laser scanner. We apply this approach to data collected for an archaeological research project in western Sicily and discuss the relative merits of the uses of radiometric data in such locations as well as its wider applicability for present and future archaeological and environmental research. In order to make the approach more accessible, we have developed a freely available tool that allows users to apply the calibration procedure to their own data.}, language = {en}, number = {8}, urldate = {2021-08-27}, journal = {Remote Sensing}, author = {Sevara, Christopher and Wieser, Martin and Doneus, Michael and Pfeifer, Norbert}, month = jan, year = {2019}, note = {Number: 8 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {archaeology, ALS, amplitude, radiometric calibration, reflectance, Sicily}, pages = {945}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\7IFJ4BF8\\945.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\6J3WIJV5\\Sevara et al. - 2019 - Relative Radiometric Calibration of Airborne LiDAR.pdf:application/pdf}, } @article{gallwey_bringing_2019, title = {Bringing {Lunar} {LiDAR} {Back} {Down} to {Earth}: {Mapping} {Our} {Industrial} {Heritage} through {Deep} {Transfer} {Learning}}, volume = {11}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Bringing {Lunar} {LiDAR} {Back} {Down} to {Earth}}, url = {https://www.mdpi.com/2072-4292/11/17/1994}, doi = {10.3390/rs11171994}, abstract = {This article presents a novel deep learning method for semi-automated detection of historic mining pits using aerial LiDAR data. The recent emergence of national scale remotely sensed datasets has created the potential to greatly increase the rate of analysis and recording of cultural heritage sites. However, the time and resources required to process these datasets in traditional desktop surveys presents a near insurmountable challenge. The use of artificial intelligence to carry out preliminary processing of vast areas could enable experts to prioritize their prospection focus; however, success so far has been hindered by the lack of large training datasets in this field. This study develops an innovative transfer learning approach, utilizing a deep convolutional neural network initially trained on Lunar LiDAR datasets and reapplied here in an archaeological context. Recall rates of 80\% and 83\% were obtained on the 0.5 m and 0.25 m resolution datasets respectively, with false positive rates maintained below 20\%. These results are state of the art and demonstrate that this model is an efficient, effective tool for semi-automated object detection for this type of archaeological objects. Further tests indicated strong potential for detection of other types of archaeological objects when trained accordingly.}, language = {en}, number = {17}, urldate = {2021-08-27}, journal = {Remote Sensing}, author = {Gallwey, Jane and Eyre, Matthew and Tonkins, Matthew and Coggan, John}, month = jan, year = {2019}, note = {Number: 17 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {deep learning, LiDAR, heritage management, historic mining, transfer learning}, pages = {1994}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\NV454XF2\\1994.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\GNFA839V\\Gallwey et al. - 2019 - Bringing Lunar LiDAR Back Down to Earth Mapping O.pdf:application/pdf}, } @article{cowley_editorial_2021, title = {Editorial for {Special} {Issue}: “{Archaeological} {Remote} {Sensing} in the 21st {Century}: ({Re}){Defining} {Practice} and {Theory}”}, volume = {13}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Editorial for {Special} {Issue}}, url = {https://www.mdpi.com/2072-4292/13/8/1431}, doi = {10.3390/rs13081431}, abstract = {“Beg, borrow and steal”: in many ways, this is a strapline for archaeology as a discipline, and perhaps especially so for archaeological remote sensing [...]}, language = {en}, number = {8}, urldate = {2021-08-27}, journal = {Remote Sensing}, author = {Cowley, Dave and Verhoeven, Geert and Traviglia, Arianna}, month = jan, year = {2021}, note = {Number: 8 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {Europe, n/a, Editorial}, pages = {1431}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\RGR7CBN3\\1431.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\6YQRWT6A\\Cowley et al. - 2021 - Editorial for Special Issue “Archaeological Remot.pdf:application/pdf}, } @book{verhoeven_archaeological_2021, title = {Archaeological {Remote} {Sensing} in the 21st {Century}: ({Re}){Defining} {Practice} and {Theory}}, isbn = {978-3-0365-1376-8}, shorttitle = {Archaeological {Remote} {Sensing} in the 21st {Century}}, abstract = {Despite the many (r)evolutions in remote sensing technology over the past three decades, integration in archaeological practice and theory has sometimes been limited by reliance on practice and theory imported from other disciplines, without questioning or deep understanding. This collection of papers aims to contribute to the exploration of developing practice and theory in remote sensing archaeology for the 21st century. The scope of this volume is the use of remotely sensed data from either air- or spaceborne platforms for the benefit of archaeology and cultural heritage in general, with a specific focus on better defining the roles and contexts that detail why archaeologists may apply remote sensing techniques. With this focus, it is our hope that remotely sensed data will be better and more intrinsically integrated into the symbiosis of archaeological practice and theory. The editorial for this volume suggests that many aspects of archaeological practice can be characterised as ‘beg, borrow and steal’. This collection provides the reader with thoughtful papers that contribute to the development of archaeological remote sensing as a mature interdisciplinary field characterised by explicit and theoretically engaged approaches to understanding the past.}, author = {Verhoeven, Geert and Cowley, David and Traviglia, Arianna}, month = jul, year = {2021}, keywords = {Archaeology, Data fusion, Airborne remote sensing, Europe, Landscape archaeology, Machine learning, Archaeological theory, Cultural resource management, Heritage documentation, Monochromatic, multi- and hyperspectral reflectance and thermal imaging, Pattern recognition and object detection, Photo interpretation, Spaceborne remote sensing, UAS/UAV}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\RPVYAP4V\\Verhoeven et al. - 2021 - Archaeological Remote Sensing in the 21st Century.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\4SWB7VC4\\4243.html:text/html}, } @article{verhoeven_mapping_2012, title = {Mapping by matching: a computer vision-based approach to fast and accurate georeferencing of archaeological aerial photographs}, volume = {39}, issn = {0305-4403}, shorttitle = {Mapping by matching}, url = {https://www.sciencedirect.com/science/article/pii/S0305440312000866}, doi = {10.1016/j.jas.2012.02.022}, abstract = {To date, aerial archaeologists generally apply simple rectification procedures or more expensive and time-consuming orthorectification algorithms to correct their aerial photographs in varying degrees for geometrical deformations induced by the topographical relief, the tilt of the camera axis and the distortion of the optics. Irrespective of the method applied, the georeferencing of the images is commonly determined with ground control points, whose measurement and identification is a time-consuming operation and often limits certain images from being accurately georeferenced. Moreover, specialised software, certain photogrammetric skills, and experience are required. Thanks to the recent advances in the fields of computer vision and photogrammetry as well as the improvements in processing power, it is currently possible to generate orthophotos of large, almost randomly collected aerial photographs in a straightforward and nearly automatic way. This paper presents a computer vision-based approach that is complemented by proven photogrammetric principles to generate orthophotos from a range of uncalibrated oblique and vertical aerial frame images. In a first phase, the method uses algorithms that automatically compute the viewpoint of each photograph as well as a sparse 3D geometric representation of the scene that is imaged. Afterwards, dense reconstruction algorithms are applied to yield a three-dimensional surface model. After georeferencing this model, it can be used to create any kind of orthophoto out of the initial aerial views. To prove the benefits of this approach in comparison to the most common ways of georeferencing aerial imagery, several archaeological case studies are presented. Not only will they showcase the easy workflow and accuracy of the results, but they will also prove that this approach moves beyond current restrictions due to its applicability to datasets that were previously thought to be unsuited for convenient georeferencing.}, language = {en}, number = {7}, urldate = {2021-08-27}, journal = {Journal of Archaeological Science}, author = {Verhoeven, G. and Doneus, M. and Briese, Ch. and Vermeulen, F.}, month = jul, year = {2012}, keywords = {Computer vision, Aerial archaeology, Europe, 3D model, Aerial photograph, Dense multi-view stereo reconstruction, Orthophoto, Structure from motion}, pages = {2060--2070}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\PMIFE57N\\Verhoeven et al. - 2012 - Mapping by matching a computer vision-based appro.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\B6LCSK3A\\S0305440312000866.html:text/html}, } @misc{noauthor_people_nodate, title = {People • {Laboratory} of {Plant} {Ecology}}, url = {https://www.plantecology.ugent.be/people/}, language = {en-US}, urldate = {2021-08-17}, journal = {Laboratory of Plant Ecology}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\WB2W9GW9\\people.html:text/html}, } @article{mcgrath_towards_2020, title = {Towards a {Satellite} {System} for {Archaeology}? {Simulation} of an {Optical} {Satellite} {Mission} with {Ideal} {Spatial} and {Temporal} {Resolution}, {Illustrated} by a {Case} {Study} in {Scotland}}, volume = {12}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Towards a {Satellite} {System} for {Archaeology}?}, url = {https://www.mdpi.com/2072-4292/12/24/4100}, doi = {10.3390/rs12244100}, abstract = {Applications of remote sensing data for archaeology rely heavily on repurposed data, which carry inherent limitations in their suitability to help address archaeological questions. Through a case study framed around archaeological imperatives in a Scottish context, this work investigates the potential for existing satellite systems to provide remote sensing data that meet defined specifications for archaeological prospection, considering both spatial and temporal resolution, concluding that the availability of commercial data is currently insufficient. Tasking a commercial constellation of 12 spacecraft to collect images of a 150 km2 region in Scotland through the month of July 2020 provided 26 images with less than 50\% cloud cover. Following an analysis of existing systems, this paper presents a high-level mission architecture for a bespoke satellite system designed from an archaeological specification. This study focuses on orbit design and the number of spacecraft needed to meet the spatial and temporal resolution requirements for archaeological site detection and monitoring in a case study of Scotland, using existing imaging technology. By exploring what an ideal scenario might look like from a satellite mission planning perspective, this paper presents a simulation analysis that foregrounds archaeological imperatives and specifies a satellite constellation design on that basis. High-level design suggests that a system of eight 100 kg spacecraft in a 581 km altitude orbit could provide coverage at a desired temporal and spatial resolution of two-weekly revisit and \<1 m ground sampling distance, respectively. The potential for such a system to be more widely applied in regions of similar latitude and climate is discussed.}, language = {en}, number = {24}, urldate = {2021-08-27}, journal = {Remote Sensing}, author = {McGrath, Ciara N. and Scott, Charlie and Cowley, Dave and Macdonald, Malcolm}, month = jan, year = {2020}, note = {Number: 24 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {archaeological survey, archaeological remote sensing, satellite archaeology, satellite mission design}, pages = {4100}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\IVKFE98A\\4100.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\BSGEEBDK\\McGrath et al. - 2020 - Towards a Satellite System for Archaeology Simula.pdf:application/pdf}, } @inproceedings{kung_accuracy_2012, title = {{THE} {ACCURACY} {OF} {AUTOMATIC} {PHOTOGRAMMETRIC} {TECHNIQUES} {ON} {ULTRA}-{LIGHT} {UAV} {IMAGERY}}, volume = {XXXVIII-1-C22}, url = {https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-1-C22/125/2011/}, doi = {10.5194/isprsarchives-XXXVIII-1-C22-125-2011}, abstract = {{\textless}p{\textgreater}{\textless}strong class="journal-contentHeaderColor"{\textgreater}Abstract.{\textless}/strong{\textgreater} This paper presents an affordable, fully automated and accurate mapping solutions based on ultra-light UAV imagery. Several datasets are analysed and their accuracy is estimated. We show that the accuracy highly depends on the ground resolution (flying height) of the input imagery. When chosen appropriately this mapping solution can compete with traditional mapping solutions that capture fewer high-resolution images from airplanes and that rely on highly accurate orientation and positioning sensors on board. Due to the careful integration with recent computer vision techniques, the post processing is robust and fully automatic and can deal with inaccurate position and orientation information which are typically problematic with traditional techniques.{\textless}/p{\textgreater}}, language = {English}, urldate = {2021-08-27}, booktitle = {The {International} {Archives} of the {Photogrammetry}, {Remote} {Sensing} and {Spatial} {Information} {Sciences}}, publisher = {Copernicus GmbH}, author = {Küng, O. and Strecha, C. and Beyeler, A. and Zufferey, J.-C. and Floreano, D. and Fua, P. and Gervaix, F.}, month = sep, year = {2012}, note = {ISSN: 1682-1750}, keywords = {UAV, Europe, DEM, Photo reconstruction, aerial triangulation, automated georeferencing, mini-drone, orthomosaic, photogrammetry, Ultra-light UAV}, pages = {125--130}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\TNZLRWKA\\Küng et al. - 2012 - THE ACCURACY OF AUTOMATIC PHOTOGRAMMETRIC TECHNIQU.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\KTH4SPIG\\2011.html:text/html}, } @misc{noauthor_sustainable_nodate, title = {Sustainable {Farming} {Incentive} pilot}, url = {https://www.gov.uk/guidance/sustainable-farming-incentive-pilot}, abstract = {An overview of the Sustainable Farming Incentive pilot scheme, including information on standards, payments, monitoring, inspections and reporting}, language = {en}, urldate = {2021-08-16}, journal = {GOV.UK}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ZQAY5D3P\\sustainable-farming-incentive-pilot.html:text/html}, } @misc{noauthor_measuring_nodate, title = {Measuring • {Laboratory} of {Plant} {Ecology}}, url = {https://www.plantecology.ugent.be/measuring/}, abstract = {Plant sensors and equipment The Laboratory of Plant Ecology is specialized in measuring plant responses and their environment, enabling fast plant stress detection. As official service provider, we offer services and consultancy for sensor installation, calibration and data interpretation. We also provide custom measurement campaigns to answer all your plant related questions. For more information …}, language = {en-US}, urldate = {2021-08-17}, journal = {Laboratory of Plant Ecology}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\4Q534HN6\\measuring.html:text/html}, } @misc{noauthor_str3s_nodate, title = {{STR3S}}, url = {http://www.str3s.org/}, abstract = {A new project looking at the potential of satellite observations of solar induced fluorescence for the understanding of global transpiration}, language = {en}, urldate = {2021-08-17}, journal = {STR3S}, } @article{sidike_dpen_2019, title = {{dPEN}: deep {Progressively} {Expanded} {Network} for mapping heterogeneous agricultural landscape using {WorldView}-3 satellite imagery}, volume = {221}, issn = {0034-4257}, shorttitle = {{dPEN}}, url = {https://www.sciencedirect.com/science/article/pii/S0034425718305406}, doi = {10.1016/j.rse.2018.11.031}, abstract = {Accurately mapping heterogeneous agricultural landscape is an important prerequisite for agricultural field management (e.g., weed control), plant phenotyping and yield prediction, as well as ecological characterization. Compared to traditional mapping practices that require intensive field surveys, remote sensing technologies offer efficient and cost-effective means for crop type mapping from regional to global scales. However, mapping heterogeneous agricultural landscape is a challenge because of diverse and complex spectral profiles of crops. We propose a novel deep learning method, namely deep progressively expanded network (dPEN), for mapping nineteen different objects including crop types, weeds and crop residues, in a heterogeneous agricultural field using WorldView-3 (WV-3) imagery. To assess the mapping accuracy of dPEN, we created a calibrated WV-3 dataset with the corresponding ground truth. In addition, the suitability of visible/near-infrared (VNIR, 400–1040 nm) and short-wave infrared (SWIR, 1195 nm–2365 nm) bands of WV-3 to classification accuracy were examined and discussed in detail. To the best of our knowledge, this is the first effort to explore the significance of all SWIR bands in WV-3 for classification accuracy in a heterogeneous agricultural landscape. The results demonstrated that: (1) The proposed dPEN allows for building a deeper neural network from multispectral data which was the limitation of many convolutional neural networks; (2) dPEN was able to extract more discriminative features from VNIR and SWIR bands by producing the highest overall accuracy (OA: 86.06\%) over competing methods such as support vector machine and random forest; (3) The inclusion of WV-3 SWIR bands greatly improved the classification accuracy; (4) SWIR bands were particularly beneficial to improve the classification accuracy of some individual classes such as weeds, crop residues, and corn and soybean during late developmental stages; (5) The red-edge band (705–745 nm) was identified as the most important band affecting the classification accuracy nearly 10\%, whereas the coastal band (400–450 nm) provided the lowest contribution; and (6) SWIR-5 band (2145–2185 nm) contributed most to OA by enhancing it approximately 4\% when combined with VNIR bands, while SWIR-1 (1195–1225 nm) yielded the lowest improvement (1.55\%) for OA. These research outcomes provide useful information for efficiently mapping agricultural landscape, and indicate the potential practices of dPEN and contributions of spectral bands in WV-3 for plant phenotyping, weed control, and crop residue retention.}, language = {en}, urldate = {2021-08-17}, journal = {Remote Sensing of Environment}, author = {Sidike, Paheding and Sagan, Vasit and Maimaitijiang, Maitiniyazi and Maimaitiyiming, Matthew and Shakoor, Nadia and Burken, Joel and Mockler, Todd and Fritschi, Felix B.}, month = feb, year = {2019}, keywords = {Crops, Weeds, Deep learning, Convolutional neural network, Image classification, Residues, SWIR, VNIR, WorldView-3}, pages = {756--772}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\XPACGD69\\Sidike et al. - 2019 - dPEN deep Progressively Expanded Network for mapp.pdf:application/pdf}, } @article{houborg_high-resolution_2016, title = {High-{Resolution} {NDVI} from {Planet}’s {Constellation} of {Earth} {Observing} {Nano}-{Satellites}: {A} {New} {Data} {Source} for {Precision} {Agriculture}}, volume = {8}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {High-{Resolution} {NDVI} from {Planet}’s {Constellation} of {Earth} {Observing} {Nano}-{Satellites}}, url = {https://www.mdpi.com/2072-4292/8/9/768}, doi = {10.3390/rs8090768}, abstract = {Planet Labs (“Planet”) operate the largest fleet of active nano-satellites in orbit, offering an unprecedented monitoring capacity of daily and global RGB image capture at 3–5 m resolution. However, limitations in spectral resolution and lack of accurate radiometric sensor calibration impact the utility of this rich information source. In this study, Planet’s RGB imagery was translated into a Normalized Difference Vegetation Index (NDVI): a common metric for vegetation growth and condition. Our framework employs a data mining approach to build a set of rule-based regression models that relate RGB data to atmospherically corrected Landsat-8 NDVI. The approach was evaluated over a desert agricultural landscape in Saudi Arabia where the use of near-coincident (within five days) Planet and Landsat-8 acquisitions in the training of the regression models resulted in NDVI predictabilities with an r2 of approximately 0.97 and a Mean Absolute Deviation (MAD) on the order of 0.014 ({\textasciitilde}9\%). The MAD increased to 0.021 ({\textasciitilde}14\%) when the Landsat NDVI training image was further away (i.e., 11–16 days) from the corrected Planet image. In these cases, the use of MODIS observations to inform on the change in NDVI occurring between overpasses was shown to significantly improve prediction accuracies. MAD levels ranged from 0.002 to 0.011 (3.9\% to 9.1\%) for the best performing 80\% of the data. The technique is generic and extendable to any region of interest, increasing the utility of Planet’s dense time-series of RGB imagery.}, language = {en}, number = {9}, urldate = {2021-08-17}, journal = {Remote Sensing}, author = {Houborg, Rasmus and McCabe, Matthew F.}, month = sep, year = {2016}, note = {Number: 9 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {Landsat, data mining, precision agriculture, NDVI, nano-satellites, planet labs, RGB}, pages = {768}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\LI9ZAK28\\Houborg and McCabe - 2016 - High-Resolution NDVI from Planet’s Constellation o.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\D7N22NRD\\768.html:text/html}, } @article{lefsky_lidar_2002, title = {Lidar remote sensing of above-ground biomass in three biomes}, volume = {11}, issn = {1466-8238}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1046/j.1466-822x.2002.00303.x}, doi = {10.1046/j.1466-822x.2002.00303.x}, abstract = {Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical structure of forests and thus hold great promise for remotely sensing the quantity and spatial organization of forest biomass. In this study, we compare the relationships between lidar-measured canopy structure and coincident field measurements of above-ground biomass at sites in the temperate deciduous, temperate coniferous, and boreal coniferous biomes. A single regression for all three sites is compared with equations derived for each site individually. The single equation explains 84\% of variance in above-ground biomass (P {\textless} 0.0001) and shows no statistically significant bias in its predictions for any individual site.}, language = {en}, number = {5}, urldate = {2021-08-19}, journal = {Global Ecology and Biogeography}, author = {Lefsky, Michael A. and Cohen, Warren B. and Harding, David J. and Parker, Geoffrey G. and Acker, Steven A. and Gower, S. Thomas}, year = {2002}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1046/j.1466-822x.2002.00303.x}, keywords = {above-ground biomass, biomass measurement, carbon storage, forest biomass, global carbon cycle, interbiome comparison, lidar remote sensing, SLICER sensor}, pages = {393--399}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\S8DLFU7T\\j.1466-822x.2002.00303.html:text/html}, } @incollection{chase_lidar_2017, address = {Cham}, series = {Geotechnologies and the {Environment}}, title = {{LiDAR} for {Archaeological} {Research} and the {Study} of {Historical} {Landscapes}}, isbn = {978-3-319-50518-3}, url = {https://doi.org/10.1007/978-3-319-50518-3_4}, abstract = {Remote sensing technologies have helped to revolutionize archaeology. LiDAR (light detection and ranging), a remote sensing technology in which lasers are used as topographic scanners that can penetrate foliage, has particularly influenced researchers in the field of settlement or landscape archaeology. LiDAR provides detailed landscape data for broad spatial areas and permits visualization of these landscapes in ways that were never before possible. These data and visualizations have been widely utilized to gain a better understanding of historical landscapes and their past uses by ancient peoples.}, language = {en}, urldate = {2021-08-30}, booktitle = {Sensing the {Past}: {From} artifact to historical site}, publisher = {Springer International Publishing}, author = {Chase, Adrian S. Z. and Chase, Diane Z. and Chase, Arlen F.}, editor = {Masini, Nicola and Soldovieri, Francesco}, year = {2017}, doi = {10.1007/978-3-319-50518-3_4}, keywords = {Archaeology, LiDAR, Landscapes, Visualization techniques}, pages = {89--100}, file = {Springer Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HV5WHTM8\\Chase et al. - 2017 - LiDAR for Archaeological Research and the Study of.pdf:application/pdf}, } @article{boursianis_internet_2020, title = {Internet of {Things} ({IoT}) and {Agricultural} {Unmanned} {Aerial} {Vehicles} ({UAVs}) in smart farming: {A} comprehensive review}, issn = {2542-6605}, shorttitle = {Internet of {Things} ({IoT}) and {Agricultural} {Unmanned} {Aerial} {Vehicles} ({UAVs}) in smart farming}, url = {https://www.sciencedirect.com/science/article/pii/S2542660520300238}, doi = {10.1016/j.iot.2020.100187}, abstract = {Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot technologies utilized in cultivation fields, which transform traditional farming practices into a new era of precision agriculture. In this paper, we perform a survey of the last research on IoT and UAV technology applied in agriculture. We describe the main principles of IoT technology, including intelligent sensors, IoT sensor types, networks and protocols used in agriculture, as well as IoT applications and solutions in smart farming. Moreover, we present the role of UAV technology in smart agriculture, by analyzing the applications of UAVs in various scenarios, including irrigation, fertilization, use of pesticides, weed management, plant growth monitoring, crop disease management, and field-level phenotyping. Furthermore, the utilization of UAV systems in complex agricultural environments is also analyzed. Our conclusion is that IoT and UAV are two of the most important technologies that transform traditional cultivation practices into a new perspective of intelligence in precision agriculture.}, language = {en}, urldate = {2021-08-12}, journal = {Internet of Things}, author = {Boursianis, Achilles D. and Papadopoulou, Maria S. and Diamantoulakis, Panagiotis and Liopa-Tsakalidi, Aglaia and Barouchas, Pantelis and Salahas, George and Karagiannidis, George and Wan, Shaohua and Goudos, Sotirios K.}, month = mar, year = {2020}, keywords = {Europe, Agriculture, Unmanned Aerial Vehicles, wireless sensor networks, Greece, Internet of Things, Smart Farming, Survey}, pages = {100187}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\2MIYI6VE\\S2542660520300238.html:text/html}, } @article{elijah_overview_2018, title = {An {Overview} of {Internet} of {Things} ({IoT}) and {Data} {Analytics} in {Agriculture}: {Benefits} and {Challenges}}, volume = {5}, issn = {2327-4662}, shorttitle = {An {Overview} of {Internet} of {Things} ({IoT}) and {Data} {Analytics} in {Agriculture}}, doi = {10.1109/JIOT.2018.2844296}, abstract = {The surge in global population is compelling a shift toward smart agriculture practices. This coupled with the diminishing natural resources, limited availability of arable land, increase in unpredictable weather conditions makes food security a major concern for most countries. As a result, the use of Internet of Things (IoT) and data analytics (DA) are employed to enhance the operational efficiency and productivity in the agriculture sector. There is a paradigm shift from use of wireless sensor network (WSN) as a major driver of smart agriculture to the use of IoT and DA. The IoT integrates several existing technologies, such as WSN, radio frequency identification, cloud computing, middleware systems, and end-user applications. In this paper, several benefits and challenges of IoT have been identified. We present the IoT ecosystem and how the combination of IoT and DA is enabling smart agriculture. Furthermore, we provide future trends and opportunities which are categorized into technological innovations, application scenarios, business, and marketability.}, number = {5}, journal = {IEEE Internet of Things Journal}, author = {Elijah, Olakunle and Rahman, Tharek Abdul and Orikumhi, Igbafe and Leow, Chee Yen and Hindia, MHD Nour}, month = oct, year = {2018}, note = {Conference Name: IEEE Internet of Things Journal}, keywords = {Soil, Agriculture, wireless sensor networks, Internet of Things, data analytics (DA), Internet of Things (IoT), IoT ecosystems, IoT in agriculture, IoT sensors, Malaysia, Optical sensors, smart agriculture, South East Asia}, pages = {3758--3773}, file = {IEEE Xplore Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\94ED333A\\Elijah et al. - 2018 - An Overview of Internet of Things (IoT) and Data A.pdf:application/pdf}, } @incollection{castrignano_author_2020, title = {Author {Index}}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731200024}, language = {en}, urldate = {2021-08-20}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.20002-4}, pages = {435--459}, } @incollection{castrignano_subject_2020, title = {Subject {Index}}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731200012}, language = {en}, urldate = {2021-08-20}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.20001-2}, pages = {417--434}, } @incollection{castrignano_preface_2020, title = {Preface}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731050010}, language = {en}, urldate = {2021-08-20}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.05001-0}, pages = {ix}, } @incollection{castrignano_front_2020, title = {Front {Matter}}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731010015}, language = {en}, urldate = {2021-08-20}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.01001-5}, pages = {iii}, } @article{zhang_integrated_2019, title = {Integrated {Satellite}, {Unmanned} {Aerial} {Vehicle} ({UAV}) and {Ground} {Inversion} of the {SPAD} of {Winter} {Wheat} in the {Reviving} {Stage}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/7/1485}, doi = {10.3390/s19071485}, abstract = {Chlorophyll is the most important component of crop photosynthesis, and the reviving stage is an important period during the rapid growth of winter wheat. Therefore, rapid and precise monitoring of chlorophyll content in winter wheat during the reviving stage is of great significance. The satellite-UAV-ground integrated inversion method is an innovative solution. In this study, the core region of the Yellow River Delta (YRD) is used as a study area. Ground measurements data, UAV multispectral and Sentinel-2A multispectral imagery are used as data sources. First, representative plots in the Hekou District were selected as the core test area, and 140 ground sampling points were selected. Based on the measured SPAD values and UAV multispectral images, UAV-based SPAD inversion models were constructed, and the most accurate model was selected. Second, by comparing satellite and UAV imagery, a reflectance correction for satellite imagery was performed. Finally, based on the UAV-based inversion model and satellite imagery after reflectance correction, the inversion results for SPAD values in multi-scale were obtained. The results showed that green, red, red-edge and near-infrared bands were significantly correlated with SPAD values. The modeling precisions of the best inversion model are R2 = 0.926, Root Mean Squared Error (RMSE) = 0.63 and Mean Absolute Error (MAE) = 0.92, and the verification precisions are R2 = 0.934, RMSE = 0.78 and MAE = 0.87. The Sentinel-2A imagery after the reflectance correction has a pronounced inversion effect; the SPAD values in the study area were concentrated between 40 and 60, showing an increasing trend from the eastern coast to the southwest and west, with obvious spatial differences. This study synthesizes the advantages of satellite, UAV and ground methods, and the proposed satellite-UAV-ground integrated inversion method has important implications for real-time, rapid and precision SPAD values collected on multiple scales.}, language = {en}, number = {7}, urldate = {2021-08-17}, journal = {Sensors}, author = {Zhang, Suming and Zhao, Gengxing and Lang, Kun and Su, Baowei and Chen, Xiaona and Xi, Xue and Zhang, Huabin}, month = jan, year = {2019}, note = {Number: 7 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {remote sensing, UAV, chlorophyll, fusion, Sentinel-2A satellite, SPAD}, pages = {1485}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\D4F4A286\\Zhang et al. - 2019 - Integrated Satellite, Unmanned Aerial Vehicle (UAV.pdf:application/pdf}, } @inproceedings{katsigiannis_fusion_2016, title = {Fusion of spatio-temporal {UAV} and proximal sensing data for an agricultural decision support system}, volume = {9688}, url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9688/96881R/Fusion-of-spatio-temporal-UAV-and-proximal-sensing-data-for/10.1117/12.2244856.short}, doi = {10.1117/12.2244856}, abstract = {Over the last few years, multispectral and thermal remote sensing imagery from unmanned aerial vehicles (UAVs) has found application in agriculture and has been regarded as a means of field data collection and crop condition monitoring source. The integration of information derived from the analysis of these remotely sensed data into agricultural management applications facilitates and aids the stakeholder’s decision making. Whereas agricultural decision support systems (DSS) have long been utilised in farming applications, there are still critical gaps to be addressed; as the current approach often neglects the plant’s level information and lacks the robustness to account for the spatial and temporal variability of environmental parameters within agricultural systems. In this paper, we demonstrate the use of a custom built autonomous UAV platform in providing critical information for an agricultural DSS. This hexacopter UAV bears two cameras which can be triggered simultaneously and can capture both the visible, near-infrared (VNIR) and the thermal infrared (TIR) wavelengths. The platform was employed for the rapid extraction of the normalized difference vegetation index (NDVI) and the crop water stress index (CWSI) of three different plantations, namely a kiwi, a pomegranate, and a vine field. The simultaneous recording of these two complementary indices and the creation of maps was advantageous for the accurate assessment of the plantation's status. Fusion of UAV and soil scanner system products pinpointed the necessity for adjustment of the irrigation management applied. It is concluded that timely CWSI and NDVI measures retrieved for different crop growing stages can provide additional information and can serve as a tool to support the existing irrigation DSS that had so far been exclusively based on telemetry data from soil and agrometeorological sensors. Additionally, the use of the multi-sensor UAV was found to be beneficial in collecting timely, spatio-temporal information for the fusion with ground-based proximal sensing data. This research work was designed and deployed in the frame of the project "AGRO\_LESS: Joint reference strategies for rural activities of reduced inputs".}, urldate = {2021-08-17}, booktitle = {Fourth {International} {Conference} on {Remote} {Sensing} and {Geoinformation} of the {Environment} ({RSCy2016})}, publisher = {International Society for Optics and Photonics}, author = {Katsigiannis, P. and Galanis, G. and Dimitrakos, A. and Tsakiridis, N. and Kalopesas, C. and Alexandridis, T. and Chouzouri, A. and Patakas, A. and Zalidis, G.}, month = aug, year = {2016}, keywords = {UAV, DSS, fusion, proximal}, pages = {96881R}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\32ZJMULK\\12.2244856.html:text/html}, } @article{zhai_decision_2020, title = {Decision support systems for agriculture 4.0: {Survey} and challenges}, volume = {170}, issn = {0168-1699}, shorttitle = {Decision support systems for agriculture 4.0}, url = {https://www.sciencedirect.com/science/article/pii/S0168169919316497}, doi = {10.1016/j.compag.2020.105256}, abstract = {Undoubtedly, high demands for food from the world-wide growing population are impacting the environment and putting many pressures on agricultural productivity. Agriculture 4.0, as the fourth evolution in the farming technology, puts forward four essential requirements: increasing productivity, allocating resources reasonably, adapting to climate change, and avoiding food waste. As advanced information systems and Internet technologies are adopted in Agriculture 4.0, enormous farming data, such as meteorological information, soil conditions, marketing demands, and land uses, can be collected, analyzed, and processed for assisting farmers in making appropriate decisions and obtaining higher profits. Therefore, agricultural decision support systems for Agriculture 4.0 has become a very attractive topic for the research community. The objective of this paper aims at exploring the upcoming challenges of employing agricultural decision support systems in Agriculture 4.0. Future researchers may improve the decision support systems by overcoming these detected challenges. In this paper, the systematic literature review technique is used to survey thirteen representative decision support systems, including their applications for agricultural mission planning, water resources management, climate change adaptation, and food waste control. Each decision support system is analyzed under a systematic manner. A comprehensive evaluation is conducted from the aspects of interoperability, scalability, accessibility, usability, etc. Based on the evaluation result, upcoming challenges are detected and summarized, suggesting the development trends and demonstrating potential improvements for future research.}, language = {en}, urldate = {2021-08-17}, journal = {Computers and Electronics in Agriculture}, author = {Zhai, Zhaoyu and Martínez, José Fernán and Beltran, Victoria and Martínez, Néstor Lucas}, month = mar, year = {2020}, keywords = {Agriculture, Smart farming, Decision support systems, Decision-making}, pages = {105256}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\RE7LD8TA\\Zhai et al. - 2020 - Decision support systems for agriculture 4.0 Surv.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\MDHELKKH\\S0168169919316497.html:text/html}, } @article{zhou_roscc_2016, title = {{ROSCC}: {An} {Efficient} {Remote} {Sensing} {Observation}-{Sharing} {Method} {Based} on {Cloud} {Computing} for {Soil} {Moisture} {Mapping} in {Precision} {Agriculture}}, volume = {9}, issn = {2151-1535}, shorttitle = {{ROSCC}}, doi = {10.1109/JSTARS.2016.2574810}, abstract = {The inversion of remote sensing images is crucial for soil moisture mapping in precision agriculture. However, the large size of remote sensing images complicates their management. Therefore, this study proposes a remote sensing observation sharing method based on cloud computing (ROSCC) to enhance remote sensing observation storage, processing, and service capability. The ROSCC framework consists of a cloud computing-enabled sensor observation service, web processing service tier, and a distributed database tier. Using MongoDB as the distributed database and Apache Hadoop as the cloud computing service, this study achieves a high-throughput method for remote sensing observation storage and distribution. The map, reduced algorithms and the table structure design in distributed databases are then explained. Along the Yangtze River, the longest river in China, Hubei Province was selected as the study area to test the proposed framework. Using GF-1 as a data source, an experiment was performed to enhance earth observation data (EOD) storage and achieve large-scale soil moisture mapping. The proposed ROSCC can be applied to enhance EOD sharing in cloud computing context, so as to achieve soil moisture mapping via the modified perpendicular drought index in an efficient way to better serve precision agriculture.}, number = {12}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, author = {Zhou, Lianjie and Chen, Nengcheng and Chen, Zeqiang and Xing, Chenjie}, month = dec, year = {2016}, note = {Conference Name: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, keywords = {Remote sensing, Agriculture, Cloud computing, Distributed databases, Earth, earth observation data (EOD) sharing enhancement, precision agriculture (PA), sensor observation service (SOS), Servers, Soil moisture}, pages = {5588--5598}, file = {IEEE Xplore Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\DWXRV4Q3\\Zhou et al. - 2016 - ROSCC An Efficient Remote Sensing Observation-Sha.pdf:application/pdf;IEEE Xplore Abstract Record:C\:\\Users\\Edify 01\\Zotero\\storage\\9MYMN93Z\\7500091.html:text/html}, } @article{khanal_overview_2017, title = {An overview of current and potential applications of thermal remote sensing in precision agriculture}, volume = {139}, issn = {0168-1699}, url = {https://www.sciencedirect.com/science/article/pii/S0168169916310225}, doi = {10.1016/j.compag.2017.05.001}, abstract = {Precision agriculture (PA) utilizes tools and technologies to identify in-field soil and crop variability for improving farming practices and optimizing agronomic inputs. Traditionally, optical remote sensing (RS) that utilizes visible light and infrared regions of the electromagnetic spectrum has been used as an integral part of PA for crop and soil monitoring. Optical RS, however, is slow in differentiating stress levels in crops until visual symptoms become noticeable. Surface temperature is considered to be a rapid response variable that can indicate crop stresses prior to their visual symptoms. By measuring estimates of surface temperature, thermal RS has been found to be a promising tool for PA. Compared to optical RS, applications of thermal RS for PA have been limited. Until recently (i.e., before the advancement of low cost RS platforms such as unmanned aerial systems (UAVs)), the availability of high resolution thermal images was limited due to high acquisition costs. Given recent developments in UAVs, thermal images with high spatial and temporal resolutions have become available at a low cost, which has increased opportunities to understand in-field variability of crop and soil conditions useful for various agronomic decision-making. Before thermal RS is adopted as a routine tool for crop and environmental monitoring, there is a need to understand its current and potential applications as well as issues and concerns. This review focuses on current and potential applications of thermal RS in PA as well as some concerns relating to its application. The application areas of thermal RS in agriculture discussed here include irrigation scheduling, drought monitoring, crop disease detection, and mapping of soil properties, residues and tillage, field tiles, and crop maturity and yield. Some of the issues related to its application include spatial and temporal resolution, atmospheric conditions, and crop growth stages.}, language = {en}, urldate = {2021-08-21}, journal = {Computers and Electronics in Agriculture}, author = {Khanal, Sami and Fulton, John and Shearer, Scott}, month = jun, year = {2017}, keywords = {Precision agriculture, Monitoring, Remote sensing, Americas, US, Thermal sensing}, pages = {22--32}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\N5P3K6FQ\\Khanal et al. - 2017 - An overview of current and potential applications .pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JNACNAWB\\S0168169916310225.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\GGDAFC5U\\Khanal et al. - 2017 - An overview of current and potential applications .pdf:application/pdf}, } @incollection{acutis_contributors_2020, title = {Contributors}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731010027}, language = {en}, urldate = {2021-08-20}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, author = {Acutis, Marco and Alexandridis, Thomas and Anastasiou, Evangelos and Ardito, Carmelo and Balafoutis, A. T. and Bechar, Avital and Bourreau, Eric and Buddenbaum, Henning and Buttafuoco, Gabriele and Caivano, Danilo and Castrignanò, Annamaria and Chanet, Jean-Pierre and Cohen, Yafit and Colizzi, Lucio and Crestey, Thomas and Desolda, Giuseppe and Dusadeerungsikul, Puwadol Oak and Fastellini, Guido and Fountas, S. and Fue, Kadeghe G. and Giroudeau, Rodolphe and Guillaume, Serge and Hou, Kun-Mean and Hui, Gao and Kayad, Ahmed and Kernecker, M. and Khosla, Raj and Knierim, A. and Liakos, Vasileios and Marinello, Francesco and Matera, Maristella and Méndez, Andrés and Morari, Francesco and Morimoto, Eiji and Moshou, Dimitrios and Mouazen, A. M. and Mulla, David and Naud, Olivier and Nawar, Said and Nof, Shimon Y. and Ørum, J. E. and Pedersen, S. M. and Pedersen, M. F. and Pinet, François and Sanga, Camilius A. and Sartori, Luigi and Schillaci, Calogero and Shi, Hongling and Sudduth, Kenneth A. and Taylor, James and Tisseyre, Bruno and Tumbo, Siza D. and van Egmond, F. and van Evert, F. K. and Vélez, Juan Pablo and Vellidis, George}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.01002-7}, pages = {vii--viii}, } @incollection{castrignano_copyright_2020, title = {Copyright}, isbn = {978-0-12-818373-1}, url = {https://www.sciencedirect.com/science/article/pii/B9780128183731120013}, language = {en}, urldate = {2021-08-20}, booktitle = {Agricultural {Internet} of {Things} and {Decision} {Support} for {Precision} {Smart} {Farming}}, publisher = {Academic Press}, editor = {Castrignanò, Annamaria and Buttafuoco, Gabriele and Khosla, Raj and Mouazen, Abdul M. and Moshou, Dimitrios and Naud, Olivier}, month = jan, year = {2020}, doi = {10.1016/B978-0-12-818373-1.12001-3}, pages = {iv}, } @misc{noauthor_pasturebase_nodate, title = {{PastureBase} {Ireland} - {Teagasc}}, url = {https://pasturebase.teagasc.ie/V2/login.aspx}, urldate = {2021-08-19}, file = {PastureBase Ireland - Teagasc:C\:\\Users\\Edify 01\\Zotero\\storage\\S6RLIYLE\\login.html:text/html}, } @article{hanrahan_pasturebase_2017, title = {{PastureBase} {Ireland}: {A} grassland decision support system and national database}, volume = {136}, issn = {0168-1699}, shorttitle = {{PastureBase} {Ireland}}, url = {https://www.sciencedirect.com/science/article/pii/S0168169916304781}, doi = {10.1016/j.compag.2017.01.029}, abstract = {PastureBase Ireland (PBI) is a web-based grassland management application incorporating a dual function of grassland decision support and a centralized national database to collate commercial farm grassland data. This database facilitates the collection and storage of vast quantities of grassland data from grassland farmers. The database spans across ruminant grassland enterprises – dairy, beef and sheep. To help farmers determine appropriate actions around grassland management, we have developed this data informed decision support tool to function at the paddock level. Individual farmers enter data through the completion of regular pasture cover estimations across the farm, allowing the performance of individual paddocks to be evaluated within and across years. To evaluate the PBI system, we compared actual pasture cut experimental data (Etesia cuts) to PBI calculated outputs. We examined three comparisons, comparing PBI outputs to actual pasture cut data, for individual DM yields at defoliation (Comparison 1), for cumulative annual DM yields including silage data (Comparison 2) and, for cumulative annual DM yields excluding silage data (Comparison 3). We found an acceptable accuracy between PBI outputs and pasture cut data when statistically analyzed using relative prediction error and concordance correlation coefficients for the measurement of total annual DM yield (Comparison 2), with a relative prediction error of 15.4\% and a concordance correlation coefficient of 0.85. We demonstrated an application of the PBI system through analysis of commercial farm data across two years (2014–2015) for 75 commercial farms who actively use the system. The analysis showed there was a significant increase in DM yield from 2014 to 2015. The results indicated a greater variation in pasture growth across paddocks within farms than across farms.}, language = {en}, urldate = {2021-08-19}, journal = {Computers and Electronics in Agriculture}, author = {Hanrahan, Liam and Geoghegan, Anne and O'Donovan, Michael and Griffith, Vincent and Ruelle, Elodie and Wallace, Michael and Shalloo, Laurence}, month = apr, year = {2017}, keywords = {Centralized database, Decision support, Dry matter production, Grassland farming, PastureBase Ireland}, pages = {193--201}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\LW97437T\\S0168169916304781.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\6FNBCXBW\\Hanrahan et al. - 2017 - PastureBase Ireland A grassland decision support .pdf:application/pdf}, } @article{higgins_improving_2019, title = {Improving productivity and increasing the efficiency of soil nutrient management on grassland farms in the {UK} and {Ireland} using precision agriculture technology}, volume = {106}, issn = {1161-0301}, url = {https://www.sciencedirect.com/science/article/pii/S1161030119300371}, doi = {10.1016/j.eja.2019.04.001}, abstract = {Grass growth and utilisation on grassland farms across the UK and Ireland are below their potential, and nutrient management is sub-optimal. Excessive soil phosphorus concentrations are an issue, contributing to eutrophication of waterways, while sub-optimal soil pH due to a reduction in lime use is seen in many areas. This paper discusses the potential for introducing technology onto grassland farms, and implementing sensible farm-specific management decisions as a means of enhancing productivity and minimising the environmental impact of livestock farming. The adoption rate of Precision Agriculture (PA) technology by grassland farmers in the UK and Ireland is still relatively low, and significantly lagging behind the advances that have taken place within the arable farming community. With rapidly advancing technology and investment in research, there are now a range of soil sensors available along with technology for grass growth monitoring, yield mapping, remote sensing, satellite imagery, and devices for tracking animal movement, behaviour and feed intake. In this review paper we examine the latest technology developments specific to grassland farming and we question their suitability and ‘readiness’ for adoption by farmers. The review identifies the challenges that are specific to grassland such as complex soil, vegetation and climatic variables along with economic barriers that may be preventing change within the farming community in these areas.}, language = {en}, urldate = {2021-08-17}, journal = {European Journal of Agronomy}, author = {Higgins, S. and Schellberg, J. and Bailey, J. S.}, month = may, year = {2019}, keywords = {Precision agriculture, Europe, Adoption, UK, Éire, Grasslands, Nutrient management, Soil fertility}, pages = {67--74}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JNAMQBG2\\S1161030119300371.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\9TMVPAJ2\\Higgins et al. - 2019 - Improving productivity and increasing the efficien.pdf:application/pdf}, } @misc{noauthor_cropsyst_nodate, title = {{CropSyst} {\textbar} {Land} \& {Water} {\textbar} {Food} and {Agriculture} {Organization} of the {United} {Nations} {\textbar} {Land} \& {Water} {\textbar} {Food} and {Agriculture} {Organization} of the {United} {Nations}}, url = {http://www.fao.org/land-water/land/land-governance/land-resources-planning-toolbox/category/details/en/c/1236450/}, urldate = {2021-08-20}, } @article{nadimi_recent_2021, title = {Recent applications of novel laser techniques for enhancing agricultural production}, volume = {31}, issn = {1555-6611}, url = {https://doi.org/10.1088/1555-6611/abebda}, doi = {10.1088/1555-6611/abebda}, abstract = {With ever increasing world population, the demands on food safety and security are also expected to substantially increase over the next few decades. As agronomic practices, agricultural mechanization and plant breeding technologies have already been extensively exploited, novel techniques need to be explored and implemented to enhance crop production. To this end, the emerging area of laser-based technologies has shown potential to bring about another revolution in enhancing quantity, quality, and safety of foods. This paper presents an exhaustive review of the use of five non-invasive non-destructive laser-based techniques in agriculture, namely laser biostimulation, light detection and ranging, laser land levelling, laser-induced fluorescence spectroscopy, and Raman spectroscopy. Herein we provide the advantages, status quo and challenges of each of these techniques and conclude with recommendations for future work. A comprehensive review of literature reveals the untapped potential of laser applications in agriculture that has the potential to unleash the next agricultural revolution.}, language = {en}, number = {5}, urldate = {2021-08-20}, journal = {Laser Physics}, author = {Nadimi, Mohammad and Sun, Da-Wen and Paliwal, Jitendra}, month = mar, year = {2021}, note = {Publisher: IOP Publishing}, pages = {053001}, file = {IOP Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\8UG5BP5W\\Nadimi et al. - 2021 - Recent applications of novel laser techniques for .pdf:application/pdf}, } @article{li_airborne_2015, title = {Airborne {LiDAR} technique for estimating biomass components of maize: {A} case study in {Zhangye} {City}, {Northwest} {China}}, volume = {57}, issn = {1470-160X}, shorttitle = {Airborne {LiDAR} technique for estimating biomass components of maize}, url = {https://www.sciencedirect.com/science/article/pii/S1470160X15001946}, doi = {10.1016/j.ecolind.2015.04.016}, abstract = {Crop biomass is an important ecological indicator of growth, light use efficiency, and carbon stocks in agro-ecosystems. Light detection and ranging (LiDAR) or laser scanning has been widely used to estimate forest structural parameters and biomass. However, LiDAR is rarely used to estimate crop parameters because the short, dense canopies of crops limit the accuracy of the results. The objective of this study is to explore the potential of airborne LiDAR data in estimating biomass components of maize, namely aboveground biomass (AGB) and belowground biomass (BGB). Five biomass-related factors were measured during the entire growing season of maize. The field-measured canopy height and leaf area index (LAI) were identified as the factors that most directly affect biomass components through Pearson's correlation analysis and structural equation modeling (SEM). Field-based estimation models were proposed to estimate maize biomass components during the tasseling stage. Subsequently, the maize height and LAI over the entire study area were derived from LiDAR data and were used as input for the estimation models to map the spatial pattern of the biomass components. The results showed that the LiDAR-estimated biomass was comparable to the field-measured biomass, with root mean squared errors (RMSE) of 288.51g/m2 (AGB), and 75.81g/m2 (BGB). In conclusion, airborne LiDAR has great potential for estimating canopy height, LAI, and biomass components of maize during the peak growing season.}, language = {en}, urldate = {2021-08-20}, journal = {Ecological Indicators}, author = {Li, Wang and Niu, Zheng and Huang, Ni and Wang, Cheng and Gao, Shuai and Wu, Chaoyang}, month = oct, year = {2015}, keywords = {Airborne LiDAR, Canopy height, Leaf area index, Maize biomass}, pages = {486--496}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JZDA44B4\\S1470160X15001946.html:text/html;ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\JWTCI6QU\\Li et al. - 2015 - Airborne LiDAR technique for estimating biomass co.pdf:application/pdf}, } @article{bregaglio_new_2015, title = {New multi-model approach gives good estimations of wheat yield under semi-arid climate in {Morocco}}, volume = {35}, issn = {1774-0746, 1773-0155}, url = {http://link.springer.com/10.1007/s13593-014-0225-6}, doi = {10.1007/s13593-014-0225-6}, abstract = {Wheat production in Morocco is crucial for economy and food security. However, wheat production is difficult because the semi-arid climate causes very variable wheat yields. To solve this issue, we need better prediction of the impact of drought on wheat yields to adapt cropping management to the semi-arid climate. Here, we adapted the models WOFOST and CropSyst to agro-climatic conditions in Morocco. Six soft and durum wheat varieties were grown during the 2011–2012 and 2012–2013 growing seasons in the experimental sites of Sidi El Aydi, Khemis Zemamra and Marchouch. Drip irrigation and rainfed treatments were arranged in a randomised-block design with three replicates. We determined the phenological stages of emergence, tillering, stem elongation, flowering and maturity. We measured aboveground biomass six times along the season. These data were used to adapt WOFOST and CropSyst to local conditions. Our results show that both models achieved good estimations, with R2 always higher than 0.91, and positive values for Nash and Sutcliffe modelling efficiencies. Results of spatially distributed simulations were then analysed for the whole country in terms of different response to drought.}, language = {en}, number = {1}, urldate = {2021-08-20}, journal = {Agronomy for Sustainable Development}, author = {Bregaglio, Simone and Frasso, Nicolò and Pagani, Valentina and Stella, Tommaso and Francone, Caterina and Cappelli, Giovanni and Acutis, Marco and Balaghi, Riad and Ouabbou, Hassan and Paleari, Livia and Confalonieri, Roberto}, month = jan, year = {2015}, pages = {157--167}, file = {Bregaglio et al. - 2015 - New multi-model approach gives good estimations of.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\C23FCR5A\\Bregaglio et al. - 2015 - New multi-model approach gives good estimations of.pdf:application/pdf}, } @article{stockle_cropsyst_2003, series = {Modelling {Cropping} {Systems}: {Science}, {Software} and {Applications}}, title = {{CropSyst}, a cropping systems simulation model}, volume = {18}, issn = {1161-0301}, url = {https://www.sciencedirect.com/science/article/pii/S1161030102001090}, doi = {10.1016/S1161-0301(02)00109-0}, abstract = {CropSyst is a multi-year, multi-crop, daily time step cropping systems simulation model developed to serve as an analytical tool to study the effect of climate, soils, and management on cropping systems productivity and the environment. CropSyst simulates the soil water and nitrogen budgets, crop growth and development, crop yield, residue production and decomposition, soil erosion by water, and salinity. The development of CropSyst started in the early 1990s, evolving to a suite of programs including a cropping systems simulator (CropSyst), a weather generator (ClimGen), GIS-CropSyst cooperator program (ArcCS), a watershed model (CropSyst Watershed), and several miscellaneous utility programs. CropSyst and associated programs can be downloaded free of charge over the Internet. One key feature of CropSyst is the implementation of a generic crop simulator that enables the simulation of both yearly and multi-year crops and crop rotations via a single set of parameters. Simulations can last a fraction of a year to hundreds of years. The model has been evaluated in many world locations by comparing model estimates to data collected in field experiments. CropSyst has been applied to perform risk and economic analyses of scenarios involving different cropping systems, management options, and soil and climatic conditions. An extensive list of references related to model development, evaluation, and application is provided.}, language = {en}, number = {3}, urldate = {2021-08-20}, journal = {European Journal of Agronomy}, author = {Stöckle, Claudio O. and Donatelli, Marcello and Nelson, Roger}, month = jan, year = {2003}, keywords = {Farming systems, Agricultural modeling, ClimGen, Cropping systems, CropSyst, Simulation models, Watershed simulation}, pages = {289--307}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\UP2IXWTG\\Stöckle et al. - 2003 - CropSyst, a cropping systems simulation model.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\MWVDZC7N\\S1161030102001090.html:text/html}, } @misc{form_wofost_2019, title = {{WOFOST} - {WOrld} {FOod} {STudies}}, url = {https://www.wur.nl/en/Research-Results/Research-Institutes/Environmental-Research/Facilities-Tools/Software-models-and-databases/WOFOST.htm}, abstract = {WOFOST (WOrld FOod STudies) is a simulation model for the quantitative analysis of the growth and production of annual field crops.}, language = {en-us}, urldate = {2021-08-20}, journal = {WUR}, author = {form, Contact dr AJWde Wit Contact}, month = aug, year = {2019}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\K3GBFFFI\\WOFOST.html:text/html}, } @inproceedings{anthony_crop_2014, address = {Chicago, IL, USA}, title = {On crop height estimation with {UAVs}}, isbn = {978-1-4799-6934-0 978-1-4799-6931-9}, url = {http://ieeexplore.ieee.org/document/6943245/}, doi = {10.1109/IROS.2014.6943245}, abstract = {Remote sensing by Unmanned Aerial Vehicles (UAVs) is changing the way agriculture operates by increasing the spatial-temporal resolution of data collection. Micro-UAVs have the potential to further improve and enrich the data collected by operating close to the crops, enabling the collection of higher spatio-temporal resolution data. In this paper, we present a UAV-mounted measurement system that utilizes a laser scanner to compute crop heights, a critical indicator of crop health. The system filters, transforms, and analyzes the cluttered range data in real-time to determine the distance to the ground and to the top of the crops. We assess the system in an indoor testbed and in a corn field. Our findings indicate that despite the dense canopy and highly variable sensor readings, we can precisely fly over crops and measure its height to within 5cm of measurements gathered using current measurement technology.}, language = {en}, urldate = {2021-08-20}, booktitle = {2014 {IEEE}/{RSJ} {International} {Conference} on {Intelligent} {Robots} and {Systems}}, publisher = {IEEE}, author = {Anthony, David and Elbaum, Sebastian and Lorenz, Aaron and Detweiler, Carrick}, month = sep, year = {2014}, pages = {4805--4812}, file = {Anthony et al. - 2014 - On crop height estimation with UAVs.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\NV689F9X\\Anthony et al. - 2014 - On crop height estimation with UAVs.pdf:application/pdf}, } @article{peprah_spatio-temporal_2021, title = {Spatio-{Temporal} {Estimation} of {Biomass} {Growth} in {Rice} {Using} {Canopy} {Surface} {Model} from {Unmanned} {Aerial} {Vehicle} {Images}}, volume = {13}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/13/12/2388}, doi = {10.3390/rs13122388}, abstract = {The awareness of spatial and temporal variations in site-specific crop parameters, such as aboveground biomass (total dry weight: (TDW), plant length (PL) and leaf area index (LAI), help in formulating appropriate management decisions. However, conventional monitoring methods rely on time-consuming manual field operations. In this study, the feasibility of using an unmanned aerial vehicle (UAV)-based remote sensing approach for monitoring growth in rice was evaluated using a digital surface model (DSM). Approximately 160 images of paddy fields were captured during each UAV survey campaign over two vegetation seasons. The canopy surface model (CSM) was developed based on the differences observed between each DSM and the first DSM after transplanting. Mean canopy height (CH) was used as a variable for the estimation models of LAI and TDW. The mean CSM of the mesh covering several hills was sufficient to explain the PL (R2 = 0.947). TDW and LAI prediction accuracy of the model were high (relative RMSE of 20.8\% and 28.7\%, and RMSE of 0.76 m2 m−2 and 141.4 g m−2, respectively) in the rice varieties studied (R2 = 0.937 (Basmati370), 0.837 (Nipponbare and IR64) for TDW, and 0.894 (Basmati370), 0.866 (Nipponbare and IR64) for LAI). The results of this study support the assertion of the benefits of DSM-derived CH for predicting biomass development. In addition, LAI and TDW could be estimated temporally and spatially using the UAV-based CSM, which is not easily affected by weather conditions.}, language = {en}, number = {12}, urldate = {2021-08-20}, journal = {Remote Sensing}, author = {Peprah, Clement Oppong and Yamashita, Megumi and Yamaguchi, Tomoaki and Sekino, Ryo and Takano, Kyohei and Katsura, Keisuke}, month = jan, year = {2021}, note = {Number: 12 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {precision agriculture, biomass, digital surface model, leaf area index, rice, unmanned aerial vehicle}, pages = {2388}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\9B4ULIGI\\2388.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\35XZPKB5\\Peprah et al. - 2021 - Spatio-Temporal Estimation of Biomass Growth in Ri.pdf:application/pdf}, } @article{jin_lidar_2021, title = {Lidar sheds new light on plant phenomics for plant breeding and management: {Recent} advances and future prospects}, volume = {171}, issn = {0924-2716}, shorttitle = {Lidar sheds new light on plant phenomics for plant breeding and management}, url = {https://www.sciencedirect.com/science/article/pii/S0924271620303130}, doi = {10.1016/j.isprsjprs.2020.11.006}, abstract = {Plant phenomics is a new avenue for linking plant genomics and environmental studies, thereby improving plant breeding and management. Remote sensing techniques have improved high-throughput plant phenotyping. However, the accuracy, efficiency, and applicability of three-dimensional (3D) phenotyping are still challenging, especially in field environments. Light detection and ranging (lidar) provides a powerful new tool for 3D phenotyping with the rapid development of facilities and algorithms. Numerous efforts have been devoted to studying static and dynamic changes of structural and functional phenotypes using lidar in agriculture. These progresses also improve 3D plant modeling across different spatial–temporal scales and disciplines, providing easier and less expensive association with genes and analysis of environmental practices and affords new insights into breeding and management. Beyond agriculture phenotyping, lidar shows great potential in forestry, horticultural, and grass phenotyping. Although lidar has resulted in remarkable improvements in plant phenotyping and modeling, the synthetization of lidar-based phenotyping for breeding and management has not been fully explored. We identify three main challenges in lidar-based phenotyping development: 1) developing low cost, high spatial–temporal, and hyperspectral lidar facilities, 2) moving into multi-dimensional phenotyping with an endeavor to generate new algorithms and models, and 3) embracing open source and big data.}, language = {en}, urldate = {2021-08-20}, journal = {ISPRS Journal of Photogrammetry and Remote Sensing}, author = {Jin, Shichao and Sun, Xiliang and Wu, Fangfang and Su, Yanjun and Li, Yumei and Song, Shiling and Xu, Kexin and Ma, Qin and Baret, Frédéric and Jiang, Dong and Ding, Yanfeng and Guo, Qinghua}, month = jan, year = {2021}, keywords = {Lidar, Management, Traits, Breeding, Multi-omics, Phenomics}, pages = {202--223}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\DPMHXS6K\\Jin et al. - 2021 - Lidar sheds new light on plant phenomics for plant.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\2MSQDXS7\\S0924271620303130.html:text/html}, } @article{zarco-tejada_tree_2014, title = {Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle ({UAV}) and automatic {3D} photo-reconstruction methods}, volume = {55}, issn = {1161-0301}, url = {https://www.sciencedirect.com/science/article/pii/S1161030114000069}, doi = {10.1016/j.eja.2014.01.004}, abstract = {This study provides insight into the assessment of canopy biophysical parameter retrieval using passive sensors and specifically into the quantification of tree height in a discontinuous canopy using a low-cost camera on board an unmanned aerial vehicle (UAV). The UAV was a 2-m wingspan fixed-wing platform with 5.8kg take-off weight and 63km/h ground speed. It carried a consumer-grade RGB camera modified for color-infrared detection (CIR) and synchronized with a GPS unit. In this study, the configuration of the electric UAV carrying the camera payload enabled the acquisition of 158ha in one single flight. The camera system made it possible to acquire very high resolution (VHR) imagery (5cmpixel−1) to generate ortho-mosaics and digital surface models (DSMs) through automatic 3D reconstruction methods. The UAV followed pre-designed flight plans over each study site to ensure the acquisition of the imagery with large across- and along-track overlaps (i.e. {\textgreater}80\%) using a grid of parallel and perpendicular flight lines. The validation method consisted of taking field measurements of the height of a total of 152 trees in two different study areas using a GPS in real-time kinematic (RTK) mode. The results of the validation assessment conducted to estimate tree height from the VHR DSMs yielded R2=0.83, an overall root mean square error (RMSE) of 35cm, and a relative root mean square error (R-RMSE) of 11.5\% for trees with heights ranging between 1.16 and 4.38m. An assessment conducted on the effects of the spatial resolution of the input images acquired by the UAV on the photo-reconstruction method and DSM generation demonstrated stable relationships for pixel resolutions between 5 and 30cm that rapidly degraded for input images with pixel resolutions lower than 35cm. RMSE and R-RMSE values obtained as a function of input pixel resolution showed errors in tree quantification below 15\% when 30cmpixel−1 resolution imagery was used to generate the DSMs. The study conducted in two orchards with this UAV system and the photo-reconstruction method highlighted that an inexpensive approach based on consumer-grade cameras on board a hand-launched unmanned aerial platform can provide accuracies comparable to those of the expensive and computationally more complex light detection and ranging (LIDAR) systems currently operated for agricultural and environmental applications.}, language = {en}, urldate = {2021-08-19}, journal = {European Journal of Agronomy}, author = {Zarco-Tejada, P. J. and Diaz-Varela, R. and Angileri, V. and Loudjani, P.}, month = apr, year = {2014}, keywords = {Remote sensing, 3D image modeling, DSM, Low-cost camera, Photo reconstruction, Tree height}, pages = {89--99}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\RVTJS6YI\\Zarco-Tejada et al. - 2014 - Tree height quantification using very high resolut.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\FKKZVH3B\\S1161030114000069.html:text/html}, } @article{chu_characterizing_2018, title = {Characterizing canopy height with {UAS} structure-from-motion photogrammetry—results analysis of a maize field trial with respect to multiple factors}, volume = {9}, issn = {2150-704X}, url = {https://doi.org/10.1080/2150704X.2018.1475771}, doi = {10.1080/2150704X.2018.1475771}, abstract = {Unmanned aircraft system (UAS) measured canopy height has frequently been determined by means of digital surface models (DSMs) derived from structure-from-motion (SfM) photogrammetry without examining specific metrics in detail. Multiple geospatial factors to be considered for the purpose of generating an accurate height estimation were characterized and summarized in this letter using UAS-SfM photogrammetry over an experimental maize field trial. This particular study demonstrated that: 1) the 99th percentile height in a 25 cm-wide crop row polygon provided the best canopy height estimation accuracy; 2) the height difference between using a rasterized DSM and direct three-dimensional (3D) point cloud was minor yet steadily increased when the DSM resolution value grew; and 3) the accuracy of the DSM-based canopy height estimation dropped significantly after the DSM resolution became coarser than 12 cm. Results also suggested that the cost function introduced in this letter has the potential to be used for optimizing the height estimation accuracy of various crop types given ground truth.}, number = {8}, urldate = {2021-08-19}, journal = {Remote Sensing Letters}, author = {Chu, Tianxing and Starek, Michael J. and Brewer, Michael J. and Murray, Seth C. and Pruter, Luke S.}, month = aug, year = {2018}, note = {Publisher: Taylor \& Francis \_eprint: https://doi.org/10.1080/2150704X.2018.1475771}, pages = {753--762}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\H72V9XPH\\Chu et al. - 2018 - Characterizing canopy height with UAS structure-fr.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\BP6G84TW\\2150704X.2018.html:text/html}, } @article{xie_crop_2021, title = {Crop height estimation based on {UAV} images: {Methods}, errors, and strategies}, volume = {185}, issn = {0168-1699}, shorttitle = {Crop height estimation based on {UAV} images}, url = {https://www.sciencedirect.com/science/article/pii/S0168169921001733}, doi = {10.1016/j.compag.2021.106155}, abstract = {Unmanned aerial vehicles (UAVs) have emerged as a promising platform for determining the dynamic phenotypic traits of crops in the field in a rapid and cost-effective manner. Crop height is a common and important phenotypic trait, and its acquisition with high accuracy usually requires spatial auxiliary (SA) information, such as a digital terrain model in the early growing season, digital surface models later in the season, ground control points, and ground truth of crop height. The reasonable selection of SA information involves balancing the cost and accuracy of crop height acquisition, but this problem has not been systematically studied and it needs to be resolved urgently in the agricultural industry. In this study, we compared four rapeseed height estimation methods using UAV images collected at three growth stages based on the structure from motion algorithm, where one method had complete data and the other three had incomplete SA information. To reduce the crop height estimation errors with incomplete data, improved methods were developed to construct the missing SA information. The optimum results were obtained using complete SA information, where R2 was 0.932 and the root mean square error (RMSE) was 0.026 m. For crop height acquisition using incomplete data, the R2 values could be controlled above 0.445 and RMSE below 0.146 m. In this study, systematic strategies were developed for selecting appropriate methods to acquire crop height with reasonable accuracy while balancing the cost requirement for use in scientific research and agricultural production.}, language = {en}, urldate = {2021-08-19}, journal = {Computers and Electronics in Agriculture}, author = {Xie, Tianjin and Li, Jijun and Yang, Chenghai and Jiang, Zhao and Chen, Yahui and Guo, Liang and Zhang, Jian}, month = jun, year = {2021}, keywords = {Precision agriculture, Crop height, Plant phenotyping, Structure from Motion, Systematic strategies, Unmanned aerial vehicle}, pages = {106155}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\M3F25UV9\\Xie et al. - 2021 - Crop height estimation based on UAV images Method.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ICYY5BPU\\S0168169921001733.html:text/html}, } @article{bendig_estimating_2014, title = {Estimating {Biomass} of {Barley} {Using} {Crop} {Surface} {Models} ({CSMs}) {Derived} from {UAV}-{Based} {RGB} {Imaging}}, volume = {6}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/6/11/10395}, doi = {10.3390/rs61110395}, abstract = {Crop monitoring is important in precision agriculture. Estimating above-ground biomass helps to monitor crop vitality and to predict yield. In this study, we estimated fresh and dry biomass on a summer barley test site with 18 cultivars and two nitrogen (N)-treatments using the plant height (PH) from crop surface models (CSMs). The super-high resolution, multi-temporal (1 cm/pixel) CSMs were derived from red, green, blue (RGB) images captured from a small unmanned aerial vehicle (UAV). Comparison with PH reference measurements yielded an R2 of 0.92. The test site with different cultivars and treatments was monitored during “Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie” (BBCH) Stages 24–89. A high correlation was found between PH from CSMs and fresh biomass (R2 = 0.81) and dry biomass (R2 = 0.82). Five models for above-ground fresh and dry biomass estimation were tested by cross-validation. Modelling biomass between different N-treatments for fresh biomass produced the best results (R2 = 0.71). The main limitation was the influence of lodging cultivars in the later growth stages, producing irregular plant heights. The method has potential for future application by non-professionals, i.e., farmers.}, language = {en}, number = {11}, urldate = {2021-08-19}, journal = {Remote Sensing}, author = {Bendig, Juliane and Bolten, Andreas and Bennertz, Simon and Broscheit, Janis and Eichfuss, Silas and Bareth, Georg}, month = nov, year = {2014}, note = {Number: 11 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {remote sensing, UAV, precision agriculture, 3D, RGB, biomass estimation, crop surface model, optical, plant height, summer barley}, pages = {10395--10412}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\CUMBY3VU\\Bendig et al. - 2014 - Estimating Biomass of Barley Using Crop Surface Mo.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\2Z3LP3FL\\htm.html:text/html}, } @article{hammerle_direct_2016, title = {Direct derivation of maize plant and crop height from low-cost time-of-flight camera measurements}, volume = {12}, issn = {1746-4811}, url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5127001/}, doi = {10.1186/s13007-016-0150-6}, abstract = {Background In agriculture, information about the spatial distribution of crop height is valuable for applications such as biomass and yield estimation, or increasing field work efficiency in terms of fertilizing, applying pesticides, irrigation, etc. Established methods for capturing crop height often comprise restrictions in terms of cost and time efficiency, flexibility, and temporal and spatial resolution of measurements. Furthermore, crop height is mostly derived from a measurement of the bare terrain prior to plant growth and measurements of the crop surface when plants are growing, resulting in the need of multiple field campaigns. In our study, we examine a method to derive crop heights directly from data of a plot of full grown maize plants captured in a single field campaign. We assess continuous raster crop height models (CHMs) and individual plant heights derived from data collected with the low-cost 3D camera Microsoft® Kinect® for Xbox One™ based on a comprehensive comparison to terrestrial laser scanning (TLS) reference data. Results We examine single measurements captured with the 3D camera and a combination of the single measurements, i.e. a combination of multiple perspectives. The quality of both CHMs, and individual plant heights is improved by combining the measurements. R2 of CHMs derived from single measurements range from 0.48 to 0.88, combining all measurements leads to an R2 of 0.89. In case of individual plant heights, an R2 of 0.98 is achieved for the combined measures (with R2 = 0.44 for the single measurements). The crop heights derived from the 3D camera measurements comprise an average underestimation of 0.06 m compared to TLS reference values. Conclusion We recommend the combination of multiple low-cost 3D camera measurements, removal of measurement artefacts, and the inclusion of correction functions to improve the quality of crop height measurements. Operating low-cost 3D cameras under field conditions on agricultural machines or on autonomous platforms can offer time and cost efficient tools for capturing the spatial distribution of crop heights directly in the field and subsequently to advance agricultural efficiency and productivity. More general, all processes which include the 3D geometry of natural objects can profit from low-cost methods producing 3D geodata. Electronic supplementary material The online version of this article (doi:10.1186/s13007-016-0150-6) contains supplementary material, which is available to authorized users.}, urldate = {2021-08-20}, journal = {Plant Methods}, author = {Hämmerle, Martin and Höfle, Bernhard}, month = nov, year = {2016}, pmid = {27933095}, pmcid = {PMC5127001}, pages = {50}, file = {PubMed Central Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\2J7KMZR9\\Hämmerle and Höfle - 2016 - Direct derivation of maize plant and crop height f.pdf:application/pdf}, } @article{li_remote_2016, title = {Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system}, volume = {67}, issn = {1470-160X}, url = {https://www.sciencedirect.com/science/article/pii/S1470160X16301406}, doi = {10.1016/j.ecolind.2016.03.036}, abstract = {Canopy height (Hcanopy) and aboveground biomass (AGB) of crops are two basic agro-ecological indicators that can provide important indications on the growth, light use efficiency, and carbon stocks in agro-ecosystems. In this study, hundreds of stereo images with very high resolution were collected to estimate Hcanopy and AGB of maize using a low-cost unmanned aerial vehicle (UAV) system. Millions of point clouds that are related to the structure from motion (SfM) were produced from the UAV stereo images through a photogrammetric workflow. Metrics that are commonly used in airborne laser scanning (ALS) were calculated from the SfM point clouds and were tested in the estimation of maize parameters for the first time. In addition, the commonly used spectral vegetation indices calculated from the UAV orthorectified image were also tested. Estimation models were established based on the UAV variables and field measurements with cross validation, during which the performance of the UAV variables was quantified. Finally, the following results were achieved: (1) the spatial patterns of maize Hcanopy and AGB were predicted by a multiple stepwise linear (SWL) regression model (R2=0.88, rRMSE=6.40\%) and a random forest regression (RF) model (R2=0.78, rRMSE=16.66\%), respectively. (2) The UAV-estimated maize parameters were proved to be comparable to the field measurements with a mean error (ME) of 0.11m for Hcanopy, and 0.05kg/m2 for AGB. (3) The SfM point metrics, especially the mean point height (Hmean) greatly contributed to the estimation model of maize Hcanopy and AGB, which can be promising indicators in the detection of maize biophysical parameters. To conclude, the variations in spectral and structural attributes for maize canopy should be simultaneously considered when only simple RGB images are available for estimating maize AGB. This study provides some suggestions on how to make full use of the low-cost and high-resolution UAV stereo images in precision agro-ecological applications and management.}, language = {en}, urldate = {2021-08-19}, journal = {Ecological Indicators}, author = {Li, Wang and Niu, Zheng and Chen, Hanyue and Li, Dong and Wu, Mingquan and Zhao, Wei}, month = aug, year = {2016}, keywords = {Canopy height, Maize biomass, Unmanned aerial vehicle, Point clouds, Stereo images}, pages = {637--648}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\GM7GLP3C\\Li et al. - 2016 - Remote estimation of canopy height and aboveground.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\FLMDU7G8\\S1470160X16301406.html:text/html}, } @article{wu_review_2021, title = {Review of {Weed} {Detection} {Methods} {Based} on {Computer} {Vision}}, volume = {21}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/21/11/3647}, doi = {10.3390/s21113647}, abstract = {Weeds are one of the most important factors affecting agricultural production. The waste and pollution of farmland ecological environment caused by full-coverage chemical herbicide spraying are becoming increasingly evident. With the continuous improvement in the agricultural production level, accurately distinguishing crops from weeds and achieving precise spraying only for weeds are important. However, precise spraying depends on accurately identifying and locating weeds and crops. In recent years, some scholars have used various computer vision methods to achieve this purpose. This review elaborates the two aspects of using traditional image-processing methods and deep learning-based methods to solve weed detection problems. It provides an overview of various methods for weed detection in recent years, analyzes the advantages and disadvantages of existing methods, and introduces several related plant leaves, weed datasets, and weeding machinery. Lastly, the problems and difficulties of the existing weed detection methods are analyzed, and the development trend of future research is prospected.}, language = {en}, number = {11}, urldate = {2021-08-20}, journal = {Sensors}, author = {Wu, Zhangnan and Chen, Yajun and Zhao, Bo and Kang, Xiaobing and Ding, Yuanyuan}, month = jan, year = {2021}, note = {Number: 11 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {deep learning, computer vision, machine learning, image processing, weed detection}, pages = {3647}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HYVAARV8\\Wu et al. - 2021 - Review of Weed Detection Methods Based on Computer.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\CHQGEQML\\3647.html:text/html}, } @article{lopez-granados_weed_2011, title = {Weed detection for site-specific weed management: mapping and real-time approaches}, volume = {51}, issn = {1365-3180}, shorttitle = {Weed detection for site-specific weed management}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-3180.2010.00829.x}, doi = {10.1111/j.1365-3180.2010.00829.x}, abstract = {López-Granados F (2011). Weed detection for site-specific weed management: mapping and real-time approaches. Weed Research 51, 1–11. Summary This work describes the current status of remote and proximal (on-ground) weed detection systems for site-specific weed management and discusses the limitations and opportunities of these technologies. Remote sensing based on multispectral aerial imagery can provide accurate weed maps, especially at late weed phenological stages, whereas images from high spatial resolution satellite and unmanned aerial vehicles must still be analysed. Hyperspectral images produce highly accurate maps at early and late phenological stages at a farm scale or medium spatial scale. However, this technology is not profitable, because of current operating costs, which are prohibitive. In studies of on-ground weed seedling detection, accurate results can be obtained at a medium farm scale. Despite numerous efforts, a powerful and flexible classifier of soil, weeds and crops in a number of situations, remains the greatest challenge of this technology. The main limitations of remote and proximal sensing may be summarised in the following two points: (i) the time and education required for applying new technological advances and (ii) the high cost of the technology and the lack of compatibility of the machinery. Possible solutions might include: (i) offering an advisory service that provides technical support, agronomic knowledge and specific training courses, (ii) the development and implementation of uniform and cheaper standards, (iii) increased research of both high resolution satellite imagery exploring object-based image analysis and pan-sharpened imagery and unmanned aerial vehicles (UAV) and (iv) enabling the development of current prototypes of robotic weeding into commercial products. The general lack of multidisciplinary research groups can be a disadvantage when comparing the economic feasibility of site-specific weed management with conventional systems.}, language = {en}, number = {1}, urldate = {2021-08-20}, journal = {Weed Research}, author = {López-Granados, F.}, year = {2011}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-3180.2010.00829.x}, keywords = {neural networks, remote sensing, precision agriculture, multispectral, hyperspectral, aerial and satellite imagery, machine vision, mapping weeds, robotic real-time, spectral signatures}, pages = {1--11}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\QFFSUM98\\López-Granados - 2011 - Weed detection for site-specific weed management .pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\EGFHPAY3\\j.1365-3180.2010.00829.html:text/html}, } @inproceedings{de_oca_low-cost_2018, title = {Low-cost multispectral imaging system for crop monitoring}, doi = {10.1109/ICUAS.2018.8453426}, abstract = {This work presents the design and development of a multispectral imaging system to precision agriculture tasks. The imaging system features two small digital cameras controlled by a microcomputer embedded in a drone. One of the cameras has been modified to be sensitive to near-infrared radiation reflected by the vegetation, whereas the other one remains as a common RGB camera. In order to determine the health status of the crop, the Normalized Difference Vegetation Index (NDVI) is computed in a developed software. Once the aerial imagery is obtained by the drone, it is processed to eliminate image distortions and insert specific metadata needed for generating the orthomosaics with the health information of the plant or soil of interest. Finally, the vegetation index will be computed from the visible and near-infrared orthomosaics for a better interpretation of the user. Experiments are presented to show the effectiveness of the system.}, booktitle = {2018 {International} {Conference} on {Unmanned} {Aircraft} {Systems} ({ICUAS})}, author = {de Oca, A. Montes and Arreola, L. and Flores, A. and Sanchez, J. and Flores, G.}, month = jun, year = {2018}, note = {ISSN: 2575-7296}, keywords = {Indexes, UAV, Agriculture, Mexico, Drones, Americas, Vegetation mapping, Precision Agriculture, Aerial photogrammetry, Cameras, Drone, Image georeferencing, Microcomputers, Multi-spectral Imaging, Normalized Difference Vegetation Index, Software}, pages = {443--451}, file = {IEEE Xplore Abstract Record:C\:\\Users\\Edify 01\\Zotero\\storage\\YQYKGQP7\\8453426.html:text/html;IEEE Xplore Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\88P2DZL6\\de Oca et al. - 2018 - Low-cost multispectral imaging system for crop mon.pdf:application/pdf}, } @article{gasparovic_automatic_2020, title = {An automatic method for weed mapping in oat fields based on {UAV} imagery}, volume = {173}, issn = {0168-1699}, url = {https://www.sciencedirect.com/science/article/pii/S016816991930359X}, doi = {10.1016/j.compag.2020.105385}, abstract = {The accurate detection and treatment of weeds in agricultural fields is a necessary procedure for managing crop yield and avoiding herbicide pollution. With the emergence of unmanned aerial vehicles (UAV), the ability to acquire spatial data at the desired spatial and temporal resolution became available, and the resulting input data met high standards for weed management. In this paper, we tested four independent classification algorithms for the creation of weed maps, combining automatic and manual methods, as well as object-based and pixel-based classification approaches, which were used separately on two subsets. Input UAV data were collected using a low-cost RGB camera due to its affordability compared to multispectral cameras. Classification algorithms were based on the random forest machine learning algorithm for weed and bare soil extraction, following an unsupervised classification with the K-means algorithm for further estimation of weeds and bare soil presence in non-weed and non-soil areas. Of the four classification algorithms tested, the automatic object-based classification method achieved the highest classification accuracy, resulting in an overall accuracy of 89.0\% for subset A and 87.1\% for subset B. Automatic classification methods were robustly developed, using at least 0.25\% of the scene size as the training data set in all circumstances anticipated for the random forest classification algorithm to operate. The use of the algorithm resulted in weed maps consisting of zoned classes and covering areas with similar biological properties, making them ready for use as inputs in weed treatments that use agricultural machinery.}, language = {en}, urldate = {2021-08-20}, journal = {Computers and Electronics in Agriculture}, author = {Gašparović, Mateo and Zrinjski, Mladen and Barković, Đuro and Radočaj, Dorijan}, month = jun, year = {2020}, keywords = {Precision agriculture, UAV, Imagery classification, Oats, Weed mapping}, pages = {105385}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\KJQUXJIX\\Gašparović et al. - 2020 - An automatic method for weed mapping in oat fields.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\9A2DU5Q5\\S016816991930359X.html:text/html}, } @incollection{mathyam_remote_2011, title = {Remote {Sensing} of {Biotic} {Stress} in {Crop} {Plants} and {Its} {Applications} for {Pest} {Management}}, isbn = {978-94-007-2219-4}, abstract = {Remote sensing (RS) of biotic stress is based on the assumption that stress interferes with photosynthesis and physical structure of the plant at tissue and canopy level, and thus affects the absorption of light energy and alters the refl ectance spectrum. Research into vegetative spectral refl ectance can help us gain a better understanding of the physical, physiological and chemical processes in plants due to pest and disease attack and to detect the resulting biotic stress. This has important implications to effective pest management. This review provides an overview of detection of various biotic stresses in different crops using various RS platforms. Previous work pertaining to the use of RS technique for assessing pest and disease severity using different RS techniques is briefl y summerized. The available sources of ground based, airborne and satellite sensors are presented along with various narrow band vegetation indices that could be used for characterizing biotic stress. Using relevant examples, the merits and demerits of various RS sensors and platforms for detection of pests and diseases are discussed. Pest surveillance programs such as fi eld scoutings are often expensive, time consuming, laborious and prone to error. As remote sensing gives a synoptic view of the area in a non-destructive and non-invasive way, this technology could be effective and provide timely information on spatial variability of pest damage over a large area. Thus remote sensing can guide scouting efforts and crop protection advisory in a more precise and effective manner. With the recent advancements in the communication, aviation and space technology, there is a lot of potential for application of remote sensing technology in the fi eld of pest management.}, booktitle = {Crop {Stress} and its {Management}: {Perspectives} and {Strategies}}, author = {Mathyam, Prabhakar and Yen, Prasad and Rao, Mahesh}, month = dec, year = {2011}, doi = {10.1007/978-94-007-2220-0_16}, note = {Journal Abbreviation: Crop Stress and its Management: Perspectives and Strategies}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\U4R9MZHT\\Mathyam et al. - 2011 - Remote Sensing of Biotic Stress in Crop Plants and.pdf:application/pdf}, } @article{hunt_detection_2017, title = {Detection of potato beetle damage using remote sensing from small unmanned aircraft systems}, volume = {11}, issn = {1931-3195, 1931-3195}, url = {https://www.spiedigitallibrary.org/journals/journal-of-applied-remote-sensing/volume-11/issue-2/026013/Detection-of-potato-beetle-damage-using-remote-sensing-from-small/10.1117/1.JRS.11.026013.short}, doi = {10.1117/1.JRS.11.026013}, abstract = {Colorado potato beetle (CPB) adults and larvae devour leaves of potato and other solanaceous crops and weeds, and may quickly develop resistance to pesticides. With early detection of CPB damage, more options are available for precision integrated pest management, which reduces the amount of pesticides applied in a field. Remote sensing with small unmanned aircraft systems (sUAS) has potential for CPB detection because low flight altitudes allow image acquisition at very high spatial resolution. A five-band multispectral sensor and up-looking incident light sensor were mounted on a six-rotor sUAS, which was flown at altitudes of 60 and 30 m in June 2014. Plants went from visibly undamaged to having some damage in just 1 day. Whole-plot normalized difference vegetation index (NDVI) and the number of pixels classified as damaged (0.70≤NDVI≤0.80) were not correlated with visible CPB damage ranked from least to most. Area of CPB damage estimated using object-based image analysis was highly correlated to the visual ranking of damage. Furthermore, plant height calculated using structure-from-motion point clouds was related to CPB damage, but this method required extensive operator intervention for success. Object-based image analysis has potential for early detection based on high spatial resolution sUAS remote sensing.}, number = {2}, urldate = {2021-08-20}, journal = {Journal of Applied Remote Sensing}, author = {Hunt, E. Raymond and Rondon, Silvia I.}, month = may, year = {2017}, note = {Publisher: International Society for Optics and Photonics}, keywords = {drone, Colorado potato beetle, Leptinotarsa decemlineata, multirotor, object-based image analysis, point clouds, Solanum tuberosum, spectral vegetation indices, structure-from-motion}, pages = {026013}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\CQRUT9Z5\\Hunt and Rondon - 2017 - Detection of potato beetle damage using remote sen.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\7MGSQLVU\\1.JRS.11.026013.html:text/html}, } @incollection{alchanatis_spectral_2011, title = {Spectral and {Spatial} {Methods} of {Hyperspectral} {Image} {Analysis} for {Estimation} of {Biophysical} and {Biochemical} {Properties} of {Agricultural} {Crops}}, isbn = {978-1-4398-4537-0}, author = {Alchanatis, Victor and Cohen, Y.}, month = oct, year = {2011}, doi = {10.1201/b11222-19}, pages = {289--308}, } @article{scharf_sensor-based_2011, title = {Sensor-{Based} {Nitrogen} {Applications} {Out}-{Performed} {Producer}-{Chosen} {Rates} for {Corn} in {On}-{Farm} {Demonstrations}}, volume = {103}, issn = {1435-0645}, url = {https://acsess.onlinelibrary.wiley.com/doi/abs/10.2134/agronj2011.0164}, doi = {10.2134/agronj2011.0164}, abstract = {Optimal N fertilizer rate for corn (Zea mays L.) and other crops can vary substantially within and among fields. Current N management practices do not address this variability. Crop reflectance sensors offer the potential to diagnose crop N need and control N application rates at a fine spatial scale. Our objective was to evaluate the performance of sensor-based variable-rate N applications to corn, relative to constant N rates chosen by the producer. Fifty-five replicated on-farm demonstrations were conducted from 2004 to 2008. Sensors were installed on the producer's N application equipment and used to direct variable-rate sidedress N applications to corn at growth stages ranging from V6 to V16. A fixed N rate chosen by the cooperating producer was also applied. Relative to the producer's N rate, sensors increased partial profit by \$42 ha−1 (P = 0.0007) and yield by 110 kg ha−1 (P = 0.18) while reducing N use by 16 kg N ha−1 (P = 0.015). This represents a reduction of approximately 25\% in the amount of N applied beyond what was removed in the grain, thus reducing unused N that can move to water or air. Our results confirm that sensors can choose N rates for corn that perform better than rates chosen by producers.}, language = {en}, number = {6}, urldate = {2021-08-11}, journal = {Agronomy Journal}, author = {Scharf, Peter C. and Shannon, D. Kent and Palm, Harlan L. and Sudduth, Kenneth A. and Drummond, Scott T. and Kitchen, Newell R. and Mueller, Larry J. and Hubbard, Victoria C. and Oliveira, Luciane F.}, year = {2011}, note = {\_eprint: https://acsess.onlinelibrary.wiley.com/doi/pdf/10.2134/agronj2011.0164}, keywords = {Precision Agriculture, Remote Sensing, N-application, Variable rate}, pages = {1683--1691}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\IX7P2KKB\\agronj2011.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HUXPA5JR\\Scharf et al. - 2011 - Sensor-Based Nitrogen Applications Out-Performed P.pdf:application/pdf}, } @article{huang_agricultural_2018, title = {Agricultural remote sensing big data: {Management} and applications}, volume = {17}, issn = {2095-3119}, shorttitle = {Agricultural remote sensing big data}, url = {https://www.sciencedirect.com/science/article/pii/S2095311917618598}, doi = {10.1016/S2095-3119(17)61859-8}, abstract = {Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures. Agricultural remote sensing is one of the backbone technologies for precision agriculture, which considers within-field variability for site-specific management instead of uniform management as in traditional agriculture. The key of agricultural remote sensing is, with global positioning data and geographic information, to produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote sensing data resources, recent development of technologies for remote sensing big data management, and remote sensing data processing and management for precision agriculture. A five-layer-fifteen-level (FLFL) satellite remote sensing data management structure is described and adapted to create a more appropriate four-layer-twelve-level (FLTL) remote sensing data management structure for management and applications of agricultural remote sensing big data for precision agriculture where the sensors are typically on high-resolution satellites, manned aircrafts, unmanned aerial vehicles and ground-based structures. The FLTL structure is the management and application framework of agricultural remote sensing big data for precision agriculture and local farm studies, which outlooks the future coordination of remote sensing big data management and applications at local regional and farm scale.}, language = {en}, number = {9}, urldate = {2021-08-12}, journal = {Journal of Integrative Agriculture}, author = {Huang, Yanbo and Chen, Zhong-xin and Yu, Tao and Huang, Xiang-zhi and Gu, Xing-fa}, month = sep, year = {2018}, keywords = {remote sensing, precision agriculture, big data, China, Americas, US, agricultural information, East Asia}, pages = {1915--1931}, file = {ScienceDirect Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\MYTZ4XQR\\Huang et al. - 2018 - Agricultural remote sensing big data Management a.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\CAH9M9VF\\S2095311917618598.html:text/html}, } @article{delgado_big_2019, title = {Big {Data} {Analysis} for {Sustainable} {Agriculture} on a {Geospatial} {Cloud} {Framework}}, volume = {3}, doi = {10.3389/fsufs.2019.00054}, abstract = {Humanity is confronted with the grand challenge of how to increase agricultural production to achieve food security during the 21st century and feed a population that is expected to grow to 10 billion people. This needs to be done while maintaining sustainable agricultural systems and simultaneously facing challenges such as a changing climate, depletion of water resources, and the potential for increased erosion and loss of productivity due to the occurrence of extreme weather events. Precision Agriculture emerged out of the advances in the 1980s because of the development of several key technologies like GPS and satellite imagery. This paper argues that with the increasing impact of climate change, the next revolution in precision agriculture and agriculture in general will be driven by Sustainable Precision Agriculture and Environment (SPAE, similar to the 7 Rs), which could leverage past technologies combined with Big Data analysis. This new, technology-focused SPAE transitions from a site-specific management focus to the notion of global sustainability. To accomplish this transition, we introduced the WebGIS framework as an organizing principle that connects local, site-specific data generators called smart farms to a regional and global view of agriculture that can support both the agricultural industry and policymakers in government. This will help integrate databases located in networks of networks into a system of systems to achieve the needed SPAE management and connect field, watershed, national, and worldwide sustainability. Automation and the use of artificial intelligence (AI), internet of things (IoT), drones, robots, and Big Data serve as a basis for a global “Digital Twin,” which will contribute to the development of site-specific conservation and management practices that will increase incomes and global sustainability of agricultural systems.}, journal = {Frontiers in Sustainable Food Systems}, author = {Delgado, Jorge and Short, Nicholas and Roberts, Daniel and Vandenberg, Bruce}, month = jul, year = {2019}, keywords = {big data, Americas, big data analysis, US}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\N5YL3EYW\\Delgado et al. - 2019 - Big Data Analysis for Sustainable Agriculture on a.pdf:application/pdf}, } @misc{noauthor_use_nodate, title = {Use controlled traffic farming}, url = {https://www.gov.uk/guidance/use-controlled-traffic-farming}, abstract = {Find out how land managers can reduce soil compaction, improve soil health and reduce runoff by using controlled traffic farming.}, language = {en}, urldate = {2021-08-17}, journal = {GOV.UK}, keywords = {UK, CTF}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\7CTPDLM8\\use-controlled-traffic-farming.html:text/html}, } @misc{noauthor_controlled_nodate, title = {Controlled {Traffic} {Farming}}, url = {http://www.controlledtrafficfarming.com/Home/Default.aspx}, urldate = {2021-08-17}, keywords = {UK, CTF}, file = {Controlled Traffic Farming:C\:\\Users\\Edify 01\\Zotero\\storage\\7WDA5SKH\\Default.html:text/html}, } @article{campana_drones_2017, title = {Drones in {Archaeology}. {State}-of-the-art and {Future} {Perspectives}}, volume = {24}, issn = {1099-0763}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1569}, doi = {10.1002/arp.1569}, abstract = {In addition to traditional platforms for low-level remote sensing (balloons, kites, etc.) new and more complex automated systems [unmanned aerial vehicles (UAVs) or drones] have become available in the last decade. The success and market expansion of these platforms has been a driving force in the development of active and passive sensors specifically designed for UAVs. In the last few years archaeologists have started testing both platforms and sensors, particularly for the following applications: three-dimensional (3D) documentation of archaeological excavations; 3D survey of monuments and historic buildings; survey of archaeological sites and landscapes; exploratory aerial survey; and the archaeological survey of woodland areas. The scale of these applications has ranged from site-based to landscapes-based (approximately up to about 10 km2 in extent). The role of such platforms in the archaeological survey of excavations and landscapes, and in diagnostics more generally, is of great interest and is inexorably growing. Copyright © 2017 John Wiley \& Sons, Ltd.}, language = {en}, number = {4}, urldate = {2021-09-01}, journal = {Archaeological Prospection}, author = {Campana, Stefano}, year = {2017}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1569}, keywords = {aerial reconnaissance, Europe, 3D modelling, Italy, 3D survey, UAV archaeology, woodland archaeology}, pages = {275--296}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\HYWD24H6\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\BGZYX7BS\\Campana - 2017 - Drones in Archaeology. State-of-the-art and Future.pdf:application/pdf}, } @article{vaart_applying_nodate, title = {Applying automated object detection in archaeological practice: {A} case study from the southern {Netherlands}}, volume = {n/a}, copyright = {© 2021 The Authors. Archaeological Prospection published by John Wiley \& Sons Ltd.}, issn = {1099-0763}, shorttitle = {Applying automated object detection in archaeological practice}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1833}, doi = {10.1002/arp.1833}, abstract = {Within archaeological prospection, Deep Learning algorithms are developed to detect objects within large remotely sensed datasets. These approaches are generally tested in an (ideal) experimental setting but have not been applied in different contexts or ‘in the wild’, that is, incorporated in archaeological prospection. This research explores the applicability, knowledge discovery—on both a quantitative and qualitative level—and efficiency gain resulting from employing an automated detection tool called WODAN within (Dutch) archaeological practice. WODAN has been used to detect barrows and Celtic fields in LiDAR data from the Dutch Midden-Limburg area, which differs in archaeology, geo-(morpho)logy and land-use from the Veluwe in which it was developed. The results show that WODAN was able to detect potential barrows and Celtic fields, including previously unknown examples, and provided information about the structuring of the landscape in the past. Based on the results, combined human-computer strategies are argued, in which automated detection has a complementary, rather than a substitute role, to manual analysis. This can offset the inherent biases in manual analysis and deal with the problem that current automated detection methods only detect objects similar to the pre-defined target class(es). The incorporation of automated detection into archaeological prospection, in which the results of automated detection are used to highlight areas of interest and to enhance and add detail to existing archaeological predictive maps, seems logical and feasible.}, language = {en}, number = {n/a}, urldate = {2021-09-01}, journal = {Archaeological Prospection}, author = {Vaart, Wouter B. Verschoof-van der and Lambers, Karsten}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1833}, keywords = {deep learning, Lidar, archaeological prospection, landscape archaeology, Netherlands, object detection}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\P28VGFBB\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\4BE6AGLX\\Vaart and Lambers - Applying automated object detection in archaeologi.pdf:application/pdf}, } @article{tapete_detection_2019, title = {Detection of {Archaeological} {Looting} from {Space}: {Methods}, {Achievements} and {Challenges}}, volume = {11}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Detection of {Archaeological} {Looting} from {Space}}, url = {https://www.mdpi.com/2072-4292/11/20/2389}, doi = {10.3390/rs11202389}, abstract = {Illegal excavations in archaeological heritage sites (namely “looting”) are a global phenomenon. Satellite images are nowadays massively used by archaeologists to systematically document sites affected by looting. In parallel, remote sensing scientists are increasingly developing processing methods with a certain degree of automation to quantify looting using satellite imagery. To capture the state-of-the-art of this growing field of remote sensing, in this work 47 peer-reviewed research publications and grey literature are reviewed, accounting for: (i) the type of satellite data used, i.e., optical and synthetic aperture radar (SAR); (ii) properties of looting features utilized as proxies for damage assessment (e.g., shape, morphology, spectral signature); (iii) image processing workflows; and (iv) rationale for validation. Several scholars studied looting even prior to the conflicts recently affecting the Middle East and North Africa (MENA) region. Regardless of the method used for looting feature identification (either visual/manual, or with the aid of image processing), they preferred very high resolution (VHR) optical imagery, mainly black-and-white panchromatic, or pansharpened multispectral, whereas SAR is being used more recently by specialist image analysts only. Yet the full potential of VHR and high resolution (HR) multispectral information in optical imagery is to be exploited, with limited research studies testing spectral indices. To fill this gap, a range of looted sites across the MENA region are presented in this work, i.e., Lisht, Dashur, and Abusir el Malik (Egypt), and Tell Qarqur, Tell Jifar, Sergiopolis, Apamea, Dura Europos, and Tell Hizareen (Syria). The aim is to highlight: (i) the complementarity of HR multispectral data and VHR SAR with VHR optical imagery, (ii) usefulness of spectral profiles in the visible and near-infrared bands, and (iii) applicability of methods for multi-temporal change detection. Satellite data used for the demonstration include: HR multispectral imagery from the Copernicus Sentinel-2 constellation, VHR X-band SAR data from the COSMO-SkyMed mission, VHR panchromatic and multispectral WorldView-2 imagery, and further VHR optical data acquired by GeoEye-1, IKONOS-2, QuickBird-2, and WorldView-3, available through Google Earth. Commonalities between the different image processing methods are examined, alongside a critical discussion about automation in looting assessment, current lack of common practices in image processing, achievements in managing the uncertainty in looting feature interpretation, and current needs for more dissemination and user uptake. Directions toward sharing and harmonization of methodologies are outlined, and some proposals are made with regard to the aspects that the community working with satellite images should consider, in order to define best practices of satellite-based looting assessment.}, language = {en}, number = {20}, urldate = {2021-09-01}, journal = {Remote Sensing}, author = {Tapete, Deodato and Cigna, Francesca}, month = jan, year = {2019}, note = {Number: 20 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {looting, Europe, SAR, Italy, archaeological remote sensing, change detection, COSMO-SkyMed, feature extraction, pattern recognition, Sentinel-2, VHR optical, WordView-2}, pages = {2389}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\DL5UY2LJ\\Tapete and Cigna - 2019 - Detection of Archaeological Looting from Space Me.pdf:application/pdf}, } @article{zhurbin_non-destructive_2020, title = {Non-destructive approach for studying medieval settlements destroyed by ploughing: combining aerial photography, geophysical and soil surveys}, volume = {27}, copyright = {© 2020 John Wiley \& Sons, Ltd.}, issn = {1099-0763}, shorttitle = {Non-destructive approach for studying medieval settlements destroyed by ploughing}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1778}, doi = {10.1002/arp.1778}, abstract = {The procedure for studying medieval settlements destroyed by ploughing is applied to one of the largest Finno-Ugric ancient settlement sites of western Urals, Guryakar (ninth–thirteenth centuries ad). The approach implies the consistent use of a number of mutually confirming non-destructive methods of survey: aerial photography using unmanned aerial vehicles followed by geophysical and soil surveying. Aerial photography in the visible spectrum enables the evaluation of possible settlement boundaries. The wavelet transmission of multispectral aerial photography data makes it possible to disclose the areas of the preserved cultural layer. A set of geophysical methods (resistivity survey, magnetic survey and electrical resistivity tomography) is used to verify and analyse these data. Additionally, geophysics makes it possible to identify fortifications and diverse layout objects that are not expressed by the surface topography. Follow-up soil drilling is a way to verify the proposed reconstruction of the layout, and the study of the chemical properties of soil cores makes it possible to justify the boundaries of the residential and industrial areas of the settlement. For this purpose, in the final stage, statistical processing of the chemical properties of soil materials is carried out (principal component analysis and the k-means algorithm classification). This approach complements the comparative analysis of diverse data and significantly increases the reliability of historical reconstruction. Interdisciplinary studies conducted at the medieval Finno-Ugric settlement of ancient Guryakar allowed fundamentally new information to be obtained for use in historical reconstructions: this work revealed a previously unknown line of the layered fortification system, reconstructed the layout of all four structural parts of the settlement and justified diverse building areas.}, language = {en}, number = {4}, urldate = {2021-09-01}, journal = {Archaeological Prospection}, author = {Zhurbin, Igor V. and Borisov, Alexander V.}, year = {2020}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1778}, keywords = {Europe, principal components analysis, Russia, fortification system, geophysics, layout, morphological and chemical soil properties, multispectral images}, pages = {343--360}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\KU2CUPK3\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\V34P9884\\Zhurbin and Borisov - 2020 - Non-destructive approach for studying medieval set.pdf:application/pdf}, } @article{davis_aerial_nodate, title = {The aerial panopticon and the ethics of archaeological remote sensing in sacred cultural spaces}, volume = {n/a}, copyright = {© 2021 John Wiley \& Sons, Ltd.}, issn = {1099-0763}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1819}, doi = {10.1002/arp.1819}, abstract = {Remote sensing technology has become a standard tool for archaeological prospecting. Yet the ethical guidelines associated with the use of these technologies are not well established and are even less-often discussed in published literature. With a nearly unobstructed view of large geographic spaces, aerial and spaceborne remote sensing technology creates an asymmetrical power dynamic between observers and the observed. Here, we explore the power dynamics involved with aerial and spaceborne remote sensing, using Foucault's notion of power and the panopticon. In many other areas of archaeological practice, such power imbalances have been actively confronted by collaborative approaches and community engagement, but remote sensing archaeology has been largely absent from such interventions. We discuss how aerial and spaceborne imagery is perceived by local communities in southwest Madagascar and advocate for a more collaborative approach to remote sensing archaeology that includes local stakeholders and researchers in all levels of data acquisition, analysis, and dissemination.}, language = {en}, number = {n/a}, urldate = {2021-09-01}, journal = {Archaeological Prospection}, author = {Davis, Dylan S. and Buffa, Danielle and Rasolondrainy, Tanambelo and Creswell, Ebony and Anyanwu, Chiamaka and Ibirogba, Abiola and Randolph, Clare and Ouarghidi, Abderrahim and Phelps, Leanne N. and Lahiniriko, François and Chrisostome, Zafy Maharesy and Manahira, George and Douglass, Kristina}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1819}, keywords = {remote sensing, Africa, community archaeology, ethics, Madagascar, surveillance}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\W3YCHYD9\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\55MH92U2\\Davis et al. - The aerial panopticon and the ethics of archaeolog.pdf:application/pdf}, } @article{fisher_ethical_nodate, title = {Ethical considerations for remote sensing and open data in relation to the endangered archaeology in the {Middle} {East} and {North} {Africa} project}, volume = {n/a}, copyright = {© 2021 The Authors. Archaeological Prospection published by John Wiley \& Sons Ltd.}, issn = {1099-0763}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1816}, doi = {10.1002/arp.1816}, abstract = {The UK-based Endangered Archaeology in the Middle East and North Africa (EAMENA) project uses remote sensing techniques to rapidly record and evaluate the status of archaeological and cultural heritage sites in the MENA region. Applying remote sensing methods to the archaeological landscapes of 20 countries, EAMENA is one of the largest documentation projects of its kind. Such a scope raises important ethical questions fundamental to the practice of remote-sensed archaeology, and this paper contributes to this discussion by reflecting on EAMENA's unique role in this subfield. We present ethical issues and possible solutions related to remote sensing and archaeology, drawing on models developed within the humanitarian aid sector and postcolonial archaeology. In addition, we consider issues of national sovereignty and their relationship to the engagement of local communities. Finally, this paper examines the roles of data openness and open access policies as ethical factors and how EAMENA has addressed these so far.}, language = {en}, number = {n/a}, urldate = {2021-09-01}, journal = {Archaeological Prospection}, author = {Fisher, Michael and Fradley, Michael and Flohr, Pascal and Rouhani, Bijan and Simi, Francesca}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1816}, keywords = {archaeology, remote sensing, ethics, cultural heritage preservation, Middle East and North Africa, open data}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\S7UQQTNJ\\Fisher et al. - Ethical considerations for remote sensing and open.pdf:application/pdf}, } @article{tapete_regional-scale_2021, title = {Regional-{Scale} {Systematic} {Mapping} of {Archaeological} {Mounds} and {Detection} of {Looting} {Using} {COSMO}-{SkyMed} {High} {Resolution} {DEM} and {Satellite} {Imagery}}, volume = {13}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/13/16/3106}, doi = {10.3390/rs13163106}, abstract = {“Tells” are archaeological mounds formed by deposition of large amounts of anthropogenic material and sediments over thousands of years and are the most important and prominent features in Near and Middle Eastern archaeological landscapes. In the last decade, archaeologists have exploited free-access global digital elevation model (DEM) datasets at medium resolution (i.e., up to 30 m) to map tells on a supra-regional scale and pinpoint tentative tell sites. Instead, the potential of satellite DEMs at higher resolution for this task was yet to be demonstrated. To this purpose, the 3 m resolution imaging capability allowed by the Italian Space Agency’s COSMO-SkyMed Synthetic Aperture Radar (SAR) constellation in StripMap HIMAGE mode was used in this study to generate DEM products of enhanced resolution to undertake, for the first time, a systematic mapping of tells and archaeological deposits. The demonstration is run at regional scale in the Governorate of Wasit in central Iraq, where the literature suggested a high density of sites, despite knowledge gaps about their location and spatial distribution. Accuracy assessment of the COSMO-SkyMed DEM is provided with respect to the most commonly used SRTM and ALOS World 3D DEMs. Owing to the 10 m posting and the consequent enhanced observation capability, the COSMO-SkyMed DEM proves capable to detect both well preserved and levelled or disturbed tells, standing out for more than 4 m from the surrounding landscape. Through the integration with CORONA KH-4B tiles, 1950s Soviet maps and recent Sentinel-2 multispectral images, the expert-led visual identification and manual mapping in the GIS environment led to localization of tens of sites that were not previously mapped, alongside the computation of a figure as up-to-date as February 2019 of the survived tells, with those affected by looting. Finally, this evidence is used to recognize hot-spot areas of potential concern for the conservation of tells. To this purpose, we upgraded the spatial resolution of the observations up to 1 m by using the Enhanced Spotlight mode to collect a bespoke time series. The change detection tests undertaken on selected clusters of disturbed tells prove how a dedicated monitoring activity may allow a regular observation of the impacts due to anthropogenic disturbance (e.g., road and canal constructions or ploughing).}, language = {en}, number = {16}, urldate = {2021-09-01}, journal = {Remote Sensing}, author = {Tapete, Deodato and Traviglia, Arianna and Delpozzo, Eleonora and Cigna, Francesca}, month = jan, year = {2021}, note = {Number: 16 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {digital elevation model, COSMO-SkyMed, Sentinel-2, Middle East, Iraq, synthetic aperture radar, Wasit}, pages = {3106}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JMCIDDV2\\3106.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\JUXH5TVC\\Tapete et al. - 2021 - Regional-Scale Systematic Mapping of Archaeologica.pdf:application/pdf}, } @article{roiha_hidden_2021, title = {The {Hidden} {Cairns}—{A} {Case} {Study} of {Drone}-{Based} {ALS} as an {Archaeological} {Site} {Survey} {Method}}, volume = {13}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/13/10/2010}, doi = {10.3390/rs13102010}, abstract = {Conducting archaeological site surveys is time consuming, and large sites may have many small features or structures that are difficult to locate and interpret. Vegetation cover and dense forest hide small structures, like cairns, while at the same time forest cover can cause problems for LiDAR tools. In this case study, drone-based ALS (airborne laser scanning) was tested as an archaeological site survey tool. The research site was complex and located partially in a forested area, which made it possible to evaluate how forest cover affects data. The survey methods used were rather simple: visual analysis, point density calculations in the forest area, and, for site interpretation purposes, digitizing observations and viewshed analysis. Using straightforward methods allowed us to evaluate the minimum time and skills needed for this type of survey. Drone-based ALS provided good results and increased knowledge of the site and its structures. Estimates of the number of cairns interpreted as graves more than doubled as a result of the high-accuracy ALS data. Based on the results of this study, drone-based ALS could be a suitable high-accuracy survey method for large archaeological sites. However, forest cover affects the accuracy, and more research is needed.}, language = {en}, number = {10}, urldate = {2021-09-01}, journal = {Remote Sensing}, author = {Roiha, Johanna and Heinaro, Einari and Holopainen, Markus}, month = jan, year = {2021}, note = {Number: 10 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {archaeology, cultural heritage, remote sensing, LiDAR, UAV, drone, survey}, pages = {2010}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\2HP7IN6G\\Roiha et al. - 2021 - The Hidden Cairns—A Case Study of Drone-Based ALS .pdf:application/pdf}, } @article{doneus_new_2014, title = {New ways to extract archaeological information from hyperspectral pixels}, volume = {52}, issn = {0305-4403}, url = {https://www.sciencedirect.com/science/article/pii/S0305440314003100}, doi = {10.1016/j.jas.2014.08.023}, abstract = {Airborne remote sensing for archaeology is the discipline that encompasses the study of archaeological remains using data collected from an airborne platform by means of digital or film-based aerial photography, airborne laser scanning, hyperspectral imaging etc. So far, airborne hyperspectral scanning or – more accurately – airborne imaging spectroscopy (AIS) has occupied only a very small niche in the field of archaeological remote sensing: besides reasons of cost, the common archaeologically-insufficient ground-sampling distance can be considered the main limiting factor. Moreover, the technical processing of these data sets with a high level of potential redundancy needs specialized software. Typically, calculation of band ratios and a principal component analysis are applied. As a result, the few practical applications of archaeological AIS have not been entirely convincing so far. The aim of this paper is to present new approaches for analysing archaeological AIS data. The imagery under study has a ground-sampling distance of 40 cm and covers the Roman town of Carnuntum (Austria). Using two algorithms embedded in a specifically developed MATLAB® toolbox, it will be shown how the extracted archaeological information can be enhanced from high-resolution hyperspectral images. A comparison with simultaneously acquired vertical photographs will indicate the specific advantages of high-resolution AIS data and the gain one can obtain when exploiting its potential using any of the newly presented methods.}, language = {en}, urldate = {2021-09-02}, journal = {Journal of Archaeological Science}, author = {Doneus, Michael and Verhoeven, Geert and Atzberger, Clement and Wess, Michael and Ruš, Michal}, month = dec, year = {2014}, keywords = {Archaeological prospection, Europe, hyperspectral, Airborne imaging spectroscopy, Austria, Distribution fitting, High-resolution, MATLAB, Red edge inflection point (REIP)}, pages = {84--96}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\5DMZ3DS6\\S0305440314003100.html:text/html}, } @article{zaina_multi-temporal_2021, title = {A multi-temporal satellite-based risk analysis of archaeological sites in {Qazvin} plain ({Iran})}, volume = {n/a}, issn = {1099-0763}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1818}, doi = {10.1002/arp.1818}, abstract = {In recent decades, we have witnessed a dramatic increase in the risks and damages to archaeological sites and heritage places across the globe. By analysing a case study (the Qazvin plain) in northern Iran, we propose a classification of the types of risks and damages to archaeological sites and we assess the impact of each type over the last 40 years (1980s–2020s). Our research methodology consists of the cross-correlated multi-temporal analysis of different sets of satellite imagery with 167 archaeological sites in the Qazvin plain to determine the types, extension and evolution of the damages over the time. This methodology allowed to develop a three-tier hierarchical framework based on the drivers, threats, and actions jeopardizing the cultural heritage of the region. The result of this study permits to overturn current narratives inferring that the most impacting risks to archaeological sites and heritage places are caused by natural hazards, looting and violent destruction rather than agricultural activity or construction. Consequently, based on this evidence, we draw a distinction between ‘silent’ but constant and pervasive and ‘loud’ but short-living and circumscribed risks.}, language = {en}, number = {n/a}, urldate = {2021-09-02}, journal = {Archaeological Prospection}, author = {Zaina, Federico and Mazloumi, Yasaman Nabati}, year = {2021}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1818}, keywords = {cultural heritage, GIS, remote sensing, landscape archaeology, archaeological risk analysis, Iran, Middle East}, pages = {1--17}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\WVG866VU\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\2VAZM6G3\\Zaina and Mazloumi - A multi-temporal satellite-based risk analysis of .pdf:application/pdf}, } @article{agapiou_earth_2020, title = {Earth {Observation} {Contribution} to {Cultural} {Heritage} {Disaster} {Risk} {Management}: {Case} {Study} of {Eastern} {Mediterranean} {Open} {Air} {Archaeological} {Monuments} and {Sites}}, volume = {12}, copyright = {http://creativecommons.org/licenses/by/3.0/}, shorttitle = {Earth {Observation} {Contribution} to {Cultural} {Heritage} {Disaster} {Risk} {Management}}, url = {https://www.mdpi.com/2072-4292/12/8/1330}, doi = {10.3390/rs12081330}, abstract = {Disaster risk management (DRM) for cultural heritage is a complex task that requires multidisciplinary cooperation. This short communication underlines the critical role of satellite remote sensing (also known as earth observation) in DRM in dealing with various hazards for cultural heritage sites and monuments. Here, satellite observation potential is linked with the different methodological steps of the DRM cycle. This is achieved through a short presentation of recent paradigms retrieved from research studies and the Scopus scientific repository. The communication focuses on the Eastern Mediterranean region, an area with an indisputable wealth of archaeological sites. Regarding the cultural heritage type, this article considers relevant satellite observation studies implemented in open-air archaeological monuments and sites. The necessity of this communication article emerged while trying to bring together earth observation means, cultural heritage needs, and DRM procedures.}, language = {en}, number = {8}, urldate = {2021-09-02}, journal = {Remote Sensing}, author = {Agapiou, Athos and Lysandrou, Vasiliki and Hadjimitsis, Diofantos G.}, month = jan, year = {2020}, note = {Number: 8 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {archaeology, cultural heritage, Europe, earth observation, Copernicus program, disaster risk management, Eastern Mediterranean, Near East}, pages = {1330}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\RXAN3G67\\1330.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\Z69ASZZ9\\Agapiou et al. - 2020 - Earth Observation Contribution to Cultural Heritag.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\BAZKRSKE\\1330.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\GDVSTPJU\\Agapiou et al. - 2020 - Earth Observation Contribution to Cultural Heritag.pdf:application/pdf}, } @article{lim_nuna_2021, title = {Nuna {Nalluyuituq} ({The} {Land} {Remembers}): {Remembering} landscapes and refining methodologies through community-based remote sensing in the {Yukon}-{Kuskokwim} {Delta}, {Southwest} {Alaska}}, volume = {28}, issn = {1099-0763}, shorttitle = {Nuna {Nalluyuituq} ({The} {Land} {Remembers})}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1840}, doi = {10.1002/arp.1840}, abstract = {The following article outlines a collaborative, multidisciplinary approach to remote sensing in Southwest Alaska's Yukon-Kuskokwim (Y-K) Delta that combines ethnographic inquiry and remote sensing to monitor, detect and preserve cultural resources for Alaskan Native communities. Because distinctive vegetation differences are readily visible on cultural sites during the summer months, the analysis of multispectral imagery obtained from remote sensing is particularly useful. In turn, we demonstrate the efficacy of this protocol on pre-contact settlement sites along the Ayakulik River system on Kodiak Island using a normalized difference vegetation index (NDVI) raster of the study area. Here, support vector machine (SVM) supervised classification was highly effective at identifying spectral patterns associated with anthropogenic activity while ethnographic data helped rule out false-positive cases. In addition, we provide the results of a 2019 archaeological prospection survey carried out in conjunction with the ongoing Nunalleq Project in Quinhagak, Alaska, to further highlight the value of ethnographic data collection, ethnobotanical surveys and unmanned aerial vehicle (UAV)-based spectroscopy alongside SVM supervised classification. Finally, we propose three suggestions for future research on Yup'ik landscapes in the Y-K Delta regarding citizen science, language preservation and the use of collaborative online maps for community-based decision making.}, language = {en}, number = {3}, urldate = {2021-09-02}, journal = {Archaeological Prospection}, author = {Lim, Jonathan S. and Gleason, Sean and Jones, Warren and Church, Willard}, year = {2021}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1840}, keywords = {erosion, vegetation indices, climate change, ethnoarchaeology, indigenous communities, satellite and UAV remote sensing}, pages = {339--355}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\E8PX6XVP\\Lim et al. - Nuna Nalluyuituq (The Land Remembers) Remembering.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\4HAUJJE8\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\H6S4GFVX\\Lim et al. - 2021 - Nuna Nalluyuituq (The Land Remembers) Remembering.pdf:application/pdf}, } @misc{noauthor_elms_nodate, title = {{ELMS} {DEFRA}'s plans - download the government paper here {\textbar} {Precision} {Decisions}}, url = {https://www.precisiondecisions.co.uk/agriculture/elms}, urldate = {2021-09-06}, file = {ELMS DEFRA's plans - download the government paper here | Precision Decisions:C\:\\Users\\Edify 01\\Zotero\\storage\\UU2PGTSG\\elms.html:text/html}, } @article{chen_remote_2021, title = {Remote {Sensing} {Image} {Augmentation} {Based} on {Text} {Description} for {Waterside} {Change} {Detection}}, volume = {13}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/13/10/1894}, doi = {10.3390/rs13101894}, abstract = {Since remote sensing images are difficult to obtain and need to go through a complicated administrative procedure for use in China, it cannot meet the requirement of huge training samples for Waterside Change Detection based on deep learning. Recently, data augmentation has become an effective method to address the issue of an absence of training samples. Therefore, an improved Generative Adversarial Network (GAN), i.e., BTD-sGAN (Text-based Deeply-supervised GAN), is proposed to generate training samples for remote sensing images of Anhui Province, China. The principal structure of our model is based on Deeply-supervised GAN(D-sGAN), and D-sGAN is improved from the point of the diversity of the generated samples. First, the network takes Perlin Noise, image segmentation graph, and encoded text vector as input, in which the size of image segmentation graph is adjusted to 128 × 128 to facilitate fusion with the text vector. Then, to improve the diversity of the generated images, the text vector is used to modify the semantic loss of the downsampled text. Finally, to balance the time and quality of image generation, only a two-layer Unet++ structure is used to generate the image. Herein, “Inception Score”, “Human Rank”, and “Inference Time” are used to evaluate the performance of BTD-sGAN, StackGAN++, and GAN-INT-CLS. At the same time, to verify the diversity of the remote sensing images generated by BTD-sGAN, this paper compares the results when the generated images are sent to the remote sensing interpretation network and when the generated images are not added; the results show that the generated image can improve the precision of soil-moving detection by 5\%, which proves the effectiveness of the proposed model.}, language = {en}, number = {10}, urldate = {2021-09-13}, journal = {Remote Sensing}, author = {Chen, Chen and Ma, Hongxiang and Yao, Guorun and Lv, Ning and Yang, Hua and Li, Cong and Wan, Shaohua}, month = jan, year = {2021}, note = {Number: 10 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {data augmentation, deeply monitoring, GAN, remote sensing image, text description}, pages = {1894}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\BWL9Y3J9\\1894.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\N5YKAV8U\\Chen et al. - 2021 - Remote Sensing Image Augmentation Based on Text De.pdf:application/pdf}, } @article{khanal_remote_2020, title = {Remote {Sensing} in {Agriculture}—{Accomplishments}, {Limitations}, and {Opportunities}}, volume = {12}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/12/22/3783}, doi = {10.3390/rs12223783}, abstract = {Remote sensing (RS) technologies provide a diagnostic tool that can serve as an early warning system, allowing the agricultural community to intervene early on to counter potential problems before they spread widely and negatively impact crop productivity. With the recent advancements in sensor technologies, data management and data analytics, currently, several RS options are available to the agricultural community. However, the agricultural sector is yet to implement RS technologies fully due to knowledge gaps on their sufficiency, appropriateness and techno-economic feasibilities. This study reviewed the literature between 2000 to 2019 that focused on the application of RS technologies in production agriculture, ranging from field preparation, planting, and in-season applications to harvesting, with the objective of contributing to the scientific understanding on the potential for RS technologies to support decision-making within different production stages. We found an increasing trend in the use of RS technologies in agricultural production over the past 20 years, with a sharp increase in applications of unmanned aerial systems (UASs) after 2015. The largest number of scientific papers related to UASs originated from Europe (34\%), followed by the United States (20\%) and China (11\%). Most of the prior RS studies have focused on soil moisture and in-season crop health monitoring, and less in areas such as soil compaction, subsurface drainage, and crop grain quality monitoring. In summary, the literature highlighted that RS technologies can be used to support site-specific management decisions at various stages of crop production, helping to optimize crop production while addressing environmental quality, profitability, and sustainability.}, language = {en}, number = {22}, urldate = {2021-09-13}, journal = {Remote Sensing}, author = {Khanal, Sami and Kc, Kushal and Fulton, John P. and Shearer, Scott and Ozkan, Erdal}, month = jan, year = {2020}, note = {Number: 22 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {remote sensing, precision agriculture, UAS, satellite}, pages = {3783}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ZGSH52UP\\3783.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\6VJ84YXA\\Khanal et al. - 2020 - Remote Sensing in Agriculture—Accomplishments, Lim.pdf:application/pdf}, } @article{haque_comparative_2020, title = {Comparative {Study} of {IoT}-{Based} {Topology} {Maintenance} {Protocol} in a {Wireless} {Sensor} {Network} for {Structural} {Health} {Monitoring}}, volume = {12}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/12/15/2358}, doi = {10.3390/rs12152358}, abstract = {A structural health monitoring (SHM) system is an approach for identifying the damages caused to various kinds of structures using different system functions and providing the necessary feedback about structure\’s conditions. As civil structures are the backbone of our society, to determine its daily operations is a very important issue. The performance measurement of those structures is manual whereas a computer-based monitoring system could automatically assess the structural damages and identify its exact location. Recently, wireless sensor networks (WSNs) have attracted a great deal of attention for remote sensing applications due to flexibility to measure of various activity of large scale network. Since technology is advancing day by day, the overall cost of a monitoring system is also decreased. However, the major challenging fact of a WSNs is to provide scalability for covering a large area. The main question is arisen how much capable have of a monitoring system to turn off unnecessary nodes to save energy while there are no events detected. To support the scalability required of an existing network and save the node energy for future use, we propose a topology maintenance protocol integrated with construction to address the issue of a node\’s energy consumption by placing it optimally and extending the monitoring system\’s lifetime. As per the authors\’ acknowledgement that, a little attention has been paid to developing such a hybrid approach. To mitigate node energy consumption issue with large scale support, an Internet of Things (IoT)-based maintenance approach is the best candidate for obtaining better system lifetime responses. Therefore, the main goal of this work is to develop an \‘on-the-fly\’-based topology maintenance monitoring system, which can maintain a network\’s infrastructure while gathering a node\’s information to switch its state regularly when the present network is no longer optimal.}, language = {en}, number = {15}, urldate = {2021-09-13}, journal = {Remote Sensing}, author = {Haque, Md Ershadul and Asikuzzaman, Md and Khan, Imran Ullah and Ra, In-Ho and Hossain, Md Sanwar and Shah, Syed Bilal Hussain}, month = jan, year = {2020}, note = {Number: 15 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {Internet of Things (IoT), on-the-fly network, structural health monitoring (SHM), topology maintenance protocol, wireless sensor networks (WSNs)}, pages = {2358}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\YN2H3DJE\\2358.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\WUGTIPBI\\Haque et al. - 2020 - Comparative Study of IoT-Based Topology Maintenanc.pdf:application/pdf}, } @article{kc_assessment_2021, title = {Assessment of the {Spatial} and {Temporal} {Patterns} of {Cover} {Crops} {Using} {Remote} {Sensing}}, volume = {13}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2072-4292/13/14/2689}, doi = {10.3390/rs13142689}, abstract = {Cover cropping is a conservation practice that helps to alleviate soil health problems and reduce nutrient losses. Understanding the spatial variability in historic and current adoption of cover cropping practices and their impacts on soil, water, and nutrient dynamics at a landscape scale is an important step in determining and prioritizing areas in a watershed to effectively utilize this practice. However, such data are lacking. Our objective was to develop a spatial and temporal inventory of winter cover cropping practices in the Maumee River watershed using images collected by Landsat satellites (Landsat 5, 7 and 8) from 2008 to 2019 in Google Earth Engine (GEE) platform. Each year, satellite images collected during cover crop growing season (i.e., between October and April) were converted into two seasonal composites based on cover crop phenology. Using these composites, various image-based covariates were extracted for 628 ground-truth (field) data. By integrating ground-truth and image-based covariates, a cover crop classification model based on a random forest (RF) algorithm was developed, trained and validated in GEE platform. Our classification scheme differentiated four cover crop categories: Winter Hardy, Winter Kill, Spring Emergent, and No Cover. The overall classification accuracy was 75\%, with a kappa coefficient of 0.63. The results showed that more than 50\% of the corn-soybean areas in the Maumee River watershed were without winter crops during 2008–2019 period. It was found that 2019/2020 and 2009/2010 were the years with the largest and lowest cover crop areas, with 34\% and 10\% in the watershed, respectively. The total cover cropping area was then assessed in relation to fall precipitation and cumulative growing degree days (GDD). There was no apparent increasing trend in cover crop areas between 2008 and 2019, but the variability in cover crops areas was found to be related to higher accumulated GDD and fall precipitation. A detailed understanding of the spatial and temporal distribution of cover crops using GEE could help in promoting site-specific management practices to enhance their environmental benefits. This also has significance to policy makers and funding agencies as they could use the information to localize areas in need of interventions for supporting adoption of cover cropping practice.}, language = {en}, number = {14}, urldate = {2021-09-13}, journal = {Remote Sensing}, author = {Kc, Kushal and Zhao, Kaiguang and Romanko, Matthew and Khanal, Sami}, month = jan, year = {2021}, note = {Number: 14 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {remote sensing, machine learning, random forest, classification, cover crop, Google Earth Engine, seasonal composites, western Lake Erie basin}, pages = {2689}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\QIMPSFYS\\2689.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\WZXJW7XR\\Kc et al. - 2021 - Assessment of the Spatial and Temporal Patterns of.pdf:application/pdf}, } @misc{noauthor_organic_nodate, title = {Organic {No}-{Till}}, url = {https://rodaleinstitute.org/why-organic/organic-farming-practices/organic-no-till/}, abstract = {No-till farming utilizes cover crops and roller crimpers instead of pesticides and tillers. Rodale Institute leads the way in organic no-till agriculture.}, language = {en-US}, urldate = {2021-09-20}, journal = {Rodale Institute}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\9HAGQWSF\\organic-no-till.html:text/html}, } @misc{noauthor_inspire_nodate, title = {{INSPIRE} tools {\textbar} {INSPIRE}}, url = {https://inspire.ec.europa.eu/inspire-tools}, urldate = {2021-09-16}, } @article{gartner_bonares_2017, title = {The {BonaRes} {Metadata} {Schema}}, copyright = {Creative Commons Attribution 4.0 International}, url = {https://tools.bonares.de/doi/doc/16/}, doi = {10.20387/BONARES-5PGG-8YRP}, abstract = {The BonaRes metadata schema provides a description for each metadata element available in the schema. Each element contains information such as its unique ID, a clear definition, an obligation and multiplicity statement as well as the data type and its data domain. The metadata schema combines international recognized standards for the description of geospatial data (INSPIRE Directive) and research data (DataCite 4.0). The compliance with DataCite 4.0 permits the assignment of a Digital Object Identifier to the research data. The Digital Object Identifier assures reliable and unambiguous access; supports re-use of the data and allows proper attribution and credit.}, language = {en}, urldate = {2021-09-28}, author = {Gärtner, Philipp and Svoboda, Nikolai and Kühnert, Thomas and Zoarder, Muqit M. A. and Heinrich, Uwe}, collaborator = {Gärtner, Philipp and Heinrich, Uwe}, month = nov, year = {2017}, note = {Artwork Size: 505kb Medium: pdf Publisher: BonaRes Centre}, keywords = {BonaRes, DataCite, INSPIRE, Metadata, Open Data}, pages = {505kb}, file = {Gärtner et al. - 2017 - The BonaRes Metadata Schema.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\WMM3CSBY\\Gärtner et al. - 2017 - The BonaRes Metadata Schema.pdf:application/pdf;BonaRes Series Template_2021-08-16.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\YSU8N92V\\BonaRes Series Template_2021-08-16.pdf:application/pdf}, } @article{ittner_sophie_impact_2020, title = {The impact of subsoil management on the delivery of ecosystem services}, copyright = {Creative Commons Attribution 2.0 Generic}, url = {https://tools.bonares.de/doi/doc/30/}, doi = {10.20387/BONARES-BSZH-QBKN}, abstract = {In recent years, the interest in subsoil has increased, since it can hold immense reservoirs of nutrients, organic matter and water. The subsoil can therefore provide important ecosystem services for the agricultural production system and beyond. This paper assesses the sustainability of two subsoil management measures with regard to the delivery of soil-related ecosystem services: a) the cultivation of deep-rooted pre-crops (biological approach) and b) stripwise mechanical subsoil loosening in combination with the incorporation of compost (Soil³ method). The analysis includes the identification of soil-related ecosystem services to which the subsoil contributes, the identification of related indicators, and the analysis of changes in the delivery of ecosystem services. The results show that both subsoil management measures lead to a change in the provision of soil-related ecosystem services. With the exception of the effect on potential N-leaching, both measures have an overall positive effect on considered ecosystem services.}, language = {en}, urldate = {2021-09-28}, author = {Ittner, Sophie and Gerdes, Holger and Athmann, Miriam and Bauke, Sara Luise and Gocke, Martina and Guigue, Julien and Jaiswal, Sanjay and Kautz, Timo and Schmittmann, Oliver and Schulz, Stefanie and Seidel, Sabine}, year = {2020}, note = {Medium: application/pdf Publisher: BonaRes Data Centre}, keywords = {Europe, ecosystem services, subsoil management}, } @article{hoffmann_data_2019, title = {Data {Standards} for {Soil}- and {Agricultural} {Research}}, url = {https://tools.bonares.de/doi/doc/25/}, doi = {10.20387/BONARES-ARM4-66M2}, abstract = {Goal of modern research data management is to provide user-friendly infrastructures to upload, manage and provide research data in findable, accessible, interoperable and reusable formats for continued use (= ”FAIR data principles”). To meet these requirements, the application of accepted and widely used standards, regulations, conventions and guidelines for the different stages of research data life is necessary. With regard to agricultural science, such standards concern a wide field, e.g. the classification and description of soils, field and laboratory methods, agricultural technology, plant varieties, fertilizer products and application, agricultural business data, and agrisemantics. Additionally, more general standards are necessary, e.g. for metadata schemes, data transformation tools, data quality, data storage and archiving, data exchange, and for spatial data provision within an online geoportal. This document presents and discusses a variety of data standards for all life stages from data acquisition to provision. It is a reference work for owners, providers and users of soil- and agricultural research data and aims to facilitate data integration and knowledge spread via data repositories.}, urldate = {2021-09-28}, author = {Hoffmann, Carsten and Schulz, Sina and Eberhardt, Einar and Grosse, Meike and Stein, Susanne and Specka, Xenia and Svoboda, Nikolai and Heinrich, Uwe}, month = dec, year = {2019}, note = {Publisher: BonaRes Data Centre (Leibniz Centre for Agricultural Landscape Research (ZALF))}, keywords = {data standards, Europe, BonaRes, agricultural science, data provision, data repository, FAIR principles, geodata, research data management, soil science, standards}, file = {Hoffmann et al. - Data Standards for Soil- and Agricultural Research.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\I6NPVY2U\\Hoffmann et al. - Data Standards for Soil- and Agricultural Research.pdf:application/pdf}, } @article{svoboda_bonares_2017, title = {The {BonaRes} {Data} {Guideline}}, copyright = {Creative Commons Attribution 4.0 International}, url = {https://tools.bonares.de/doi/doc/4/}, doi = {10.20387/BONARES-E1AZ-ETD7}, abstract = {This data guideline provides rules for the handling, digital storage and free re-use of research data generated in the BonaRes program, while respecting the Intellectual Property Right of the owner of the research data and respecting his or her right to the first scientific use, in accordance with the requirements arising from the BonaRes program allocation of funds. The Data Guideline aims at a) a timely submission of quality approved soil research data to the BonaRes Data Centre and its central storage b) facilitate the exchange of data among BonaRes scientists c) the provision of data to the scientific community.}, language = {en}, urldate = {2021-09-28}, author = {Svoboda, Nikolai and Heinrich, Uwe}, collaborator = {Svoboda, Nikolai and Heinrich, Uwe}, month = jul, year = {2017}, note = {Publisher: BonaRes Data Centre}, keywords = {BonaRes, DOI, embargo, Intellectual Property Right, license, policy, provision of research data, re-use}, file = {Svoboda and Heinrich - 2017 - The BonaRes Data Guideline.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\BEYXTQ87\\Svoboda and Heinrich - 2017 - The BonaRes Data Guideline.pdf:application/pdf}, } @misc{noauthor_dynamics_nodate, title = {dynamics}, url = {https://www.bonares.de/soil-functions/dynamics}, urldate = {2021-09-28}, keywords = {Europe, BonaRes, soil functions}, file = {dynamics:C\:\\Users\\Edify 01\\Zotero\\storage\\CKANIZ5K\\dynamics.html:text/html}, } @article{vogel_systemic_2018, title = {A systemic approach for modeling soil functions}, volume = {4}, issn = {2199-398X}, url = {https://soil.copernicus.org/articles/4/83/2018/}, doi = {10.5194/soil-4-83-2018}, abstract = {Abstract. The central importance of soil for the functioning of terrestrial systems is increasingly recognized. Critically relevant for water quality, climate control, nutrient cycling and biodiversity, soil provides more functions than just the basis for agricultural production. Nowadays, soil is increasingly under pressure as a limited resource for the production of food, energy and raw materials. This has led to an increasing demand for concepts assessing soil functions so that they can be adequately considered in decision-making aimed at sustainable soil management. The various soil science disciplines have progressively developed highly sophisticated methods to explore the multitude of physical, chemical and biological processes in soil. It is not obvious, however, how the steadily improving insight into soil processes may contribute to the evaluation of soil functions. Here, we present to a new systemic modeling framework that allows for a consistent coupling between reductionist yet observable indicators for soil functions with detailed process understanding. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. The non-linear character of these interactions produces stability and resilience of soil with respect to functional characteristics. We anticipate that this new conceptional framework will integrate the various soil science disciplines and help identify important future research questions at the interface between disciplines. It allows the overwhelming complexity of soil systems to be adequately coped with and paves the way for steadily improving our capability to assess soil functions based on scientific understanding.}, language = {en}, number = {1}, urldate = {2021-09-28}, journal = {SOIL}, author = {Vogel, Hans-Jörg and Bartke, Stephan and Daedlow, Katrin and Helming, Katharina and Kögel-Knabner, Ingrid and Lang, Birgit and Rabot, Eva and Russell, David and Stößel, Bastian and Weller, Ulrich and Wiesmeier, Martin and Wollschläger, Ute}, month = mar, year = {2018}, keywords = {Europe, BonaRes, soil functions, systemic modelling}, pages = {83--92}, file = {Full Text:C\:\\Users\\Edify 01\\Zotero\\storage\\IKD8J3PZ\\Vogel et al. - 2018 - A systemic approach for modeling soil functions.pdf:application/pdf}, } @misc{noauthor_inspire_2013, title = {{INSPIRE} {Data} {Specification} on {Soil} – {Technical} {Guidelines} {\textbar} {INSPIRE}}, url = {https://inspire.ec.europa.eu/id/document/tg/so}, urldate = {2021-10-01}, month = dec, year = {2013}, file = {INSPIRE Data Specification on Soil – Technical Guidelines | INSPIRE:C\:\\Users\\Edify 01\\Zotero\\storage\\9TY59NPJ\\so.html:text/html;INSPIRE Data Specification on Soil – Technical Gui.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\IHZHBBC4\\INSPIRE Data Specification on Soil – Technical Gui.pdf:application/pdf}, } @article{specka_bonares_2019, title = {The {BonaRes} metadata schema for geospatial soil-agricultural research data – {Merging} {INSPIRE} and {DataCite} metadata schemes}, volume = {132}, issn = {0098-3004}, url = {https://www.sciencedirect.com/science/article/pii/S009830041930086X}, doi = {10.1016/j.cageo.2019.07.005}, abstract = {A spatial data infrastructure (SDI) for the upload and provision of soil-agricultural research data in Germany was developed and launched in 2017. The precondition for the new SDI were to be compliant with the European initiative for spatial information (INSPIRE), to consider FAIR data principles, to be interoperable with other disciplinary national and international SDIs and to support dataset registrations with digital object identifiers (DOI). To meet these requirements, the new SDI had to support both the INSPIRE and DataCite metadata standards. As there was no metadata standard available that supported both metadata schemas from different disciplines, it became necessary to merge these two existing standards. The objective of this paper is to describe the developmental steps of the newly created BonaRes metadata schema for geospatial soil-agricultural research data. First, we analyzed the INSPIRE and DataCite metadata schemas, identified and compared semantically equivalent metadata elements, including properties and allowed content values, for potential mapping. In the next step, we specified the new metadata model, whose elements were derived from INSPIRE or DataCite under consideration of the previously developed mapping. Third, additional metadata elements were defined to directly describe the underlying data model. The advantages and disadvantages of the method that was applied to define the BonaRes metadata schema elements originating from INSPIRE and DataCite schemas are presented and discussed. By implementing the new metadata model, the SDIs can achieve cross-portal metadata interoperability with other INSPIRE-compliant SDIs. Furthermore, researchers who store their geospatial research data in SDIs to implement the BonaRes metadata schema can increase the visibility and findability of their research, as the data can be assigned a DOI, which is a prerequisite for data citations and data publications. The new metadata elements of the BonaRes metadata schema allows targeted dataset queries, e.g., soil pH values, yields or parameters, which were measured by a specific method, using the underlying data model, and improves the discovery and reusability of research data.}, language = {en}, urldate = {2021-10-01}, journal = {Computers \& Geosciences}, author = {Specka, Xenia and Gärtner, Philipp and Hoffmann, Carsten and Svoboda, Nikolai and Stecker, Markus and Einspanier, Udo and Senkler, Kristian and Zoarder, M. A. Muqit and Heinrich, Uwe}, month = nov, year = {2019}, keywords = {INSPIRE, BonaRes Repository, Crosswalk, DataCite 4.0, FAIR data principles, Metadata mapping, Metadata schema}, pages = {33--41}, file = {Specka et al. - 2019 - The BonaRes metadata schema for geospatial soil-ag.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\PLEJ2P2J\\Specka et al. - 2019 - The BonaRes metadata schema for geospatial soil-ag.pdf:application/pdf}, } @article{elstone_high_2020, title = {High {Speed} {Crop} and {Weed} {Identification} in {Lettuce} {Fields} for {Precision} {Weeding}}, volume = {20}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/20/2/455}, doi = {10.3390/s20020455}, abstract = {Precision weeding can significantly reduce or even eliminate the use of herbicides in farming. To achieve high-precision, individual targeting of weeds, high-speed, low-cost plant identification is essential. Our system using the red, green, and near-infrared reflectance, combined with a size differentiation method, is used to identify crops and weeds in lettuce fields. Illumination is provided by LED arrays at 525, 650, and 850 nm, and images are captured in a single-shot using a modified RGB camera. A kinematic stereo method is utilised to compensate for parallax error in images and provide accurate location data of plants. The system was verified in field trials across three lettuce fields at varying growth stages from 0.5 to 10 km/h. In-field results showed weed and crop identification rates of 56\% and 69\%, respectively. Post-trial processing resulted in average weed and crop identifications of 81\% and 88\%, respectively.}, language = {en}, number = {2}, urldate = {2021-10-07}, journal = {Sensors}, author = {Elstone, Lydia and How, Kin Yau and Brodie, Samuel and Ghazali, Muhammad Zulfahmi and Heath, William P. and Grieve, Bruce}, month = jan, year = {2020}, note = {Number: 2 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {kinetic stereo imaging, multispectral imaging, plant detection, precision weeding}, pages = {455}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\PCR88IIH\\455.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\3IY2J5WU\\Elstone et al. - 2020 - High Speed Crop and Weed Identification in Lettuce.pdf:application/pdf}, } @article{nasirahmadi_deep_2019, title = {Deep {Learning} and {Machine} {Vision} {Approaches} for {Posture} {Detection} of {Individual} {Pigs}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/17/3738}, doi = {10.3390/s19173738}, abstract = {Posture detection targeted towards providing assessments for the monitoring of health and welfare of pigs has been of great interest to researchers from different disciplines. Existing studies applying machine vision techniques are mostly based on methods using three-dimensional imaging systems, or two-dimensional systems with the limitation of monitoring under controlled conditions. Thus, the main goal of this study was to determine whether a two-dimensional imaging system, along with deep learning approaches, could be utilized to detect the standing and lying (belly and side) postures of pigs under commercial farm conditions. Three deep learning-based detector methods, including faster regions with convolutional neural network features (Faster R-CNN), single shot multibox detector (SSD) and region-based fully convolutional network (R-FCN), combined with Inception V2, Residual Network (ResNet) and Inception ResNet V2 feature extractions of RGB images were proposed. Data from different commercial farms were used for training and validation of the proposed models. The experimental results demonstrated that the R-FCN ResNet101 method was able to detect lying and standing postures with higher average precision (AP) of 0.93, 0.95 and 0.92 for standing, lying on side and lying on belly postures, respectively and mean average precision (mAP) of more than 0.93.}, language = {en}, number = {17}, urldate = {2021-10-07}, journal = {Sensors}, author = {Nasirahmadi, Abozar and Sturm, Barbara and Edwards, Sandra and Jeppsson, Knut-Håkan and Olsson, Anne-Charlotte and Müller, Simone and Hensel, Oliver}, month = jan, year = {2019}, note = {Number: 17 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {convolutional neural networks, livestock, lying posture, standing posture}, pages = {3738}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\EJM8VLE8\\3738.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\9FS54ZPH\\Nasirahmadi et al. - 2019 - Deep Learning and Machine Vision Approaches for Po.pdf:application/pdf}, } @article{owino_automated_2019, title = {Automated {Measurement} and {Control} of {Germination} {Paper} {Water} {Content}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/10/2232}, doi = {10.3390/s19102232}, abstract = {Germination paper (GP) is used as a growth substrate in plant development studies. Current studies bear two limitations: (1) The actual GP water content and variations in GP water content are neglected. (2) Existing irrigation methods either maintain the GP water content at fully sufficient or at a constant deficit. Variation of the intensity of water deficit over time for plants grown on GP is not directly achievable using these methods. In this contribution, a new measurement and control approach was presented. As a first step, a more precise measurement of water content was realized by employing the discharging process of capacitors to determine the electrical resistance of GP, which is related to the water content. A Kalman filter using an evapotranspiration model in combination with experimental data was used to refine the measurements, serving as the input for a model predictive controller (MPC). The MPC was used to improve the dynamics of the irrigation amount to more precisely achieve the required water content for regulated water uptake in plant studies. This is important in studies involving deficit irrigation. The novel method described was capable of increasing the accuracy of GP water content control. As a first step, the measurement system achieved an improved accuracy of 0.22 g/g. The application of a MPC for water content control based on the improved measurement results in an overall control accuracy was 0.09 g/g. This method offers a new approach, allowing the use of GP for studies with varying water content. This addressed the limitations of existing plant growth studies and allowed the prospection of dependencies between dynamic water deficit and plant development using GP as a growth substrate for research studies.}, language = {en}, number = {10}, urldate = {2021-10-07}, journal = {Sensors}, author = {Owino, Lina and Hilkens, Marvin and Kögler, Friederike and Söffker, Dirk}, month = jan, year = {2019}, note = {Number: 10 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {germination paper, Kalman filter, model predictive control, moisture measurement}, pages = {2232}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JU26C7XQ\\2232.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\PELQWGN6\\Owino et al. - 2019 - Automated Measurement and Control of Germination P.pdf:application/pdf}, } @article{khongnawang_three-dimensional_2019, title = {Three-{Dimensional} {Mapping} of {Clay} and {Cation} {Exchange} {Capacity} of {Sandy} and {Infertile} {Soil} {Using} {EM38} and {Inversion} {Software}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/18/3936}, doi = {10.3390/s19183936}, abstract = {Most cultivated upland areas of northeast Thailand are characterized by sandy and infertile soils, which are difficult to improve agriculturally. Information about the clay (\%) and cation exchange capacity (CEC\—cmol(+)/kg) are required. Because it is expensive to analyse these soil properties, electromagnetic (EM) induction instruments are increasingly being used. This is because the measured apparent soil electrical conductivity (ECa\—mS/m), can often be correlated directly with measured topsoil (0\–0.3 m), subsurface (0.3\–0.6 m) and subsoil (0.6\–0.9 m) clay and CEC. In this study, we explore the potential to use this approach and considering a linear regression (LR) between EM38 acquired ECa in horizontal (ECah) and vertical (ECav) modes of operation and the soil properties at each of these depths. We compare this approach with a universal LR relationship developed between calculated true electrical conductivity (\σ\—mS/m) and laboratory measured clay and CEC at various depths. We estimate \σ by inverting ECah and ECav data, using a quasi-3D inversion algorithm (EM4Soil). The best LR between ECa and soil properties was between ECah and subsoil clay (R2 = 0.43) and subsoil CEC (R2 = 0.56). We concluded these LR were unsatisfactory to predict clay or CEC at any of the three depths, however. In comparison, we found that a universal LR could be established between \σ with clay (R2 = 0.65) and CEC (R2 = 0.68). The LR model validation was tested using a leave-one-out-cross-validation. The results indicated that the universal LR between \σ and clay at any depth was precise (RMSE = 2.17), unbiased (ME = 0.27) with good concordance (Lin\’s = 0.78). Similarly, satisfactory results were obtained by the LR between \σ and CEC (Lin\’s = 0.80). We conclude that in a field where a direct LR relationship between clay or CEC and ECa cannot be established, can still potentially be mapped by developing a LR between estimates of \σ with clay or CEC if they all vary with depth.}, language = {en}, number = {18}, urldate = {2021-10-07}, journal = {Sensors}, author = {Khongnawang, Tibet and Zare, Ehsan and Zhao, Dongxue and Srihabun, Pranee and Triantafilis, John}, month = jan, year = {2019}, note = {Number: 18 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {cation exchange capacity, clay content, quasi-3D inversion algorithm, sandy infertile soil, Three-dimensional mapping}, pages = {3936}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\WRKQU78D\\3936.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\XSBJ8GSD\\Khongnawang et al. - 2019 - Three-Dimensional Mapping of Clay and Cation Excha.pdf:application/pdf}, } @article{taleb_bendiab_coupling_2019, title = {Coupling {Waveguide}-{Based} {Micro}-{Sensors} and {Spectral} {Multivariate} {Analysis} to {Improve} {Spray} {Deposit} {Characterization} in {Agriculture}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/19/4168}, doi = {10.3390/s19194168}, abstract = {The leaf coverage surface is a key measurement of the spraying process to maximize spray efficiency. To determine leaf coverage surface, the development of optical micro-sensors that, coupled with a multivariate spectral analysis, will be able to measure the volume of the droplets deposited on their surface is proposed. Rib optical waveguides based on Ge-Se-Te chalcogenide films were manufactured and their light transmission was studied as a response to the deposition of demineralized water droplets on their surface. The measurements were performed using a dedicated spectrophotometric bench to record the transmission spectra at the output of the waveguides, before (reference) and after drop deposition, in the wavelength range between 1200 and 2000 nm. The presence of a hollow at 1450 nm in the relative transmission spectra has been recorded. This corresponds to the first overtone of the O\–H stretching vibration in water. This result tends to show that the optical intensity decrease observed after droplet deposition is partly due to absorption by water of the light energy carried by the guided mode evanescent field. The probe based on Ge-Se-Te rib optical waveguides is thus sensitive throughout the whole range of volumes studied, i.e., from 0.1 to 2.5 \μL. Principal Component Analysis and Partial Least Square as multivariate techniques then allowed the analysis of the statistics of the measurements and the predictive character of the transmission spectra. It confirmed the sensitivity of the measurement system to the water absorption, and the predictive model allowed the prediction of droplet volumes on an independent set of measurements, with a correlation of 66.5\% and a precision of 0.39 \μL.}, language = {en}, number = {19}, urldate = {2021-10-07}, journal = {Sensors}, author = {Taleb Bendiab, Anis and Ryckewaert, Maxime and Heran, Daphné and Escalier, Raphaël and Kribich, Raphaël K. and Vigreux, Caroline and Bendoula, Ryad}, month = jan, year = {2019}, note = {Number: 19 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {precision agriculture, crop protection, droplet characterization, infrared spectroscopy, optical micro-sensors, partial least squares (PLS), principal component analysis (PCA)}, pages = {4168}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\NLJSYCFJ\\4168.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\WKS95QIB\\Taleb Bendiab et al. - 2019 - Coupling Waveguide-Based Micro-Sensors and Spectra.pdf:application/pdf}, } @article{vogel_evaluating_2019, title = {Evaluating {Soil}-{Borne} {Causes} of {Biomass} {Variability} in {Grassland} by {Remote} and {Proximal} {Sensing}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/20/4593}, doi = {10.3390/s19204593}, abstract = {On a grassland field with sandy soils in Northeast Germany (Brandenburg), vegetation indices from multi-spectral UAV-based remote sensing were used to predict grassland biomass productivity. These data were combined with soil pH value and apparent electrical conductivity (ECa) from on-the-go proximal sensing serving as indicators for soil-borne causes of grassland biomass variation. The field internal magnitude of spatial variability and hidden correlations between the variables of investigation were analyzed by means of geostatistics and boundary-line analysis to elucidate the influence of soil pH and ECa on the spatial distribution of biomass. Biomass and pH showed high spatial variability, which necessitates high resolution data acquisition of soil and plant properties. Moreover, boundary-line analysis showed grassland biomass maxima at pH values between 5.3 and 7.2 and ECa values between 3.5 and 17.5 mS m\−1. After calibrating ECa to soil moisture, the ECa optimum was translated to a range of optimum soil moisture from 7\% to 13\%. This matches well with to the plant-available water content of the predominantly sandy soil as derived from its water retention curve. These results can be used in site-specific management decisions to improve grassland biomass productivity in low-yield regions of the field due to soil acidity or texture-related water scarcity.}, language = {en}, number = {20}, urldate = {2021-10-07}, journal = {Sensors}, author = {Vogel, Sebastian and Gebbers, Robin and Oertel, Marcel and Kramer, Eckart}, month = jan, year = {2019}, note = {Number: 20 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {UAV, apparent electrical conductivity (ECa), boundary-line, law of minimum, pH, quantile regression}, pages = {4593}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\FNG6MTC3\\4593.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\IPTRYC2P\\Vogel et al. - 2019 - Evaluating Soil-Borne Causes of Biomass Variabilit.pdf:application/pdf}, } @article{li_ise-based_2019, title = {An {ISE}-based {On}-{Site} {Soil} {Nitrate} {Nitrogen} {Detection} {System}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/21/4669}, doi = {10.3390/s19214669}, abstract = {Soil nitrate\–nitrogen (NO3\−-N) is one of the primary factors used to control nitrogen topdressing application during the crop growth period. The ion-selective electrode (ISE) is a promising method for rapid lower-cost in-field detection. Due to the simplification of sample preparation, the accuracy and stability of ISE-based in-field detection is doubted. In this paper, a self-designed prototype system for on-site soil NO3\−-N detection was developed. The procedure of spinning centrifugation was used to avoid interference from soil slurry suspension. A modified Nernstian prediction model was quantitatively characterized with outputs from both the ISE and the soil moisture sensor. The measurement accuracy of the sensor fusion model was comparable with the laboratory ISE detections with standard sample pretreatment. Compared with the standard spectrometric method, the average absolute error (AE) and root-mean-square error (RMSE) were found to be less than 4.7 and 6.1 mg/L, respectively. The on-site soil testing efficiency was 4\–5 min/sample, which reduced the operation time by 60\% compared with manual sample preparation. The on-site soil NO3\−-N status was dynamically monitored for 42 consecutive days. The declining peak of NO3\−-N was observed. In all, the designed ISE-based detection system demonstrated a promising capability for the dynamic on-site monitoring of soil macronutrients.}, language = {en}, number = {21}, urldate = {2021-10-07}, journal = {Sensors}, author = {Li, Yanhua and Yang, Qingliang and Chen, Ming and Wang, Maohua and Zhang, Miao}, month = jan, year = {2019}, note = {Number: 21 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {sensor fusion, soil moisture, ion-selective electrode (ISE), on-site detection, soil nitrate nitrogen (NO$_{\textrm{3}}$$^{\textrm{−}}$-N)}, pages = {4669}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\Z2A36YV9\\4669.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HV9TRI2U\\Li et al. - 2019 - An ISE-based On-Site Soil Nitrate Nitrogen Detecti.pdf:application/pdf}, } @article{huang_body_2019, title = {Body {Dimension} {Measurements} of {Qinchuan} {Cattle} with {Transfer} {Learning} from {LiDAR} {Sensing}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/22/5046}, doi = {10.3390/s19225046}, abstract = {For the time-consuming and stressful body measuring task of Qinchuan cattle and farmers, the demand for the automatic measurement of body dimensions has become more and more urgent. It is necessary to explore automatic measurements with deep learning to improve breeding efficiency and promote the development of industry. In this paper, a novel approach to measuring the body dimensions of live Qinchuan cattle with on transfer learning is proposed. Deep learning of the Kd-network was trained with classical three-dimensional (3D) point cloud datasets (PCD) of the ShapeNet datasets. After a series of processes of PCD sensed by the light detection and ranging (LiDAR) sensor, the cattle silhouettes could be extracted, which after augmentation could be applied as an input layer to the Kd-network. With the output of a convolutional layer of the trained deep model, the output layer of the deep model could be applied to pre-train the full connection network. The TrAdaBoost algorithm was employed to transfer the pre-trained convolutional layer and full connection of the deep model. To classify and recognize the PCD of the cattle silhouette, the average accuracy rate after training with transfer learning could reach up to 93.6\%. On the basis of silhouette extraction, the candidate region of the feature surface shape could be extracted with mean curvature and Gaussian curvature. After the computation of the FPFH (fast point feature histogram) of the surface shape, the center of the feature surface could be recognized and the body dimensions of the cattle could finally be calculated. The experimental results showed that the comprehensive error of body dimensions was close to 2\%, which could provide a feasible approach to the non-contact observations of the bodies of large physique livestock without any human intervention.}, language = {en}, number = {22}, urldate = {2021-10-07}, journal = {Sensors}, author = {Huang, Lvwen and Guo, Han and Rao, Qinqin and Hou, Zixia and Li, Shuqin and Qiu, Shicheng and Fan, Xinyun and Wang, Hongyan}, month = jan, year = {2019}, note = {Number: 22 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {deep learning, transfer learning, body dimensions, feature recognition, FFPH, Kd-network, non-contact measurement, point cloud}, pages = {5046}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\5QJNEAHF\\5046.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\WM8IBS6X\\Huang et al. - 2019 - Body Dimension Measurements of Qinchuan Cattle wit.pdf:application/pdf}, } @article{riebe_comparison_2019, title = {Comparison of {Calibration} {Approaches} in {Laser}-{Induced} {Breakdown} {Spectroscopy} for {Proximal} {Soil} {Sensing} in {Precision} {Agriculture}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/23/5244}, doi = {10.3390/s19235244}, abstract = {The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method.}, language = {en}, number = {23}, urldate = {2021-10-07}, journal = {Sensors}, author = {Riebe, Daniel and Erler, Alexander and Brinkmann, Pia and Beitz, Toralf and Löhmannsröben, Hans-Gerd and Gebbers, Robin}, month = jan, year = {2019}, note = {Number: 23 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {proximal soil sensing, elemental composition, laser-induced breakdown spectroscopy, LIBS, soil nutrients}, pages = {5244}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ZIL676NP\\5244.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\XGF9UPPZ\\Riebe et al. - 2019 - Comparison of Calibration Approaches in Laser-Indu.pdf:application/pdf}, } @article{unal_real-time_2020, title = {Real-{Time} {Electrical} {Resistivity} {Measurement} and {Mapping} {Platform} of the {Soils} with an {Autonomous} {Robot} for {Precision} {Farming} {Applications}}, volume = {20}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/20/1/251}, doi = {10.3390/s20010251}, abstract = {Soil electrical resistivity (ER) is an important indicator to indirectly determine soil physical and chemical properties such as moisture, salinity, porosity, organic matter level, bulk density, and soil texture. In this study, real-time ER measurement system has been developed with the help of an autonomous robot. The aim of this study is to provide rapid measurement of the ER in large areas using the Wenner four-probe measurement method for precision farming applications. The ER measurement platform consists of the Wenner probes, a y-axis shifter driven by a DC motor through a gear reducer, all installed on a steel-frame that mount to an autonomous robot. An embedded industrial computer and differential global positioning system (DGPS) were used to assist in real-time measuring, recording, mapping, and displaying the ER and the robot position during the field operation. The data acquisition software was codded in Microsoft Visual Basic.NET. Field experiments were carried out in a 1.2 ha farmland soil. ER and DGPS values were stored in Microsoft SQL Server 2005 database, an ordinary Kriging interpolation technique by ArcGIS was used and the average ER values were mapped for the soil depth between 0 and 50 cm. As a result, ER values were observed to be between 30.757 and 70.732 ohm-m. In conclusion, the experimental results showed that the designed system works quite well in the field and the ER measurement platform is a practical tool for providing real-time soil ER measurements.}, language = {en}, number = {1}, urldate = {2021-10-07}, journal = {Sensors}, author = {Ünal, İlker and Kabaş, Önder and Sözer, Salih}, month = jan, year = {2020}, note = {Number: 1 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {soil, autonomous robot, mapping, precision farming, real-time measurement, soil electrical resistivity}, pages = {251}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\9Q3M85SQ\\251.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\D73L3T77\\Ünal et al. - 2020 - Real-Time Electrical Resistivity Measurement and M.pdf:application/pdf}, } @article{leclerc_development_2020, title = {Development of {Willow} {Tree} {Yield}-{Mapping} {Technology}}, volume = {20}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/20/9/2650}, doi = {10.3390/s20092650}, abstract = {With today\’s environmental challenges, developing sustainable energy sources is crucial. From this perspective, woody biomass has been, and continues to be, a significant research interest. The goal of this research was to develop new technology for mapping willow tree yield grown in a short-rotation forestry (SRF) system. The system gathered the physical characteristics of willow trees on-the-go, while the trees were being harvested. Features assessed include the number of trees harvested and their diameter. To complete this task, a machine-vision system featuring an RGB-D stereovision camera was built. The system tagged these data with the corresponding geographical coordinates using a Global Navigation Satellite System (GNSS) receiver. The proposed yield-mapping system showed promising detection results considering the complex background and variable light conditions encountered in the outdoors. Of the 40 randomly selected and manually observed trees in a row, 36 were successfully detected, yielding a 90\% detection rate. The correctly detected tree rate of all trees within the scenes was actually 71.8\% since the system tended to be sensitive to branches, thus, falsely detecting them as trees. Manual validation of the diameter estimation function showed a poor coefficient of determination and a root mean square error (RMSE) of 10.7 mm.}, language = {en}, number = {9}, urldate = {2021-10-07}, journal = {Sensors}, author = {Leclerc, Maxime and Adamchuk, Viacheslav and Park, Jaesung and Lachapelle-T., Xavier}, month = jan, year = {2020}, note = {Number: 9 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {precision agriculture, machine vision, willow tree, yield estimation}, pages = {2650}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ZIF6NCEC\\2650.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\5ZE64IQQ\\Leclerc et al. - 2020 - Development of Willow Tree Yield-Mapping Technolog.pdf:application/pdf}, } @article{tavares_simplifying_2019, title = {Simplifying {Sample} {Preparation} for {Soil} {Fertility} {Analysis} by {X}-ray {Fluorescence} {Spectrometry}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/23/5066}, doi = {10.3390/s19235066}, abstract = {Portable X-ray fluorescence (pXRF) sensors allow one to collect digital data in a practical and environmentally friendly way, as a complementary method to traditional laboratory analyses. This work aimed to assess the performance of a pXRF sensor to predict exchangeable nutrients in soil samples by using two contrasting strategies of sample preparation: pressed pellets and loose powder (\<2 mm). Pellets were prepared using soil and a cellulose binder at 10\% w w\−1 followed by grinding for 20 min. Sample homogeneity was probed by X-ray fluorescence microanalysis. Exchangeable nutrients were assessed by pXRF furnished with a Rh X-ray tube and silicon drift detector. The calibration models were obtained using 58 soil samples and leave-one-out cross-validation. The predictive capabilities of the models were appropriate for both exchangeable K (ex-K) and Ca (ex-Ca) determinations with R2 \≥ 0.76 and RPIQ \> 2.5. Although XRF analysis of pressed pellets allowed a slight gain in performance over loose powder samples for the prediction of ex-K and ex-Ca, satisfactory performances were also obtained with loose powders, which require minimal sample preparation. The prediction models with local samples showed promising results and encourage more detailed investigations for the application of pXRF in tropical soils.}, language = {en}, number = {23}, urldate = {2021-10-07}, journal = {Sensors}, author = {Tavares, Tiago Rodrigues and Nunes, Lidiane Cristina and Alves, Elton Eduardo Novais and Almeida, Eduardo de and Maldaner, Leonardo Felipe and Krug, Francisco José and Carvalho, Hudson Wallace Pereira de and Molin, José Paulo}, month = jan, year = {2019}, note = {Number: 23 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {precision agriculture, proximal soil sensing, spectroscopy, soil nutrients, soil testing, X-ray fluorescence}, pages = {5066}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\WS6ITZ8L\\5066.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HSTEPKXM\\Tavares et al. - 2019 - Simplifying Sample Preparation for Soil Fertility .pdf:application/pdf}, } @article{xiong_automatic_2019, title = {An {Automatic} {Head} {Surface} {Temperature} {Extraction} {Method} for {Top}-{View} {Thermal} {Image} with {Individual} {Broiler}}, volume = {19}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/19/23/5286}, doi = {10.3390/s19235286}, abstract = {Surface temperature variation in a broiler\’s head can be used as an indicator of its health status. Surface temperatures in the existing thermograph based animal health assessment studies were mostly obtained manually. 2185 thermal images, each of which had an individual broiler, were captured from 20 broilers. Where 15 broilers served as the experimental group, they were injected with 0.1mL of pasteurella inoculum. The rest, 5 broilers, served as the control group. An algorithm was developed to extract head surface temperature automatically from the top-view broiler thermal image. Adaptive K-means clustering and ellipse fitting were applied to locate the broiler\’s head region. The maximum temperature inside the head region was extracted as the head surface temperature. The developed algorithm was tested in Matlab\® (R2016a) and the testing results indicated that the head region in 92.77\% of the broiler thermal images could be located correctly. The maximum error of the extracted head surface temperatures was not greater than 0.1 \°C. Different trend features were observed in the smoothed head surface temperature time series of the broilers in experimental and control groups. Head surface temperature extracted by the presented algorithm lays a foundation for the development of an automatic system for febrile broiler identification.}, language = {en}, number = {23}, urldate = {2021-10-07}, journal = {Sensors}, author = {Xiong, Xingguo and Lu, Mingzhou and Yang, Weizhong and Duan, Guanghui and Yuan, Qingyan and Shen, Mingxia and Norton, Tomas and Berckmans, Daniel}, month = jan, year = {2019}, note = {Number: 23 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {adaptive K-means, broiler surface temperature extraction, ellipse fitting, head region locating, thermal image processing}, pages = {5286}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\YZ8U42PL\\5286.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\4YBYKW7Q\\Xiong et al. - 2019 - An Automatic Head Surface Temperature Extraction M.pdf:application/pdf}, } @article{zhang_autonomous_2020, title = {An {Autonomous} {Fruit} and {Vegetable} {Harvester} with a {Low}-{Cost} {Gripper} {Using} a {3D} {Sensor}}, volume = {20}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/1424-8220/20/1/93}, doi = {10.3390/s20010093}, abstract = {Reliable and robust systems to detect and harvest fruits and vegetables in unstructured environments are crucial for harvesting robots. In this paper, we propose an autonomous system that harvests most types of crops with peduncles. A geometric approach is first applied to obtain the cutting points of the peduncle based on the fruit bounding box, for which we have adapted the model of the state-of-the-art object detector named Mask Region-based Convolutional Neural Network (Mask R-CNN). We designed a novel gripper that simultaneously clamps and cuts the peduncles of crops without contacting the flesh. We have conducted experiments with a robotic manipulator to evaluate the effectiveness of the proposed harvesting system in being able to efficiently harvest most crops in real laboratory environments.}, language = {en}, number = {1}, urldate = {2021-10-07}, journal = {Sensors}, author = {Zhang, Tan and Huang, Zhenhai and You, Weijie and Lin, Jiatao and Tang, Xiaolong and Huang, Hui}, month = jan, year = {2020}, note = {Number: 1 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {cutting point detection, gripper, harvesting robot, segmentation}, pages = {93}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\58FAX7IS\\93.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\7AB4TFN6\\Zhang et al. - 2020 - An Autonomous Fruit and Vegetable Harvester with a.pdf:application/pdf}, } @inproceedings{veys_ultra-low-cost_2017, title = {An ultra-low-cost active multispectral crop diagnostics device}, doi = {10.1109/ICSENS.2017.8234211}, abstract = {A multispectral imaging system is presented, using components that will support its deployment within the world of small-holder agriculture. An active narrowband illumination setup was selected, which allowed a low-cost broadband image sensor to be used. The preliminary set-up has been demonstrated with droughted tomato plants as a proof of concept. The results demonstrated a 5, 28 and 90\% deterioration after day 1, 2 and 3 respectively; calculated by the disease/water stress index. Initial analysis showed that for specific applications the device be used in lieu of high-cost diffraction gratings, however additional innovation is required to negate unwanted sensing phenomena.}, booktitle = {2017 {IEEE} {SENSORS}}, author = {Veys, Charles and Hibbert, James and Davis, Phillip and Grieve, Bruce}, month = oct, year = {2017}, keywords = {Indexes, Agriculture, Vegetation mapping, Remote Sensing, Crop Analysis, Drought, Imaging, Lighting, Multispectral Imaging, Reflectivity, Stress}, pages = {1--3}, file = {IEEE Xplore Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\IBVRHZ59\\Veys et al. - 2017 - An ultra-low-cost active multispectral crop diagno.pdf:application/pdf}, } @misc{noauthor_gtr_nodate, title = {{GtR}}, url = {https://gtr.ukri.org/projects?ref=101817}, urldate = {2021-10-07}, file = {GtR:C\:\\Users\\Edify 01\\Zotero\\storage\\8NEETD2W\\projects.html:text/html}, } @misc{hgca_-_home_grown_cereal_authority_hgca_nodate, title = {{HGCA}: {Wheat} {Growth} {Guide} 2008}, author = {HGCA - Home Grown Cereal Authority}, keywords = {Europe, UK, wheat, development cycle, growth stages}, file = {WGG_2008.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\EYD5KUQ4\\WGG_2008.pdf:application/pdf}, } @misc{noauthor_growth_nodate, title = {The growth stages of cereals {\textbar} {AHDB}}, url = {https://ahdb.org.uk/knowledge-library/the-growth-stages-of-cereals}, urldate = {2021-10-10}, keywords = {Europe, Cereal crops, UK, development cycle, growth stages}, file = {The growth stages of cereals | AHDB:C\:\\Users\\Edify 01\\Zotero\\storage\\QLXZB56C\\the-growth-stages-of-cereals.html:text/html}, } @misc{noauthor_growth_nodate-1, title = {The growth stages of oilseed rape {\textbar} {AHDB}}, url = {https://ahdb.org.uk/knowledge-library/the-growth-stages-of-oilseed-rape}, urldate = {2021-10-10}, keywords = {Europe, Cereal crops, UK, development cycle, growth stages}, } @misc{noauthor_step-by-step_2021, title = {Step-by-step guide for a tailored approach to crop nutrition}, url = {https://www.fwi.co.uk/arable/crop-management/nutrition-and-fertiliser/step-by-step-guide-for-a-tailored-approach-to-crop-nutrition}, abstract = {Taking a tailored approach to nutrition can help cereal growers achieve a more sustainable crop performance, through better plant health and resilience.}, language = {en-US}, urldate = {2021-10-17}, journal = {Farmers Weekly}, month = jan, year = {2021}, note = {Section: Nutrition and fertiliser}, keywords = {UK, cereals, crop nutrition}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ZJLNDC46\\step-by-step-guide-for-a-tailored-approach-to-crop-nutrition.html:text/html}, } @misc{noauthor_agronomy_2018, title = {Agronomy {Advice} {\textbar} {N}-{Sensor} twins science with sense {\textbar} {Yara} {UK}}, url = {https://www.yara.co.uk/crop-nutrition/agronomy-advice/n-sensor-science-with-sense/}, abstract = {There are two aspects, you could argue, that define the real cutting-edge technological advances in today’s agricultural equipment – tools that generate...}, language = {en-GB}, urldate = {2021-10-17}, journal = {Yara United Kingdom}, month = feb, year = {2018}, keywords = {multi-spectral sensors, N sensor, VRA, Yara}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\7B75MUSD\\n-sensor-science-with-sense.html:text/html}, } @article{fink_iron_2016, title = {Iron oxides and organic matter on soil phosphorus availability}, volume = {40}, issn = {1413-7054, 1981-1829}, url = {http://www.scielo.br/j/cagro/a/LSkxx83fPT5pLnf6MmK9vnn/?lang=en}, doi = {10.1590/1413-70542016404023016}, abstract = {ABSTRACT Continuous crop expansion has led to a growing demand for phosphate fertilizers. A sound knowledge of the dynamics of phosphorus, and its interaction with iron oxides and organic matter, can be useful to develop effective strategies for sustainable management, especially in a scenario of increasing shortage of mineral phosphate resources. In this paper, we review the relationship of phosphate to iron oxides and organic matter, and its effect on phosphorus availability. Crops typically obtain phosphate from weathered minerals and dissolved fertilizers. However, the amount of phosphorus present in the soil solution depends on the extent to which it is adsorbed or desorbed by iron oxides, which may be influenced by interactions with organic matter. Therefore, systems for fertilizer recomendation based on methodologies considering interactions between soil components such as oxides and organic matter, and the phosphorus sorption capacity resulting from such interactions (e.g. residual P analysis), may be more reliable to ensure efficient, rational use of phosphate.}, language = {en}, urldate = {2021-10-26}, journal = {Ciência e Agrotecnologia}, author = {Fink, Jessé Rodrigo and Inda, Alberto Vasconcellos and Tiecher, Tales and Barrón, Vidal}, month = aug, year = {2016}, note = {Publisher: Editora da UFLA}, keywords = {Goethite, hematite, organic carbon, phosphorus adsorption, phosphorus desorption}, pages = {369--379}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\S52SDHMU\\LSkxx83fPT5pLnf6MmK9vnn.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\UMHAFXMQ\\Fink et al. - 2016 - Iron oxides and organic matter on soil phosphorus .pdf:application/pdf}, } @article{hoque_mechanisms_1981, title = {Mechanisms of phosphorus fixation in soil and the factors affecting them}, url = {https://scholar.google.com/scholar_lookup?title=Mechanisms+of+phosphorus+fixation+in+soil+and+the+factors+affecting+them&author=Hoque%2C+M.S.+%28Bangladesh+Agricultural+Univ.%2C+Mymensingh.+Dept.+of+Soil+Science%29&publication_year=1981}, abstract = {The literature on the mechanisms of fixation in soil and the factors affecting the processes are reviewed and discussed. Phosphates may become fixed in soils by absorption or precipitation or by both. In acid soils P fixation is caused mainly by absorbed or soluble forms of Fe, Al and Mn and their hydrated oxides as well as by clay mineral. There is ample evidence that Ca plays the major role in P fixation in calcareous or alkalin soils. Fixation of P in soils is influenced by many factors like P status in soil time of reaction, temperature, moisture, soil reaction, type of mineral, organic matter and others. The greater the time of soils and added P are in contact, the greater is the amount of P fixation. The P fixing capacity of soils increases with departure from a pH near neutrality.}, language = {English}, urldate = {2021-10-26}, journal = {Bangladesh Journal of Agricultural Sciences (Bangladesh)}, author = {Hoque, M. S.}, year = {1981}, } @book{asomaning_processes_2020, title = {Processes and {Factors} {Affecting} {Phosphorus} {Sorption} in {Soils}}, isbn = {978-1-83880-114-4}, url = {https://www.intechopen.com/chapters/70866}, abstract = {The subject of this chapter is soil chemistry. The chapter is entitled Processes and Factors Affecting Phosphorus (P) Adsorption in Soils. The chapter aims to give an overview of the major mechanisms responsible for phosphate sorption (i.e., adsorption and absorption of phosphate) in soils, particularly of acid soils. According to studies conducted by some soil scientists, the major soil factors affecting P sorption are time, soil pH, soil organic matter, and iron and aluminium oxides of soils. Studies conducted indicated that adsorption of the P increases as the P ages in the soil. Soil pH affects phosphate adsorption but the effect is limited for adsorption by soils in the pH range of 4–8. Organic matter may affect P adsorption in two ways: indirectly by inhibiting iron oxide crystallisation and directly by competing for adsorption sites. On per mole basis, oxalate extractable aluminium oxides adsorb nearly twice as much P as oxalate extractable iron oxides due to poorer crystallinity (higher specific area) of the aluminium oxides compared to the iron oxides and also to a higher charge of the former. The chapter also highlights the pedotransfer functions (PTFs) of Borggaard, which can be used to calculate for the P adsorption in highly weathered acid soils.}, language = {en}, urldate = {2021-10-26}, publisher = {IntechOpen}, author = {Asomaning, Samuel Kwesi}, month = mar, year = {2020}, doi = {10.5772/intechopen.90719}, note = {Publication Title: Sorption in 2020s}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\LGHIQEYF\\70866.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\EBGDT2P2\\Asomaning - 2020 - Processes and Factors Affecting Phosphorus Sorptio.pdf:application/pdf}, } @article{cuenca-garcia_soil_2019, title = {Soil geochemical methods in archaeo-geophysics: {Exploring} a combined approach at sites in {Scotland}}, volume = {26}, issn = {1099-0763}, shorttitle = {Soil geochemical methods in archaeo-geophysics}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1723}, doi = {10.1002/arp.1723}, abstract = {This article explores the application of geophysical and soil geochemical methods to detect archaeological features in three traditionally ‘difficult’ survey environments in Scotland: wind-blown sands (Bay of Skaill, Orkney), clay (Chesterhall Parks Farm, Lanarkshire) and glacial drift deposits (Forteviot, Perthshire). The results presented here are part of the first research project that systematically tested a combined approach using geophysical and soil characterisation to understand the proxy responses of known archaeological features. First, a range of geophysical techniques [earth resistance, magnetometry, frequency domain electromagnetics (FDEM) and ground-penetrating radar (GPR)] was employed over archaeological targets. Second, the different geophysical results were considered with respect to soil chemical concentrations (total phosphate and multi-element analysis), texture, pH, conductivity, organic matter content and magnetic susceptibility from archaeological deposits, topsoil and subsoil samples. This study demonstrates that, by focusing on the responses of single archaeological features and assessing their physical and chemical signatures, soil composition and processes involved in the ‘history’ of buried features are of importance in improving our understanding of the reasons behind their detection with geophysical means. For example, at the cropmark site at Forteviot, chemical transformations can be triggered by organic matter accumulation and increased water retention within prehistoric ditch deposits and can have an effect on the type of magnetic contrast. In addition, chemical concentrations revealing anthropogenic organic materials can explain the enhanced conductivity of theoretically impervious features, as illustrated at the Bay of Skaill site. The study also provide insights into how a particular soil environment may affect different geophysical techniques such as the masking effects of heterogeneous glacial drift deposits or deep windblown sands. These types of survey environments characterise many archaeologically rich areas in Scotland, where integrated strategies, such as the one used in this investigation, are the best option to maximise detection of subsurface features and provide confident and augmented interpretations.}, language = {en}, number = {1}, urldate = {2021-10-26}, journal = {Archaeological Prospection}, author = {Cuenca-García, Carmen}, year = {2019}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1723}, keywords = {archaeological prospection, multi-technique geophysical survey, Scottish archaeology, soil chemical analysis, soil magnetic susceptibility, soil physical characterisation}, pages = {57--72}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\QNENWRSW\\Cuenca-García - 2019 - Soil geochemical methods in archaeo-geophysics Ex.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\TMKQ7AJZ\\arp.html:text/html}, } @article{romero-ruiz_review_2018, title = {A {Review} of {Geophysical} {Methods} for {Soil} {Structure} {Characterization}}, volume = {56}, issn = {1944-9208}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2018RG000611}, doi = {10.1029/2018RG000611}, abstract = {The growing interest in the maintenance of favorable soil structure is largely motivated by its central role in plant growth, soil ecological functioning, and impacts on surface water and energy fluxes. Soil structure pertains to the spatial arrangement of voids and solid constituents, their aggregation, and mechanical state. As a fragile product of soil biological activity that includes invisible ingredients (mechanical and ecological states), soil structure is difficult to define rigorously, and measurements of relevant metrics often rely on core samples or on episodic point measurements. The presence of soil structure has not yet been explicitly incorporated in climate and Earth systems models, partially due to incomplete methodological means to characterize it at relevant scales and to parameterize it in spatially extensive models. We seek to review the potential of harnessing geophysical methods to fill the scale gap in characterization of soil structure directly (via impact of soil pores, transport, and mechanical properties on geophysical signals) or indirectly by measurement of surrogate variables (wetness and rates of drainage). We review basic aspects of soil structure and challenges of characterization across spatial and temporal scales and how geophysical methods could be used for the task. Additionally, we propose the use of geophysical models, inversion techniques, and combination of geophysical methods for extracting soil structure information at previously unexplored spatial and temporal scales.}, language = {en}, number = {4}, urldate = {2021-10-26}, journal = {Reviews of Geophysics}, author = {Romero-Ruiz, Alejandro and Linde, Niklas and Keller, Thomas and Or, Dani}, year = {2018}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2018RG000611}, keywords = {geophysics, hydro-ecological function, pedophysics, petrophysics, soil structure}, pages = {672--697}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\BJS4VNNT\\Romero-Ruiz et al. - 2018 - A Review of Geophysical Methods for Soil Structure.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\YU4X3384\\2018RG000611.html:text/html}, } @article{corti_evaluation_2020, title = {Evaluation of {In}-{Season} {Management} {Zones} from {High}-{Resolution} {Soil} and {Plant} {Sensors}}, volume = {10}, doi = {10.3390/agronomy10081124}, abstract = {The adoption of precision agriculture has the potential to increase the environmental sustainability of cropping systems as well as farmers’ income. Farmers in transition to precision agriculture need low-input and effective protocols to delineate homogenous management zones to optimize their actions without past knowledge e.g., yield maps. Different approaches have been developed so far, based on the analysis of the within-field variability in crop and soil properties, but procedures were rarely suited for operational conditions. We identified here a low-inputs protocol to map management zones from soil electrical conductivity and/or crop vegetation indices, using a winter wheat field in northern Italy as a pilot case. The reliability of the alternative data sources was evaluated at three crop development stages using a yield map as reference. Red-edge and NIR (NDRE) bands were the most reliable data sources for management zones identification, with 62\%, 68\%, and 74\% of correct classifications at early tillering, stem elongation, and late booting, respectively. Our work identifies a minimum dataset for accurate management zones’ definition and highlights that in-season monitoring based on the red-edge band was able to reliably identify management zones already at early tillering, despite minor differences in crop growth.}, journal = {Agronomy}, author = {Corti, Martina and Marino Gallina, Pietro and Cavalli, Daniele and Ortuani, Bianca and Cabassi, Giovanni and Cola, Gabriele and Vigoni, Antonio and Degano, Luigi and Bregaglio, Simone}, month = aug, year = {2020}, pages = {1124}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\IYAM3BP9\\Corti et al. - 2020 - Evaluation of In-Season Management Zones from High.pdf:application/pdf}, } @article{corti_evaluation_2020-1, title = {Evaluation of {In}-{Season} {Management} {Zones} from {High}-{Resolution} {Soil} and {Plant} {Sensors}}, volume = {10}, doi = {10.3390/agronomy10081124}, abstract = {The adoption of precision agriculture has the potential to increase the environmental sustainability of cropping systems as well as farmers’ income. Farmers in transition to precision agriculture need low-input and effective protocols to delineate homogenous management zones to optimize their actions without past knowledge e.g., yield maps. Different approaches have been developed so far, based on the analysis of the within-field variability in crop and soil properties, but procedures were rarely suited for operational conditions. We identified here a low-inputs protocol to map management zones from soil electrical conductivity and/or crop vegetation indices, using a winter wheat field in northern Italy as a pilot case. The reliability of the alternative data sources was evaluated at three crop development stages using a yield map as reference. Red-edge and NIR (NDRE) bands were the most reliable data sources for management zones identification, with 62\%, 68\%, and 74\% of correct classifications at early tillering, stem elongation, and late booting, respectively. Our work identifies a minimum dataset for accurate management zones’ definition and highlights that in-season monitoring based on the red-edge band was able to reliably identify management zones already at early tillering, despite minor differences in crop growth.}, journal = {Agronomy}, author = {Corti, Martina and Marino Gallina, Pietro and Cavalli, Daniele and Ortuani, Bianca and Cabassi, Giovanni and Cola, Gabriele and Vigoni, Antonio and Degano, Luigi and Bregaglio, Simone}, month = aug, year = {2020}, pages = {1124}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\8BFFM3NX\\Corti et al. - 2020 - Evaluation of In-Season Management Zones from High.pdf:application/pdf}, } @article{christiansen_improved_2016, title = {Improved {Geoarchaeological} {Mapping} with {Electromagnetic} {Induction} {Instruments} from {Dedicated} {Processing} and {Inversion}}, volume = {8}, issn = {2072-4292}, url = {http://www.mdpi.com/2072-4292/8/12/1022}, doi = {10.3390/rs8121022}, abstract = {Increasingly, electromagnetic induction methods (EMI) are being used within the area of archaeological prospecting for mapping soil structures or for studying paleo-landscapes. Recent hardware developments have made fast data acquisition, combined with precise positioning, possible, thus providing interesting possibilities for archaeological prospecting. However, it is commonly assumed that the instrument operates in what is referred to as Low Induction Number, or LIN. Here, we detail the problems of the approximations while discussing a best practice for EMI measurements, data processing, and inversion for understanding a paleo-landscape at an Iron Age human bone depositional site (Alken Enge) in Denmark. On synthetic as well as field data we show that soil mapping based on EMI instruments can be improved by applying data processing methodologies from adjacent scientific fields. Data from a 10 hectare study site was collected with a line spacing of 1–4 m, resulting in roughly 13,000 processed soundings, which were inverted with a full non-linear algorithm. The models had higher dynamic range in the retrieved resistivity values, as well as sharper contrasts between structural elements than we could obtain by looking at data alone. We show that the pre-excavation EMI mapping facilitated an archaeological prospecting where traditional trenching could be replaced by a few test pits at selected sites, hereby increasing the chance of finding human bones. In a general context we show that (1) dedicated processing of EMI data is necessary to remove coupling from anthropogenic structures (fences, phone cables, paved roads, etc.), and (2) that carrying out a dedicated full non-linear inversion with spatial coherency constraints improves the accuracy of resistivities and structures over using the data as they are or using the Low Induction Number (LIN) approximation.}, language = {en}, number = {12}, urldate = {2021-11-05}, journal = {Remote Sensing}, author = {Christiansen, Anders and Pedersen, Jesper and Auken, Esben and Søe, Niels and Holst, Mads and Kristiansen, Søren}, month = dec, year = {2016}, pages = {1022}, file = {Christiansen et al. - 2016 - Improved Geoarchaeological Mapping with Electromag.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\HEIT748R\\Christiansen et al. - 2016 - Improved Geoarchaeological Mapping with Electromag.pdf:application/pdf}, } @article{algeo_comparison_2018, title = {A {Comparison} of {Ground}-{Penetrating} {Radar} {Early}-{Time} {Signal} {Approaches} for {Mapping} {Changes} in {Shallow} {Soil} {Water} {Content}}, volume = {17}, doi = {10.2136/vzj2018.01.0001}, abstract = {Improving irrigation efficiency requires accurate assessment of the soil moisture distribution in time and space, but obtaining accurate observational data is challenging. Early-time signal (ETS) amplitude analysis of ground-penetrating radar (GPR) data may permit such rapid noninvasive characterization. In this study we performed controlled irrigation experiments using a multifrequency GPR system to compare two statistics used to quantify the ETS: average envelope amplitude (AEA) and carrier frequency amplitude (CFA). Supporting data were provided by direct measurements, electrical resistivity imaging (ERI), and synthetic modeling. In our first experiment, both statistics successfully related the ETS for 250 and 400 MHz GPR data to increasing water content. However, the 400 MHz AEA lost sensitivity at later stages of the irrigation process, whereas the 400 MHz CFA remained sensitive to changes in water content. The 1000 MHz data did not show the expected relationships, possibly due to shallow reflectors, such as the wetting front, which the higher frequency antennae would have a greater chance of detecting, as supported by synthetic modeling. In our second experiment, we focused on the effect of the time window on calculating ETS statistics. We demonstrate that, when there is interference in the ETS, using a shorter time window instead of the more common first positive half cycle improves correlation with soil moisture content. Our work shows that the GPR ETS data respond to changes in soil water content in similar fashion to ERI data.}, journal = {Vadose Zone Journal}, author = {Algeo, Jonathan and Slater, Lee and Binley, Andrew and Van Dam, Remke and Watts, C.}, month = sep, year = {2018}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\2JTEPRXT\\Algeo et al. - 2018 - A Comparison of Ground-Penetrating Radar Early-Tim.pdf:application/pdf}, } @misc{noauthor_handbook_nodate, title = {Handbook of {Agricultural} {Geophysics}}, url = {https://www.routledge.com/Handbook-of-Agricultural-Geophysics/Allred-Daniels-Ehsani/p/book/9780367387211}, abstract = {Precision farming, site infrastructure assessment, hydrologic monitoring, and environmental investigations — these are just a few current and potential uses of near-surface geophysical methods in agriculture. Responding to the growing demand for this technology, the Handbook of Agricultural Geophysics supplies a clear, concise overview of near-surface geophysical methods that can be used in agriculture and provides detailed descriptions of situations in which these techniques have been employe}, language = {en}, urldate = {2021-11-21}, journal = {Routledge \& CRC Press}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\M9CPNGVS\\9780367387211.html:text/html}, } @article{attia_al_hagrey_geophysical_2007, title = {Geophysical imaging of root-zone, trunk, and moisture heterogeneity}, volume = {58}, issn = {0022-0957}, url = {https://doi.org/10.1093/jxb/erl237}, doi = {10.1093/jxb/erl237}, abstract = {The most significant biotic and abiotic stress agents of water extremity, salinity, and infection lead to wood decay and modifications of moisture and ion content, and density. This strongly influences the (di-)electrical and mechanical properties and justifies the application of geophysical imaging techniques. These are less invasive and have high resolution in contrast to classical methods of destructive, single-point measurements for inspecting stresses in trees and soils. This review presents some in situ and in vivo applications of electric, radar, and seismic methods for studying water status and movement in soils, roots, and tree trunks. The electrical properties of a root-zone are a consequence of their moisture content. Electrical imaging discriminates resistive, woody roots from conductive, soft roots. Both types are recognized by low radar velocities and high attenuation. Single roots can generate diffraction hyperbolas in radargrams. Pedophysical relationships of water content to electrical resistivity and radar velocity are established by diverse infiltration experiments in the field, laboratory, and in the full-scale ‘GeoModel’ at Kiel University. Subsurface moisture distributions are derived from geophysical attribute models. The ring electrode technique around trunks images the growth ring structure of concentric resistivity, which is inversely proportional to the fluid content. Healthy trees show a central high resistivity within the dry heartwood that strongly decreases towards the peripheral wet sapwood. Observed structural deviations are caused by infection, decay, shooting, or predominant light and/or wind directions. Seismic trunk tomography also differentiates between decayed and healthy woods.}, number = {4}, urldate = {2021-11-21}, journal = {Journal of Experimental Botany}, author = {Attia al Hagrey, Said}, month = mar, year = {2007}, pages = {839--854}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\GQVN2XMS\\429474.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\4APB7EV9\\Attia al Hagrey - 2007 - Geophysical imaging of root-zone, trunk, and moist.pdf:application/pdf}, } @phdthesis{van_den_berge_role_2021, type = {dissertation}, title = {Role of hedgerow systems for biodiversity and ecosystem services in agricultural landscapes}, copyright = {I have retained and own the full copyright for this publication}, url = {http://hdl.handle.net/1854/LU-8687480}, language = {eng}, urldate = {2021-11-11}, school = {Ghent University}, author = {Van Den Berge, Sanne}, year = {2021}, note = {ISBN: 9789463573894}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\4927F37T\\8687480.html:text/html}, } @article{van_den_berge_soil_2021, title = {Soil carbon of hedgerows and ‘ghost’ hedgerows}, volume = {95}, copyright = {I have transferred the copyright for this publication to the publisher}, issn = {0167-4366, 1572-9680}, url = {http://hdl.handle.net/1854/LU-8716769}, doi = {10.1007/s10457-021-00634-6}, abstract = {Agroforestry can contribute significantly to carbon sequestration in agricultural lands, as carbon accumulates both in tree biomass and the soil. One of the oldest, yet declining, forms of agroforestry in Europe are hedgerow-bordered fields. An analysis of historical maps of our study area in Belgium shows that 70\% of the hedgerow network was cleared since 1960, creating a large number of 'ghost' hedgerows. We selected arable fields next to hedgerows, 'ghost' hedgerows and grass strips to study how hedgerow trees influence SOC stocks and how much of these are still present after hedgerow clearing. SOC stocks to a depth of 23 cm reached up to 81.7 +/- 28.8 Mg C ha(-1) in hedgerows, storing a considerably larger amount of soil carbon compared to grass strips (56.6 +/- 14.5 Mg C ha(-1)). These built-up stocks were completely gone in 'ghost' hedgerows (57.9 +/- 14.1 Mg C ha(-1)). In the fields adjacent to hedgerows, SOC stocks were only slightly (and insignificantly) increased compared to stocks in fields with grass strips (56.4 +/- 6.3 vs 55.6 +/- 5.0 Mg C ha(-1)) with an exponential decay up to 30 m from the margin. This trend was still limitedly detectable in 'ghost' hedgerowbordered fields, however stocks were not elevated anymore (53.9 +/- 6.1 Mg C ha(-1)). Since 1960, 4 957 +/- 1 664 Mg C from the soil alone were released back into the atmosphere due to hedgerow removal in the study area. The implementation of a strict hedgerow conservation policy would thus be a highly effective climate change mitigation measure in agricultural landscapes.}, language = {eng}, number = {6}, urldate = {2021-11-11}, journal = {AGROFORESTRY SYSTEMS}, author = {Van Den Berge, Sanne and Vangansbeke, Pieter and Baeten, Lander and Vanneste, Thomas and Vos, Fien and Verheyen, Kris}, year = {2021}, note = {Number: 6}, pages = {1087--1103}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JPZ97RK8\\8716769.html:text/html}, } @article{ford_how_2019, title = {How do hedgerows influence soil organic carbon stock in livestock-grazed pasture?}, volume = {35}, issn = {1475-2743}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/sum.12517}, doi = {10.1111/sum.12517}, abstract = {Hedgerows have the potential to influence ecosystem function in livestock-grazed pasture. Despite this, they are often ignored when quantifying farmland ecosystem service delivery. In this study, we assess the contribution of hedgerows to the ecosystem function of carbon (C) storage, with a particular emphasis on soil organic carbon (SOC). We measured SOC stock (kg C m−2), on an equivalent soil mass basis, at 0–0.15 m depth in pasture adjacent to 38 hedgerows (biotic) and 16 stone walls or fences (abiotic controls) across ten farms in the county of Conwy, Wales, UK. Pasture SOC stock ( 7 kg C m−2) was similar adjacent to biotic and abiotic field boundaries, positively associated with soil moisture and negatively with soil bulk density (BD). For biotic boundaries, two further variables were significantly associated with SOC stock, distance from hedgerow (decrease in SOC stock) and slope orientation (upslope SOC stock greater than downslope). For pasture adjacent to hedgerows, a model combining the aforementioned variables (BD, soil moisture, distance from hedgerow, slope orientation) explained 78\% of variation in SOC stock. This study demonstrates that whilst hedgerows do have subtle positive effects on SOC stock in adjacent pasture, SOC storage adjacent to field boundaries is influenced more by soil moisture content and BD than field boundary type.}, language = {en}, number = {4}, urldate = {2021-11-11}, journal = {Soil Use and Management}, author = {Ford, Hilary and Healey, John R. and Webb, Bid and Pagella, Tim F. and Smith, Andrew R.}, year = {2019}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/sum.12517}, keywords = {agriculture, agroforestry, ecosystem function, grassland, soil carbon, woody linear feature}, pages = {576--584}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\VSI4NI6V\\sum.html:text/html;Submitted Version:C\:\\Users\\Edify 01\\Zotero\\storage\\ENND2XK5\\Ford et al. - 2019 - How do hedgerows influence soil organic carbon sto.pdf:application/pdf}, } @article{dal_ferro_organic_2020, title = {Organic carbon storage potential in deep agricultural soil layers: {Evidence} from long-term experiments in northeast {Italy}}, volume = {300}, issn = {0167-8809}, shorttitle = {Organic carbon storage potential in deep agricultural soil layers}, url = {https://www.sciencedirect.com/science/article/pii/S0167880920301523}, doi = {10.1016/j.agee.2020.106967}, abstract = {The significant contribution to the global carbon budget made by soil organic carbon (SOC) inspired the “4 per 1000” initiative. It promotes agricultural practices aimed at raising SOC stocks 0.4 \% annually over 20 years. However, the response of topsoil and deep soil profiles to agroecosystem changes is largely unknown at present. Our work aims to quantify deep SOC accumulations in stabilized croplands and grasslands of northeast Italy and identify the best management practices to increase those stores. Soil profiles were collected to 70 and 90 cm depths from three well-established long-term experiments. A total of 1242 soil samples were analyzed for SOC concentrations as a function of soil type, soil management practice, and cropping system. SOC stocks were quantified using the equivalent soil mass method. Results show that SOC stocks averaged 23.2 Mg ha−1 in sandy Arenosol, 59.3 Mg ha−1 in silty loam Cambisol, 111.6 Mg ha−1 in clay loam Gleysol, and 383.5 Mg ha−1 in peaty Histosol. Substantial SOC stocks were found in the subsoil beneath the tilled layer, ranging between 59 \% and 74 \% in sandy and clay loam soils. Among the considered managements, the SOC accumulation rate of permanent meadow topsoil was higher than croplands (0.299 Mg ha−1 yr−1), which fell to 0.256 Mg ha−1 yr−1 when estimated along the full soil profile. In contrast, organic carbon added through manures and residues, coupled with minimum tillage practices, led to increased average SOC stock rates in the topsoil (0.205 Mg ha−1 yr−1) and throughout the full soil profile (0.386 Mg ha−1 yr−1), suggesting that some translocation dynamics occurred. The long-term adoption of permanent meadow, along with manure or residue addition under minimum tillage, made it possible to achieve “4 per 1000” goals to great depths in naturally poor-SOC sandy and silty loam soils. In SOC-rich soil, only in the topsoil layer achieved this.}, language = {en}, urldate = {2021-11-11}, journal = {Agriculture, Ecosystems \& Environment}, author = {Dal Ferro, Nicola and Piccoli, Ilaria and Berti, Antonio and Polese, Riccardo and Morari, Francesco}, month = sep, year = {2020}, keywords = {Cropping systems, 4 per 1000 initiative, Management practices, SOC, SOC stock change, Tillage}, pages = {106967}, } @article{poeplau_stocks_2020, title = {Stocks of organic carbon in {German} agricultural soils—{Key} results of the first comprehensive inventory}, volume = {183}, issn = {1522-2624}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jpln.202000113}, doi = {10.1002/jpln.202000113}, abstract = {Background: There is considerable uncertainty about the actual size of the global soil organic carbon (SOC) pool and its spatial distribution due to insufficient and heterogeneous data coverage. Aims: We aimed to assess the size of the German agricultural SOC stock and develop a stratification approach that could be used in national greenhouse gas reporting. Methods: Soils from a total of 3104 sites, comprising 2234 croplands, 820 permanent grasslands and 50 sites with permanent crops (vineyards, orchards) were sampled in a grid of 8 × 8 km to a depth of 100 cm in fixed depth increments. In addition, a decade of management data was recorded in a questionnaire completed by farmers. Two different approaches were used to stratify cropland and grassland mineral soils and derive homogeneous groups: stratification via soil type (pedogenesis) and via SOC-relevant soil properties. Results: A total of 146 soils were identified as organic soils, which stored by far the highest average SOC stock of 528 ± 201 Mg ha−1 in 0–100 cm depth. Of the mineral soils, croplands and permanent crops stored on average 61 ± 25 and 62 ± 25 Mg ha−1 in 0–30 cm (topsoil) and 35 ± 30 and 44 ± 28 Mg ha−1 in 30–100 cm (subsoil), while permanent grasslands stored significantly more SOC (88 ± 32 and 47 ± 50 Mg ha−1 in topsoil and subsoil). Overall, topsoils stored 67 ± 14\% and subsoils 33 ± 14\% of total SOC stocks. Soil C:N ratio, clay content and groundwater level were major factors that explained the spatial variability of SOC stocks in mineral soils. Accordingly, Podzols, Gleysols and Vertisols were found to have the highest SOC stocks. Conclusions: Stratification via soil properties yielded the most comparable cropland and grassland strata and is thus preferable for estimating land-use change effects, e.g., for greenhouse gas inventories. In total, 2.5 Pg C are stored in the upper 100 cm of German agricultural soils, making them the largest organic carbon pool in terrestrial ecosystems of Germany. This bares a large responsibility for the agricultural sector and society as a whole to maintain and, if possible, enhance this pool.}, language = {en}, number = {6}, urldate = {2021-11-11}, journal = {Journal of Plant Nutrition and Soil Science}, author = {Poeplau, Christopher and Jacobs, Anna and Don, Axel and Vos, Cora and Schneider, Florian and Wittnebel, Mareille and Tiemeyer, Bärbel and Heidkamp, Arne and Prietz, Roland and Flessa, Heinz}, year = {2020}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/jpln.202000113}, keywords = {agriculture, agricultural soil inventory, soil organic matter, soil survey, stratification, terrestrial carbon}, pages = {665--681}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\HUK5GMHP\\jpln.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\YRCQ4YQA\\Poeplau et al. - 2020 - Stocks of organic carbon in German agricultural so.pdf:application/pdf}, } @article{collier_are_2021, title = {Are field boundary hedgerows the earliest example of a nature-based solution?}, volume = {120}, issn = {1462-9011}, url = {https://www.sciencedirect.com/science/article/pii/S1462901121000538}, doi = {10.1016/j.envsci.2021.02.008}, abstract = {The arrival of the phrase nature-based solutions into the lexicon of academics, planners, managers and policy makers in recent years has sparked a heated debate as to the effectiveness of using nature as a viable solution for mitigating the impacts of anthropogenic environmental change. One of the difficulties of evaluating the potential efficacy and impact of nature-based solutions is that it is believed that there is little evidence by way of a precedent or long-term successful examples. Much literature exists on the subject of designing with nature to provide multi-functional green infrastructure, connectivity in the landscape, and ecosystem service provision. Indeed, in the opinion of many, the nature-based solution approach appears to synergise research into green infrastructure, ecological connectivity and ecosystem service provision for building climate-related resilience. However, when a nature-based solution has been specifically selected over, say, an engineered solution the literature is rather less clear. So, decision-makers may find it necessary to rely on less reliable sources of impact evidence. This paper argues that field boundary hedgerows may be considered to be exemplars of a nature-based solution, one that was planned, designed, perfected and mainstreamed at a landscape scale, that was specifically selected over a non-nature-based solution, and one that is still in providing solutions and co-benefits today. Therefore, hedgerows may provide some perspective into the potential or emergent co-benefits that the current nature-based solution approach seeks to provide.}, language = {en}, urldate = {2021-11-11}, journal = {Environmental Science \& Policy}, author = {Collier, Marcus J.}, month = jun, year = {2021}, keywords = {Co-benefits, Field boundaries, Hedgerow, Nature-based solutions}, pages = {73--80}, } @article{braud_building_2020, title = {Building the information system of the {French} {Critical} {Zone} {Observatories} network: {Theia}/{OZCAR}-{IS}}, volume = {0}, issn = {0262-6667}, shorttitle = {Building the information system of the {French} {Critical} {Zone} {Observatories} network}, url = {https://doi.org/10.1080/02626667.2020.1764568}, doi = {10.1080/02626667.2020.1764568}, abstract = {The French Critical Zone research infrastructure, OZCAR-RI, gathers 20 observatories sampling various compartments of the critical zone, each having developed their own data management and distribution systems. A common information system (Theia/OZCAR IS) was built to make their in situ observation FAIR (findable, accessible, interoperable, reusable). The IS architecture was designed after consultation of the users, data producers and IT teams involved in data management. A common data model based on various metadata standards was defined to create information fluxes between observatories’ ISs and the Theia/OZCAR IS. Controlled vocabularies were defined to develop a data discovery web portal offering a faceted search with various criteria, including variables names and categories that were harmonized in a thesaurus published on the web. This paper describes the IS architecture, the pivot data model and open-source solutions used to implement data discovery, and future steps to implement data downloading and interoperability services.}, number = {0}, urldate = {2021-11-22}, journal = {Hydrological Sciences Journal}, author = {Braud, Isabelle and Chaffard, Véronique and Coussot, Charly and Galle, Sylvie and Juen, Patrick and Alexandre, Hugues and Baillion, Philippe and Battais, Annick and Boudevillain, Brice and Branger, Flora and Brissebrat, Guillaume and Cailletaud, Rémi and Cochonneau, Gérard and Decoupes, Rémy and Desconnets, Jean-Christophe and Dubreuil, Arnaud and Fabre, Juliette and Gabillard, Santiago and Gérard, Marie-Françoise and Grellet, Sylvain and Herrmann, Agnès and Laarman, Olivier and Lajeunesse, Eric and Le Hénaff, Geneviève and Lobry, Olivier and Mauclerc, Antony and Paroissien, Jean-Baptiste and Pierret, Marie-Claire and Silvera, Norbert and Squividant, Hervé}, month = may, year = {2020}, note = {Publisher: Taylor \& Francis \_eprint: https://doi.org/10.1080/02626667.2020.1764568}, keywords = {information system, critical zone, data portal, FAIR data, in situ observations, land surface, OZCAR-RI}, pages = {1--19}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\C3BRZ7HR\\02626667.2020.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\PN3CBGV9\\Braud et al. - 2020 - Building the information system of the French Crit.pdf:application/pdf}, } @incollection{cummins_soils_2018, address = {Cham}, series = {World {Soils} {Book} {Series}}, title = {Soils and {Archaeology}}, isbn = {978-3-319-71189-8}, url = {https://doi.org/10.1007/978-3-319-71189-8_19}, abstract = {Archaeology is the study of the human past from its material remains, most of which are made of or found within soils and sediments. Past human actions impact the soil record, as seen through relics of changes in soil characteristics and qualities, changes to sedimentation, and the presence of archaeological features and artefacts preserved within modern soils. Soil and sediment conditions control what survives in the burial environment, what decomposes, and consequently influence all archaeological sites, artefacts, and ecological remains. The study of these remains, through survey, excavation, and post-excavation analyses, informs our understanding of past cultures and environments, providing insight into how people have interacted with the soil, both directly, through settlement, land use, and monument construction, and indirectly, by altering local ecosystems over time. Soils can be considered repositories of traces of human action, and in turn the soils of Ireland have formed under the continuous influence of people, up to the present day, when most land in Ireland is actively managed for agriculture, forestry, extraction or construction. Consequently, all land managers are stewards of soil-bound heritage, and have the opportunity and responsibility to recognize the archaeological heritage value of land in their care, and to participate in conserving this value as a public good. This chapter reviews some of the soil evidence for Irish landscape history, the heritage content of soils, archaeological work that has helped discover that heritage, and issues surrounding the management of the cultural heritage in soils.}, language = {en}, urldate = {2021-12-06}, booktitle = {The {Soils} of {Ireland}}, publisher = {Springer International Publishing}, author = {Cummins, Thomas and Lewis, Helen and Ní Lionáin, Clíodhna and Davis, Stephen}, editor = {Creamer, Rachel and O’Sullivan, Lilian}, year = {2018}, doi = {10.1007/978-3-319-71189-8_19}, keywords = {Geoarchaeology, Archaeological prospection, Taphonomy, Archaeological heritage, Cultural soils, Dowth, Sediments, Soil heritage}, pages = {267--280}, file = {Springer Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\T32LDZB8\\Cummins et al. - 2018 - Soils and Archaeology.pdf:application/pdf}, } @article{casana_archaeological_2017, title = {Archaeological {Aerial} {Thermography} in {Theory} and {Practice}}, volume = {5}, issn = {2326-3768}, url = {https://www.academia.edu/34609733/Archaeological_Aerial_Thermography_in_Theory_and_Practice}, abstract = {Archaeological Aerial Thermography in Theory and Practice}, language = {en}, number = {04}, urldate = {2021-11-28}, journal = {Advances in Archaeological Practice}, author = {Casana, Jesse and Wiewel, Adam and Cool, Autumn and Hill, Austin Chad and Fisher, Kevin D. and Laugier, Elise J.}, month = jan, year = {2017}, pages = {1}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\NY2A9EJG\\Archaeological_Aerial_Thermography_in_Theory_and_Practice.html:text/html}, } @article{blanchy_time-lapse_2020, title = {Time-lapse geophysical assessment of agricultural practices on soil moisture dynamics}, volume = {19}, issn = {1539-1663}, url = {https://doi.org/10.1002/vzj2.20080}, doi = {10.1002/vzj2.20080}, abstract = {Geophysical surveys are now commonly used in agriculture for mapping applications. High-throughput collection of geophysical properties such as electrical conductivity (inverse of resistivity) can be used as a proxy for soil properties of interest (e.g., moisture, texture, salinity). Most applications only rely on a single geophysical survey at a given time. However, time-lapse geophysical surveys have greater capabilities to characterize the dynamics of the system, which is the focus of this work. Assessing the impact of agricultural practices through the growth season can reveal important information for the crop production. In this work, we demonstrate the use of time-lapse electrical resistivity tomography (ERT) and electromagnetic induction (EMI) surveys through a series of three case studies illustrating common agricultural practices (cover crops, compaction with irrigation, and tillage with N fertilization). In the first case study, time-lapse EMI reveals the initial effect of cover crops on soil drying and the absence of effect on the subsequent main crop. In the second case study, compaction leading to a shallower drying depth for potatoes (Solanum tuberosum L.) was imaged by timelapse ERT. In the third case study, larger changes in electrical conductivity over time were observed in conventional tillage compared with direct drill using timelapse EMI. In addition, different N application rates had a significant effect on the yield and leaf area index but only ephemeral effects on the dynamics of electrical conductivity, mainly after the first application. Overall, time-lapse geophysical surveys show great potential for monitoring the impact of different agricultural practices that can influence crop yield.}, language = {en}, number = {1}, urldate = {2021-12-06}, journal = {Vadose Zone Journal}, author = {Blanchy, G. and Watts, C. W. and Richards, J. and Bussell, J. and Huntenburg, K. and Sparkes, D. L. and Stalham, M. and Hawkesford, M. J. and Whalley, W. R. and Binley, A.}, month = oct, year = {2020}, note = {Number: 1 Publisher: Soil Science Society of America (SSSA)}, pages = {e20080}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\XJGH93RA\\time-lapse-geophysical-assessment-of-agricultural-practices-on-soil-moisture-dynamics.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\PAV6WPDB\\Blanchy et al. - 2020 - Time-lapse geophysical assessment of agricultural .pdf:application/pdf}, } @misc{noauthor_aerial_nodate, title = {Aerial {Ground} {Penetrating} {Radar} ({GPR}) for {Soil} {Mapping} and {Irrigation} {Scheduling}}, url = {https://helixfarm.co.uk/technology-showcase/remote-sensing/aerial-ground-penetrating-radar-gpr-for-soil-mapping-and-irrigation-scheduling/}, abstract = {Non-destructive mapping of farm soil profiles, usefully combined with GPS systems ...}, language = {en-GB}, urldate = {2021-12-08}, journal = {Helix}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\F2NVLTEA\\aerial-ground-penetrating-radar-gpr-for-soil-mapping-and-irrigation-scheduling.html:text/html}, } @misc{noauthor_ground-penetrating_nodate, title = {Ground-{Penetrating} {Radar} - an overview {\textbar} {ScienceDirect} {Topics}}, url = {https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/ground-penetrating-radar}, urldate = {2021-12-08}, file = {Ground-Penetrating Radar - an overview | ScienceDirect Topics:C\:\\Users\\Edify 01\\Zotero\\storage\\NRKM55B7\\ground-penetrating-radar.html:text/html}, } @misc{noauthor_agriculture_nodate, title = {Agriculture \& {Forestry}}, url = {https://www.sensoft.ca/ground-penetrating-radar/agriculture-forestry/}, abstract = {Agriculture Forestry Environment Agriculture GPR sees use in high value crop management such as vineyards. The primary focus is on managing soil water…}, language = {en}, urldate = {2021-12-08}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\B4YNXJ5D\\agriculture-forestry.html:text/html}, } @misc{noauthor_geomorphological_nodate, title = {Geomorphological {Techniques} {\textbar} {British} {Society} for {Geomorphology}}, url = {https://www.geomorphology.org.uk/geomorph_techniques}, urldate = {2021-12-08}, file = {Geomorphological Techniques | British Society for Geomorphology:C\:\\Users\\Edify 01\\Zotero\\storage\\HX7MEM2F\\geomorph_techniques.html:text/html}, } @article{robinson_155_2013, title = {1.5.5. {Ground} {Penetrating} {Radar}}, abstract = {Ground-penetrating radar (GPR) is an effective tool to visualise the structure of the shallow subsurface. The purpose of this article is to offer guidelines to non-specialist GPR users on the collection, processing and interpretation of GPR data in a range of environments. The discussion on survey design focuses on single fold, fixed-offset reflection profiling, the most common mode of GPR data collection, however the design factors can be applied to other survey types. Information on the visualisation of processed data, as well as the advantages and disadvantages of GPR, is provided. Possible applications of GPR in geomorphological research are presented, along with a case study outlining how GPR can be used to measure peat thickness.}, language = {en}, journal = {Geomorphological Techniques}, author = {Robinson, Martin and Bristow, Charlie and McKinley, Jennifer and Ruffell, Alastair}, year = {2013}, pages = {26}, file = {Robinson et al. - 2013 - 1.5.5. Ground Penetrating Radar.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\QHDGW4F9\\Robinson et al. - 2013 - 1.5.5. Ground Penetrating Radar.pdf:application/pdf}, } @book{hubbard_environmental_2005, title = {Environmental and {Agricultural} {Applications} of {GPR}}, volume = {2005}, isbn = {978-90-809701-1-3}, abstract = {It is widely recognized that natural heterogeneity and the large spatial variability of hydraulic parameters control the spread of contaminants and water in the subsurface. Similarly, hydrological and biogeochemical processes are variable over a wide range of spatial scales. The inadequacy of conventional (wellbore) approaches for characterizing or monitoring the parameters and processes at over large enough areas yet with high enough resolution hinders our ability to optimally manage our natural water resources. GPR methods hold promise for improved and minimally invasive characterization and monitoring of the subsurface. This paper will review several case studies where we have successfully used GPR for a variety of environmental and precision agricultural investigations.}, author = {Hubbard, Susan and Chen, Jinsong and Williams, Ken and Rubin, Yoram and Peterson, J.}, month = feb, year = {2005}, doi = {10.1109/AGPR.2005.1487843}, note = {Journal Abbreviation: Proceedings of the 3rd International Workshop on Advanced Ground Penetrating Radar, IWAGPR 2005 Pages: 49 Publication Title: Proceedings of the 3rd International Workshop on Advanced Ground Penetrating Radar, IWAGPR 2005}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\JV2CNZDS\\Hubbard et al. - 2005 - Environmental and Agricultural Applications of GPR.pdf:application/pdf}, } @misc{noauthor_home_nodate, title = {Home}, url = {https://helixfarm.co.uk/}, abstract = {...}, language = {en-GB}, urldate = {2021-12-08}, journal = {Helix}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\M26ZXCYM\\helixfarm.co.uk.html:text/html}, } @article{filzwieser_towards_2020, title = {Towards an {Online} {Database} for {Archaeological} {Landscapes}. {Using} the {Web} {Based}, {Open} {Source} {Software} {OpenAtlas} for the {Acquisition}, {Analysis} and {Dissemination} of {Archaeological} and {Historical} {Data} on a {Landscape} {Basis}}, volume = {3}, doi = {10.3390/heritage3040077}, abstract = {In this paper, we present the web-based, open source software OpenAtlas, which uses the International Council of Museums' Conceptual Reference Model (CIDOC CRM), and its possible future potential for the acquisition, analysis and dissemination of a wide range of archaeological and historical data on a landscape basis. To this end, we will first introduce the ongoing research project The Anthropological and Archaeological Database of Sepultures (THANADOS), built upon OpenAtlas, as well as its data model and interactive web interface/presentation frontend. Subsequently, the article will then discuss the possible extension of this database of early medieval cemeteries with regard to the integration of further archaeological structures (e.g., medieval settlements, fortifications, field systems and traffic routes) and other data, such as historical maps, aerial photographs and airborne laser scanning data. Finally, the paper will conclude with the general added value for future research projects by such a collaborative and web-based approach.}, journal = {Heritage}, author = {Filzwieser, Roland and Eichert, Stefan}, month = nov, year = {2020}, pages = {1385--1401}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\HWT7NS3J\\Filzwieser and Eichert - 2020 - Towards an Online Database for Archaeological Land.pdf:application/pdf}, } @incollection{nawar_chapter_2017, title = {Chapter {Four} - {Delineation} of {Soil} {Management} {Zones} for {Variable}-{Rate} {Fertilization}: {A} {Review}}, volume = {143}, shorttitle = {Chapter {Four} - {Delineation} of {Soil} {Management} {Zones} for {Variable}-{Rate} {Fertilization}}, url = {https://www.sciencedirect.com/science/article/pii/S0065211317300032}, abstract = {Different methods of management zone (MZ) delineation have been established over the past 2 decades based on approaches, which have been largely constrained by the available data collection methods that are often time consuming and expensive. This situation is being changed by recent advances in sensor technology, making a huge amount of data available. Advances in computing power make it possible to analyze and utilize this large amount of data. These current advances in technology are gradually turning MZ maps into commercially viable agricultural products for large-scale adoption. The aim of this paper is to provide a critical overview of MZ delineation approaches for precision agriculture applications, and to compare and contrast traditional with advanced sensing technologies for delineating MZs. This review illustrates how recent development in sensing technologies, geostatistical analysis, data fusion, and interpolation techniques have improved precision and reliability of MZ delineation, making it a viable strategy in commercial agriculture. Studies from the last decade showed that when MZ delineation techniques are used for variable-rate nutrient application, farm efficiency increased when this is compared to traditional uniform-rate application methods. This improved farm production efficiency is accompanied by a reduction in environmental impacts. Implementation of MZ therefore often provides financial and environmental benefits, and we can foresee an increase in the diffusion and application of precision agriculture techniques in the near future.}, language = {en}, urldate = {2021-12-09}, booktitle = {Advances in {Agronomy}}, publisher = {Academic Press}, author = {Nawar, Said and Corstanje, Ronald and Halcro, Graham and Mulla, David and Mouazen, Abdul M.}, editor = {Sparks, Donald L.}, month = jan, year = {2017}, doi = {10.1016/bs.agron.2017.01.003}, keywords = {Data fusion, Geostatistical analysis, Management zone delineation, Proximal sensors, Variable-rate application}, pages = {175--245}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\8AY33K8C\\S0065211317300032.html:text/html}, } @article{kaufmann_effect_2020, title = {Effect of fertilizers and irrigation on multi-configuration electromagnetic induction measurements}, volume = {36}, issn = {1475-2743}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/sum.12530}, doi = {10.1111/sum.12530}, abstract = {Electromagnetic induction (EMI) data are often used to investigate spatial and temporal patterns of soil texture, soil water content and soil salinity. We hypothesized that the EMI methodology might thus also offer potential to detect agricultural legacy effects originating from fertilizer application and irrigation of different fields. Therefore, we performed EMI measurements on two long-term field experiments (LTFE) at Thyrow near Berlin (Germany) that differed in agricultural management with regard to long-term irrigation in combination with mineral (NPK and lime) and organic amendments (straw and farmyard manure). Two different rigid-boom multi-coil EMI instruments were used to measure simultaneously the apparent electrical conductivity (ECa) over nine different depth ranges to study the entire soil profile from topsoil to deep subsoil. Additionally, soil samples were taken from the different treatments to ground-truth the measurements and disentangle the nutrient application or irrigation effects from natural soil heterogeneity. The soil samples indicated a rather homogenous soil and the correlation between soil parameters or states were not significant. However, the treatments showed significant differences in measured ECa values. In general, ECa values were largest on regularly irrigated as well as on mineral and organic fertilized plots, with regular irrigation exhibiting the largest impact on EMI records even though the last application was months before the EMI measurement. Overall, this study reveals that EMI data can support the classical in situ assessment of agricultural management effects within LTFE, while offering new potentials in detecting and understanding legacy effects of agricultural management on spatial soil properties at farm level.}, language = {en}, number = {1}, urldate = {2021-12-10}, journal = {Soil Use and Management}, author = {Kaufmann, Manuela S. and von Hebel, Christian and Weihermüller, Lutz and Baumecker, Michael and Döring, Thomas and Schweitzer, Kathlin and Hobley, Eleanor and Bauke, Sara L. and Amelung, Wulf and Vereecken, Harry and van der Kruk, Jan}, year = {2020}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/sum.12530}, keywords = {soil mapping, fertilizer, electrical conductivity, electromagnetic induction, irrigation}, pages = {104--116}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\RD42KSRC\\sum.html:text/html}, } @article{weihermueller_fertilization_2017, title = {Fertilization effects on the electrical conductivity measured by {EMI}, {ERT}, and {GPR}}, volume = {2017}, url = {https://ui.adsabs.harvard.edu/abs/2017AGUFMNS23A0001W}, abstract = {Near surface geophysics such as electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) are widely used for field characterization, to delineate soil units, and to estimate soil texture, bulk densities and/or soil water contents. Hereby, the measured soil apparent conductivity (ECa) is often used. Soil ECa is governed by horizontal and vertical changes in soil texture, mineralogy, soil water content, and temperature, and the single contributions are not easy to disentangle. Within single fields and between fields fertilization management may vary spatially, which holds especially for field trials. As a result, ECa might vary due to differences in electrolyte concentration and subsequent pore fluid conductivity, but secondary fertilization effects might also play a major role in ECa differences such as differences in soil water uptake by growing plants. To study the direct effect of mineral fertilization on ECa, a field experiment was performed on 21 bare soil plots each of a size of 9 m2, where 7 different fertilization treatments were established in triplicates. As mineral fertilizers, commercial calcium ammonium nitrate and potassium chloride were chosen and applied in dosages of 200, 400, and 2000 kg ha-1 N equivalent. Additionally, soil water, soil temperature, and EC were recorded in a pit at different depths using commercial sensors. Changes in ECa were measured every 10 days using EMI and monthly using GPR and ERT. Additionally, soil samples were monthly taken at all plots and nitrate, chloride, and potassium contents were measured in the lab. The poster will show the effect of ECa changes due to fertilization and corresponding leaching of the fertilized elements over time. The experimental results provide information of how fertilization is influencing ECa readings and how long the fertilizers are influencing ECa measurements with geophysical instruments. This study helps to overcome restricted interpretation of ECa measurements on managed agricultural soils.}, urldate = {2021-12-10}, author = {Weihermueller, L. and Kaufmann, M. and Steinberger, P. and Pätzold, S. and Vereecken, H. and Van Der Kruk, J.}, month = dec, year = {2017}, note = {Conference Name: AGU Fall Meeting Abstracts ADS Bibcode: 2017AGUFMNS23A0001W}, keywords = {0994 Instruments and techniques, 0999 General or miscellaneous, 1835 Hydrogeophysics, EXPLORATION GEOPHYSICS, HYDROLOGY}, pages = {NS23A--0001}, } @article{craddock_application_2014, title = {The {Application} of {Phosphate} {Analysis} to the {Location} and {Interpretation} of {Archaeological} {Sites}}, copyright = {© 1985 Taylor and Francis Group, LLC}, issn = {0066-5983}, url = {https://www.tandfonline.com/doi/abs/10.1080/00665983.1985.11021068}, abstract = {This paper describes the uses of phosphate analysis as a means of locating and interpreting archaeological sites based on ten years fieldwork principally in East Anglia. Practical details of the sa...}, language = {en}, urldate = {2021-12-13}, journal = {Archaeological Journal}, author = {Craddock, P. T. and Gurney, D. and Pryor, F. and Hughes, M. J.}, month = dec, year = {2014}, note = {Publisher: Routledge}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\B836EA4E\\00665983.1985.html:text/html}, } @article{provan_soil_1971, title = {Soil phosphate analysis as a tool in archaeology}, volume = {4}, issn = {0029-3652}, url = {https://doi.org/10.1080/00293652.1971.9965134}, doi = {10.1080/00293652.1971.9965134}, abstract = {The theory underlying the use of soil phosphate analysis in archaeology is discussed. After describing the field and laboratory methods used at Stavanger Museum, the method is illustrated by several examples. In all cases the results showed good agreement with the archaeological evidence, and generally provided useful supplementary information. The method may be used as a guide to the functions carried out in different parts of a site and to the intensity of occupation. Although no hidden sites were found in a reconnaissance survey, the results indicate that the method has considerable scope in locating sites in areas destined for town development, etc.}, number = {1}, urldate = {2021-12-13}, journal = {Norwegian Archaeological Review}, author = {Provan, Donald M. J.}, month = jan, year = {1971}, note = {Publisher: Routledge \_eprint: https://doi.org/10.1080/00293652.1971.9965134}, pages = {37--50}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\D8VZWTD4\\00293652.1971.html:text/html}, } @article{bakkevig_phosphate_1980, title = {Phosphate analysis in archaeology ‐ problems and recent progress}, volume = {13}, issn = {0029-3652}, url = {https://doi.org/10.1080/00293652.1980.9965334}, doi = {10.1080/00293652.1980.9965334}, abstract = {Ecological knowledge is important if phosphate analysis is to become a useful tool for the archaeologist. The author mentions variation in natural phosphate content, solifluction, drifting sand, iron pan, different land use, and the vegetation and climate as examples of factors which must be taken into consideration before sampling and discussion of the results. On this basis a critical evaluation is made of some papers dealing with phosphate analysis applied to archaeology. The author claims that a rapid field test can in many cases make the much more laborious laboratory procedure unnecessary, and gives examples of the use of the spot test from areas with summer farming, settlements from the Iron Age and Mesolithic Age, modern farming, and cattle tracks. A trained person can sample and analyse some hundred samples a day, and this compensates for the low accuracy of the spot test.}, number = {2}, urldate = {2021-12-13}, journal = {Norwegian Archaeological Review}, author = {Bakkevig, Sverre}, month = jan, year = {1980}, note = {Publisher: Routledge \_eprint: https://doi.org/10.1080/00293652.1980.9965334}, pages = {73--100}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\RNP7RTR8\\00293652.1980.html:text/html}, } @article{sjoberg_phosphate_1976, title = {Phosphate {Analysis} of {Anthropic} {Soils}}, volume = {3}, issn = {0093-4690}, url = {https://doi.org/10.1179/009346976791490493}, doi = {10.1179/009346976791490493}, abstract = {The use of phosphate analysis in archaeology is possible because past human occupation and activities increased the amount of soil phosphorus in the areas occupied. The accumulated phosphorus in archaeological deposits tends to remain constant through time and is measurable through soil sampling and chemical analysis, thereby providing archaeology with a valuable tool, applicable to a wide variety of research situations. Phosphate analysis is especially useful in surveying large areas to locate and delimit sites.}, number = {4}, urldate = {2021-12-13}, journal = {Journal of Field Archaeology}, author = {Sjöberg, Alf}, month = jan, year = {1976}, note = {Publisher: Routledge \_eprint: https://doi.org/10.1179/009346976791490493}, pages = {447--454}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\FIPYCBMV\\009346976791490493.html:text/html}, } @article{sjoberg_phosphate_1976-1, title = {Phosphate {Analysis} of {Anthropic} {Soils}}, volume = {3}, issn = {0093-4690}, url = {https://www.jstor.org/stable/529561}, doi = {10.2307/529561}, abstract = {The use of phosphate analysis in archaeology is possible because past human occupation and activities increased the amount of soil phosphorus in the areas occupied. The accumulated phosphorus in archaeological deposits tends to remain constant through time and is measurable through soil sampling and chemical analysis, thereby providing archaeology with a valuable tool, applicable to a wide variety of research situations. Phosphate analysis is especially useful in surveying large areas to locate and delimit sites.}, number = {4}, urldate = {2021-12-13}, journal = {Journal of Field Archaeology}, author = {Sjöberg, Alf}, year = {1976}, note = {Publisher: [Maney Publishing, Trustees of Boston University]}, pages = {447--454}, file = {Sjöberg - 1976 - Phosphate Analysis of Anthropic Soils.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\4K26ZURQ\\Sjöberg - 1976 - Phosphate Analysis of Anthropic Soils.pdf:application/pdf}, } @article{zlateva_applications_2018, title = {Applications of soil phosphate analysis for identification of activity areas at {Doschkere}, {SE} {Bulgaria}}, issn = {25732897}, abstract = {Human occupation enriches soils with phosphorus, which may provide a useful chemical tracer for site delineation in archaeological studies. In the present paper we use “spot-method” as well as extractible phosphorous soil content to estimate site boundaries and the activity areas at the region “Doschkere”, situated near Malko Tranovo, Chirpan, SE Bulgaria.}, language = {en}, journal = {Journal of Historical Archaeology \& Anthropological Sciences}, author = {Zlateva, Boika}, year = {2018}, file = {[No title found].pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\UKDXKA5G\\[No title found].pdf:application/pdf}, } @article{holliday_methods_2007, title = {Methods of soil {P} analysis in archaeology}, volume = {34}, doi = {10.1016/j.jas.2006.05.004}, abstract = {Phosphorus (P) is unique among the elements in being a sensitive and persistent indicator of human activity. It has long been of interest to archaeologists because of its potential to inform them about the presence of past human occupation and to offer clues regarding the type and intensity of human activity. A wide variety of methods have been developed in both soil science and in archaeology to extract and measure soil P, resulting in a tremendous amount of data and a wide array of interpretations, but also considerable confusion over appropriateness of methods and terminology. The primary purpose of this paper is to address these issues by clarifying soil P analyses. Anthropogenic additions of phosphorus to the soil come from human refuse and waste, burials, the products of animal husbandry in barns, pens, and on livestock paths, or intentional enrichment from soil fertilizer. Once added to the soil, phosphorus in its common form as phosphate is stable and generally immobile in soils. Soil P comes in many forms, organized for the purposes of this paper on the basis of extraction and measurement procedures as (1) extraction for available P (Pav); (2) portable field techniques (the spot test or ring test); (3) chemical digestion of a soil sample for total P (Ptot); (4) extractions of inorganic P (Pin) for fractionation studies and extractions to look at individual compounds of P; (5) measurements of organic P (Porg); and (6) extractions for total elemental analysis. To compare the suitability of various extractants as the “best” indicator of human input and activity we subjected samples from three very different archaeological sites (Lubbock Lake, TX; Hulburt Creek, IA; British Camp, WA) to four methods of soil P extraction: perchloric acid digestion (Ptot), sulfuric–nitric acid extraction Ptot), hydrochloric acid extraction after ignition (Pin), and citric acid extraction (Pav). Further, methods of measurement were compared via colorimetry vs. Inductively Coupled Plasma (ICP) spectrometry, and the two methods of supposed “total P” were both measured via ICP. In general, the stronger extractants yielded more soil P, but the result are not clear-cut. Likely variables include the intensity of occupation, nature of the parent material, and postdepositional weathering (e.g., the addition of dust).}, journal = {Journal of Archaeological Science}, author = {Holliday, Vance and Gartner, William}, month = feb, year = {2007}, pages = {301--333}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\3AFK74GK\\Holliday and Gartner - 2007 - Methods of soil P analysis in archaeology.pdf:application/pdf}, } @article{eidt_detection_1977, title = {Detection and {Examination} of {Anthrosols} by {Phosphate} {Analysis}}, volume = {197}, url = {https://www.science.org/doi/10.1126/science.197.4311.1327}, doi = {10.1126/science.197.4311.1327}, number = {4311}, urldate = {2021-12-13}, journal = {Science}, author = {Eidt, Robert C.}, month = sep, year = {1977}, note = {Publisher: American Association for the Advancement of Science}, pages = {1327--1333}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\WNTQQX4I\\Eidt - 1977 - Detection and Examination of Anthrosols by Phospha.pdf:application/pdf}, } @article{mcmichael_sparse_2012, title = {Sparse {Pre}-{Columbian} {Human} {Habitation} in {Western} {Amazonia}}, volume = {336}, url = {https://www.science.org/doi/10.1126/science.1219982}, doi = {10.1126/science.1219982}, number = {6087}, urldate = {2021-12-13}, journal = {Science}, author = {McMichael, C. H. and Piperno, D. R. and Bush, M. B. and Silman, M. R. and Zimmerman, A. R. and Raczka, M. F. and Lobato, L. C.}, month = jun, year = {2012}, note = {Publisher: American Association for the Advancement of Science}, pages = {1429--1431}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\PZWK85UD\\McMichael et al. - 2012 - Sparse Pre-Columbian Human Habitation in Western A.pdf:application/pdf}, } @incollection{holliday_anthrosols_2017, address = {Dordrecht}, title = {Anthrosols}, isbn = {978-1-4020-4409-0}, url = {https://doi.org/10.1007/978-1-4020-4409-0_130}, language = {en}, urldate = {2021-12-13}, booktitle = {Encyclopedia of {Geoarchaeology}}, publisher = {Springer Netherlands}, author = {Holliday, Vance T.}, editor = {Gilbert, Allan S.}, year = {2017}, doi = {10.1007/978-1-4020-4409-0_130}, pages = {24--27}, file = {Springer Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\FZ6CBHQU\\Holliday - 2017 - Anthrosols.pdf:application/pdf}, } @incollection{kolb_analysis_2017, address = {Dordrecht}, title = {Analysis of {Carbon}, {Nitrogen}, {pH}, {Phosphorus}, and {Carbonates} as {Tools} in {Geoarchaeological} {Research}}, isbn = {978-1-4020-4409-0}, url = {https://doi.org/10.1007/978-1-4020-4409-0_11}, language = {en}, urldate = {2021-12-13}, booktitle = {Encyclopedia of {Geoarchaeology}}, publisher = {Springer Netherlands}, author = {Kolb, Michael F.}, editor = {Gilbert, Allan S.}, year = {2017}, doi = {10.1007/978-1-4020-4409-0_11}, pages = {15--24}, file = {Springer Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\9PYEE7P5\\Kolb - 2017 - Analysis of Carbon, Nitrogen, pH, Phosphorus, and .pdf:application/pdf}, } @article{roos_phosphates_2012, title = {Phosphates, plowzones, and plazas: a minimally invasive approach to settlement structure of plowed village sites}, volume = {39}, issn = {0305-4403}, shorttitle = {Phosphates, plowzones, and plazas}, url = {https://www.sciencedirect.com/science/article/pii/S0305440311002317}, doi = {10.1016/j.jas.2011.06.033}, abstract = {Inferences about settlement structure play an important role in explanations of social and political change in Late Prehistoric eastern North America, but ethical and logistical challenges posed by extensive horizontal excavations mean that archaeologists must develop low cost, minimally invasive methods for investigating key properties of village structure. There are two important components of most villages in the region: 1) the peripheral distribution of middens; and 2) the size and location of formal communal spaces or plazas, each of which leaves traces in soil chemistry. In shallowly buried, plowed village sites where artifacts have been physically displaced, the chemical signature of middens may be more resistant to disturbance and provide an enduring signature of ancient settlement structure. We conducted a systematic soil phosphorus survey at the Reinhardt Site (33PI880) in central Ohio, the primary occupation of which occurred during the Late Prehistoric Period (ca. AD 1200–1450), to test for the presence and approximate size of a central plaza and the shape and distribution of peripheral midden deposits. Soil samples from the modern plowzone (N=131) were analyzed for Mehlich II extractable phosphorus using molybdate colorimetry. The interpolated phosphorus distributions indicate a clear ring midden approximately 90m across with an internal plaza that is roughly 30m×40m. Artifact distributions from a shovel test pit survey and interpolations of plowzone magnetic susceptibility measurements identify the location of the village but are ambiguous with regards to village size and do not clearly distinguish the central plaza. Our results suggest that systematic surveys of soil phosphorus are a rapid, minimally invasive, and inexpensive method for generating data on the size and shape of villages and their plazas.}, language = {en}, number = {1}, urldate = {2021-12-13}, journal = {Journal of Archaeological Science}, author = {Roos, Christopher I. and Nolan, Kevin C.}, month = jan, year = {2012}, keywords = {Fort Ancient, Middens, Phosphates, Plazas, Plowzone, Site structure, Soil chemistry}, pages = {23--32}, } @article{crowther_magnetic_1995, title = {Magnetic susceptibility: {Distinguishing} anthropogenic effects from the natural}, volume = {2}, issn = {1099-0763}, shorttitle = {Magnetic susceptibility}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/1099-0763%28199512%292%3A4%3C207%3A%3AAID-ARP6140020404%3E3.0.CO%3B2-%23}, doi = {10.1002/1099-0763(199512)2:4<207::AID-ARP6140020404>3.0.CO;2-#}, abstract = {Two possible approaches to separating anthropogenic from natural (geological and pedogenic) causes of variations in magnetic susceptibility are examined, the first using χmax and fractional conversion data, and the second based on the relationship between topsoil and subsoil magnetic susceptibility. Results presented from three contrasted sites in the UK suggest that the first approach, used in conjunction with stepwise multiple regression analysis, has considerable potential and should be incorporated routinely in magnetic susceptibility surveys. A recommended sampling and analytical strategy is suggested for fractional conversion work. The second approach is applicable only under restricted site and soil conditions, and has limited potential when used independently of fractional conversion studies.}, language = {en}, number = {4}, urldate = {2021-12-13}, journal = {Archaeological Prospection}, author = {Crowther, J. and Barker, P.}, year = {1995}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/1099-0763\%28199512\%292\%3A4\%3C207\%3A\%3AAID-ARP6140020404\%3E3.0.CO\%3B2-\%23}, keywords = {fractional conversion, magnetic susceptibility surveys, subsoils, topsoils}, pages = {207--215}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\38BJ2H2X\\1099-0763(199512)24207AID-ARP61400204043.0.html:text/html}, } @incollection{zhang_sensing_2021, address = {Cham}, series = {Women in {Engineering} and {Science}}, title = {Sensing {Technologies} and {Automation} for {Precision} {Agriculture}}, isbn = {978-3-030-49244-1}, url = {https://doi.org/10.1007/978-3-030-49244-1_2}, abstract = {This chapter begins by introducing the concept of precision agriculture and the impact of new technologies on the development and deployment of precision agriculture technologies. It then extensively reviews the sensing technologies commonly used in precision agriculture applications for crop, root, and soil monitoring. The chapter also reviewed platforms developed to implement field sensing tasks, including ground-based static platforms, ground-based mobile platforms, and aerial-based platforms. Two case studies using precision agriculture sensing technologies are finally presented.}, language = {en}, urldate = {2021-12-16}, booktitle = {Women in {Precision} {Agriculture}: {Technological} breakthroughs, {Challenges} and {Aspirations} for a {Prosperous} and {Sustainable} {Future}}, publisher = {Springer International Publishing}, author = {Zhang, Man and Wang, Ning and Chen, Liping}, editor = {Hamrita, Takoi Khemais}, year = {2021}, doi = {10.1007/978-3-030-49244-1_2}, keywords = {Crop phenotyping, Crop sensing, Root sensing, Soil sensing, Wireless sensor network}, pages = {35--54}, file = {Springer Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\DH8I35RP\\Zhang et al. - 2021 - Sensing Technologies and Automation for Precision .pdf:application/pdf}, } @article{aspinall_twenty_nodate, title = {Twenty five years of archaeological prospection}, abstract = {Much of the basic instrumentation in current use in archaeological geophysics had already been developed by 1972. The next fifteen years were a period of consolidation and adaptation for general use. The last ten years, up to 1997, have seen the introduction of new methods of field investigation, such as ground-penetrating radar and other electromagnetic methods. In Britain, partly as a result of legislation on land utilisation, there has been an explosion of archaeological interest in geophysical survey. The improvements in instrumentation have been paralleled by developments in data handling, presentation and interpretation. The problems of the 1970s were mainly concerned with the visualisation of data, allowing only minimal interpretation. In the 1980s, as increasing computer power became available, methods of data enhancement were introduced. In recent years attention has been focused on reconstructing the physical objects which give rise to the observed data, only a short step from direct archaeological interpretation.The future prospects are towards the interlinked development of instrumentation and interpretative methodology.}, language = {en}, author = {Aspinall, A and Haigh, J G B}, pages = {6}, file = {Aspinall and Haigh - Twenty five years of archaeological prospection.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\CZVJ9V3P\\Aspinall and Haigh - Twenty five years of archaeological prospection.pdf:application/pdf}, } @misc{noauthor_twenty_nodate, title = {Twenty {Five} {Years} of {Archaeological} {Prospection} - {CAA} {Online} {Proceedings}}, url = {https://proceedings.caaconference.org/paper/04_aspinall_haigh_caa_1997/}, language = {en-US}, urldate = {2022-01-05}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\95LLJPNL\\04_aspinall_haigh_caa_1997.html:text/html}, } @article{marino_detection_2019, title = {Detection of {Spatial} and {Temporal} {Variability} of {Wheat} {Cultivars} by {High}-{Resolution} {Vegetation} {Indices}}, volume = {9}, copyright = {http://creativecommons.org/licenses/by/3.0/}, url = {https://www.mdpi.com/2073-4395/9/5/226}, doi = {10.3390/agronomy9050226}, abstract = {An on-farm research study was carried out on two small-plots cultivated with two cultivars of durum wheat (Odisseo and Ariosto). The paper presents a theoretical approach for investigating frequency vegetation indices (VIs) in different areas of the experimental plot for early detection of agronomic spatial variability. Four flights were carried out with an unmanned aerial vehicle (UAV) to calculate high-resolution normalized difference vegetation index (NDVI) and optimized soil-adjusted vegetation index (OSAVI) images. Ground agronomic data (biomass, leaf area index (LAI), spikes, plant height, and yield) have been linked to the vegetation indices (VIs) at different growth stages. Regression coefficients of all samplings data were highly significant for both the cultivars and VIs at anthesis and tillering stage. At harvest, the whole plot (W) data were analyzed and compared with two sub-areas characterized by high agronomic performance (H) yield 20\% higher than the whole plot, and low performances (L), about 20\% lower of yield related to the whole plot). The whole plot and two sub-areas were analyzed backward in time comparing the VIs frequency curves. At anthesis, more than 75\% of the surface of H sub-areas showed a VIs value higher than the L sub-plot. The differences were evident also at the tillering and seedling stages, when the 75\% (third percentile) of VIs H data was over the 50\% (second percentile) of the W curve and over the 25\% (first percentile) of L sub-plot. The use of high-resolution images for analyzing the frequency value of VIs in different areas can be a useful approach for the detection of agronomic constraints for precision agriculture purposes.}, language = {en}, number = {5}, urldate = {2022-01-09}, journal = {Agronomy}, author = {Marino, Stefano and Alvino, Arturo}, month = may, year = {2019}, note = {Number: 5 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {UAV, precision agriculture, vegetation indices, cultivars, relative frequencies, yield}, pages = {226}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\4Q8HW6RG\\Marino and Alvino - 2019 - Detection of Spatial and Temporal Variability of W.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\IIWG92KJ\\htm.html:text/html}, } @article{cusworth_using_2021, title = {Using the ‘good farmer’ concept to explore agricultural attitudes to the provision of public goods. {A} case study of participants in an {English} agri-environment scheme}, volume = {38}, issn = {1572-8366}, url = {https://doi.org/10.1007/s10460-021-10215-z}, doi = {10.1007/s10460-021-10215-z}, abstract = {Across the European Union, the receipt of agricultural subsidisation is increasingly being predicated on the delivery of public goods. In the English context, in particular, these changes can be seen in the redirection of money to the new Environmental Land Management scheme. Such shifts reflect the changed expectations that society is placing on agriculture—from something that provides one good (food) to something that supplies many (food, access to green spaces, healthy rural environment, flood resilience, reduced greenhouse gas emissions). Whilst the reasons behind the changes are well documented, understanding how these shifts are being experienced by the managers expected to deliver on these new expectations is less well understood. Bourdieu’s social theory and the good farmer concept are used to attend to this blind spot, and to provide timely insight as the country progresses along its public goods subsidy transition. Evidence from 65 interviews with 40 different interviewees (25 of whom gave a repeat interview) show a general willingness towards the transition to a public goods model of subsidisation. The optimisation and efficiency that has historically characterised the productivist identity is colouring the way managers are approaching the delivery of public goods. Ideas of land sparing and land sharing (and the farming preference for the former over the latter) are used to help understand these new social and attitudinal realities. The policy implications of these findings are discussed, with reference to the new scheme’s ‘priority themes’.}, language = {en}, number = {4}, urldate = {2022-01-09}, journal = {Agriculture and Human Values}, author = {Cusworth, George and Dodsworth, Jennifer}, month = dec, year = {2021}, pages = {929--941}, file = {Springer Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\REEEK47M\\Cusworth and Dodsworth - 2021 - Using the ‘good farmer’ concept to explore agricul.pdf:application/pdf}, } @misc{noauthor_what_nodate, title = {What is {SHINE}? - {Historic} {Environment} {Farm} {Environment} {Record} ({HEFER}) {Portal}}, url = {https://www.myshinedata.org.uk/what-is-shine-1}, urldate = {2022-01-17}, file = {What is SHINE? - Historic Environment Farm Environment Record (HEFER) Portal:C\:\\Users\\Edify 01\\Zotero\\storage\\L7TTQIET\\what-is-shine-1.html:text/html}, } @article{baggaley_soil_2020, title = {Soil risk maps – {Interpreting} soils data for policy makers, agencies and industry}, volume = {36}, issn = {1475-2743}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/sum.12541}, doi = {10.1111/sum.12541}, abstract = {Surface runoff, erosion, compaction and the leaching of potential pollutants from land can degrade the soil resource and damage the water environment, reducing crop yields, causing loss of valuable nutrients and organic matter, together with increasing flood risk. Increasingly, it is recognized that scientific information must be translated into practical tools to change practices and protect the soil and water resource. Working alongside agencies in Scotland, we applied a suite of simple, transparent, rule-based models to identify areas most at risk of exporting sediment and pollutants that may degrade water quality based on field-scale (1:25,000) soil maps. The maps have been used by Scottish Environment Protection Agency, Scottish Water and Scottish Government to assess soil risks to waters from field to regional scale. The work brought scientists together with policy makers, agencies and the water industry to pool their knowledge to apply these practical tools for decision-making. It highlights the need to apply existing knowledge to answer salient questions. All three examples described show that providing the right type of information, which is based on fundamental soils data, can directly influence the implementation of policies, investment and monitoring decisions and provide evidence in support of government. However, this requires both researchers and agency scientists to develop skills as knowledge brokers and to normalize the use of soil data in everyday agency settings.}, language = {en}, number = {1}, urldate = {2022-01-18}, journal = {Soil Use and Management}, author = {Baggaley, Nikki and Lilly, Allan and Blackstock, Kirsty and Dobbie, Karen and Carson, Adam and Leith, Fraser}, year = {2020}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/sum.12541}, keywords = {policy, mapping, agencies, soil risks}, pages = {19--26}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\B85VEZEL\\sum.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\6MPB824L\\Baggaley et al. - 2020 - Soil risk maps – Interpreting soils data for polic.pdf:application/pdf}, } @article{campbell_are_2017, title = {Are existing soils data meeting the needs of stakeholders in {Europe}? {An} analysis of practical use from policy to field}, volume = {69}, issn = {0264-8377}, shorttitle = {Are existing soils data meeting the needs of stakeholders in {Europe}?}, url = {https://www.sciencedirect.com/science/article/pii/S0264837716312467}, doi = {10.1016/j.landusepol.2017.09.016}, abstract = {Soils form a major component of the natural system and their functions underpin many key ecosystem goods and services. The fundamental importance of soils in the environment means that many different organisations and stakeholders make extensive use of soils data and information in their everyday working practices. For many reasons, stakeholders are not always aware that they are reliant upon soil data and information to support their activities. Various reviews of stakeholder needs and how soil information could be improved have been carried out in recent years. However, to date, there has been little consideration of user needs from a non-expert perspective. The aim of this study was to explore the use of explicit and hidden soil information in different organisations across Europe and gain a better understanding of improvements needed in soil data and information to assist in practical use by non-expert stakeholders. An on-line questionnaire was used to investigate different uses of soils data and information with 310 responses obtained from 77 organisations across Europe. Results illustrate the widespread use of soil data and information across diverse organisations within Europe, particularly spatial products and soil functional assessments and tools. A wide range of improvements were expressed with a prevalence for finer scale resolution, trends over time, future scenarios, improved accuracy, non-technical supporting information and better capacity to use GIS. An underlying message is that existing legacy soils data need to be supplemented by new up-to-date data to meet stakeholder needs and information gaps.}, language = {en}, urldate = {2022-01-19}, journal = {Land Use Policy}, author = {Campbell, G. A and Lilly, A and Corstanje, R. and Mayr, T. R. and Black, H. I. J}, month = dec, year = {2017}, keywords = {Data, Soil functions, Soils, Improvements, Non-expert, Questionnaire, Stakeholders}, pages = {211--223}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\CX8KGTBP\\S0264837716312467.html:text/html;Submitted Version:C\:\\Users\\Edify 01\\Zotero\\storage\\4E8ZFFH3\\Campbell et al. - 2017 - Are existing soils data meeting the needs of stake.pdf:application/pdf}, } @incollection{zhang_digital_2016, address = {Singapore}, series = {Springer {Environmental} {Science} and {Engineering}}, title = {Digital {Soil} {Mapping} {Across} {Paradigms}, {Scales}, and {Boundaries}: {A} {Review}}, isbn = {978-981-10-0415-5}, shorttitle = {Digital {Soil} {Mapping} {Across} {Paradigms}, {Scales}, and {Boundaries}}, url = {https://doi.org/10.1007/978-981-10-0415-5_1}, abstract = {Accurate spatial soil information is urgently needed for dealing with the global issues such as agricultural production, environmental pollution, food security, water security, and human health. This need has been motivating the development of digital soil mapping. We reviewed recent advances in digital soil mapping with respect to paradigms, scales, and boundaries, with the intent to improve our understanding on current status of soil mapping. Some important challenges thus research opportunities emerged recently were then outlined, such as 3D digital mapping of the soil properties beyond soil organic matter, soil mapping in areas with intensive human activities, and multi-source soil data integration for soil mapping.}, language = {en}, urldate = {2022-01-19}, booktitle = {Digital {Soil} {Mapping} {Across} {Paradigms}, {Scales} and {Boundaries}}, publisher = {Springer}, author = {Zhang, Gan-Lin and Liu, Feng and Song, Xiao-Dong and Zhao, Yu-Guo}, editor = {Zhang, Gan-Lin and Brus, Dick and Liu, Feng and Song, Xiao-Dong and Lagacherie, Philippe}, year = {2016}, doi = {10.1007/978-981-10-0415-5_1}, keywords = {Digital Soil, Soil Data, Soil Mapping, Soil Organic Carbon, Soil Organic Carbon Stock}, pages = {3--10}, file = {Springer Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\UWX5KU32\\Zhang et al. - 2016 - Digital Soil Mapping Across Paradigms, Scales, and.pdf:application/pdf}, } @article{lauer_organic_2014, title = {Organic {Fertilization} and {Sufficient} {Nutrient} {Status} in {Prehistoric} {Agriculture}? – {Indications} from {Multi}-{Proxy} {Analyses} of {Archaeological} {Topsoil} {Relicts}}, volume = {9}, issn = {1932-6203}, shorttitle = {Organic {Fertilization} and {Sufficient} {Nutrient} {Status} in {Prehistoric} {Agriculture}?}, url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0106244}, doi = {10.1371/journal.pone.0106244}, abstract = {Neolithic and Bronze Age topsoil relicts revealed enhanced extractable phosphorus (P) and plant available inorganic P fractions, thus raising the question whether there was targeted soil amelioration in prehistoric times. This study aimed (i) at assessing the overall nutrient status and the soil organic matter content of these arable topsoil relicts, and (ii) at tracing ancient soil fertilizing practices by respective stable isotope and biomarker analyses. Prehistoric arable topsoils were preserved in archaeological pit fillings, whereas adjacent subsoils served as controls. One Early Weichselian humic zone represented the soil status before the introduction of agriculture. Recent topsoils served as an additional reference. The applied multi-proxy approach comprised total P and micronutrient contents, stable N isotope ratios, amino acid, steroid, and black carbon analyses as well as soil color measurements. Total contents of P and selected micronutrients (I, Cu, Mn, Mo, Se, Zn) of the arable soil relicts were above the limits for which nutrient deficiencies could be assumed. All pit fillings exhibited elevated δ15N values close to those of recent topsoils (δ15N{\textgreater}6 to 7‰), giving first hints for prehistoric organic N-input. Ancient legume cultivation as a potential source for N input could not be verified by means of amino acid analysis. In contrast, bile acids as markers for faecal input exhibited larger concentrations in the pit fillings compared with the reference and control soils indicating faeces (i.e. manure) input to Neolithic arable topsoils. Also black carbon contents were elevated, amounting up to 38\% of soil organic carbon, therewith explaining the dark soil color in the pit fillings and pointing to inputs of burned biomass. The combination of different geochemical analyses revealed a sufficient nutrient status of prehistoric arable soils, as well as signs of amelioration (inputs of organic material like charcoal and faeces-containing manure).}, language = {en}, number = {9}, urldate = {2022-01-23}, journal = {PLOS ONE}, author = {Lauer, Franziska and Prost, Katharina and Gerlach, Renate and Pätzold, Stefan and Wolf, Mareike and Urmersbach, Sarah and Lehndorff, Eva and Eckmeier, Eileen and Amelung, Wulf}, month = sep, year = {2014}, note = {Publisher: Public Library of Science}, keywords = {Archaeology, Agricultural soil science, Bile, Legumes, Neolithic period, Paleopedology, Steroids, Sterols}, pages = {e106244}, file = {Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\7LXZBXJ3\\Lauer et al. - 2014 - Organic Fertilization and Sufficient Nutrient Stat.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\74EJP282\\article.html:text/html}, } @misc{noauthor_sustainable_nodate-1, title = {Sustainable {Crop} {Production} - {Frontier} {Agriculture}}, url = {https://www.frontierag.co.uk/crop-production/sustainable-crop-production}, urldate = {2022-01-26}, file = {Sustainable Crop Production - Frontier Agriculture:C\:\\Users\\Edify 01\\Zotero\\storage\\V8DEDAGV\\sustainable-crop-production.html:text/html}, } @misc{noauthor_making_nodate, title = {Making the {Sustainable} {Farming} {Incentive} work for your farm: {Crop} production and environmental management don’t need to be competitive}, shorttitle = {Making the {Sustainable} {Farming} {Incentive} work for your farm}, url = {https://www.frontierag.co.uk/blog/making-the-sustainable-farming-incentive-work-for-your-farm-crop-production-and-environmental-management-don-t-need-to-be-competitive}, abstract = {​At the beginning of December the government released further detail on the Sustainable Farming Incentive (SFI) and how the widescale roll-out to all growers will work in 2022.Before we look further into the options available to growers later in the blog, it is worth emphasising from the start that the SFI offers a real opportunity for growers to a...}, language = {en-gb}, urldate = {2022-01-26}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\XWDECUGS\\making-the-sustainable-farming-incentive-work-for-your-farm-crop-production-and-environmental-m.html:text/html}, } @misc{noauthor_issue_nodate, title = {Issue 58. {Digital} {Archiving} in {Archaeology}: {The} {State} of the {Art}}, shorttitle = {Issue 58. {Digital} {Archiving} in {Archaeology}}, url = {https://intarch.ac.uk/journal/issue58/index.html}, abstract = {Issue 58. Digital Archiving in Archaeology: The State of the Art}, language = {en}, urldate = {2022-02-02}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\JWI9CU79\\issue58.html:text/html}, } @article{noauthor_nature-based_nodate, title = {Nature-based solutions: rhetoric or reality? - {The} potential contribution of nature-based solutions to net zero in the {UK}}, abstract = {The term “nature-based solutions” is used to mean working with the grain of nature to achieve a range of benefits, including enhanced biodiversity, flood alleviation, better livelihoods for local communities, and contributing to greenhouse gas reductions, either by storing carbon or by preventing its release. Our focus in this report is on the role of nature-based solutions in reducing carbon emissions and sequestering carbon, as part of the Government’s plan to achieve net zero emissions of greenhouse gases by 2050.}, language = {en}, pages = {82}, file = {Nature-based solutions rhetoric or reality - The.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\KJX5BR6C\\Nature-based solutions rhetoric or reality - The.pdf:application/pdf}, } @article{noauthor_nature-based_nodate-1, title = {Nature-based solutions: rhetoric or reality? - {The} potential contribution of nature-based solutions to net zero in the {UK}}, abstract = {The term “nature-based solutions” is used to mean working with the grain of nature to achieve a range of benefits, including enhanced biodiversity, flood alleviation, better livelihoods for local communities, and contributing to greenhouse gas reductions, either by storing carbon or by preventing its release. Our focus in this report is on the role of nature-based solutions in reducing carbon emissions and sequestering carbon, as part of the Government’s plan to achieve net zero emissions of greenhouse gases by 2050.}, language = {en}, pages = {82}, file = {Nature-based solutions rhetoric or reality - The.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\RH4BQ2LY\\Nature-based solutions rhetoric or reality - The.pdf:application/pdf}, } @article{cannell_delineating_2018, title = {Delineating an {Unmarked} {Graveyard} by {High}-{Resolution} {GPR} and {pXRF} {Prospection}: {The} {Medieval} {Church} {Site} of {Furulund} in {Norway}}, volume = {1}, copyright = {Authors who publish with this journal agree to the following terms: Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access ). All third-party images reproduced on this journal are shared under Educational Fair Use. For more information on Educational Fair Use , please see this useful checklist prepared by Columbia University Libraries . All copyright of third-party content posted here for research purposes belongs to its original owners. Unless otherwise stated all references to characters and comic art presented on this journal are ©, ® or ™ of their respective owners. No challenge to any owner’s rights is intended or should be inferred.}, issn = {2514-8362}, shorttitle = {Delineating an {Unmarked} {Graveyard} by {High}-{Resolution} {GPR} and {pXRF} {Prospection}}, url = {http://journal.caa-international.org/articles/10.5334/jcaa.9/}, doi = {10.5334/jcaa.9}, abstract = {The lack of accurate locational information on abandoned medieval and later graveyards constitutes a considerable challenge to national and local bodies tasked with their protection and management. These sites are increasingly in danger of destruction due to climatic changes, intensified farming schemes or developmental encroachment, and there is an ever-growing need to develop nonintrusive methods to ensure their detection and delineation so that they can be protected. In 2014, the Norwegian Directorate for Cultural Heritage received alarming information on the worsening state of the medieval church site at Furulund, in the southeast of the country. A successful, cost-effective campaign using high-resolution, large-scale georadar surveys in conjunction with geochemical mapping using portable XRF was undertaken in order to delineate and characterise the graveyard so that remedial actions could be initiated and the graveyard protected. Whilst the interpretations are unique to the site, the method combination has the potential to effectively resolve detection and protection of other, similar sites in Norway and beyond.}, language = {eng}, number = {1}, urldate = {2022-02-10}, journal = {Journal of Computer Applications in Archaeology}, author = {Cannell, Rebecca J. S. and Gustavsen, Lars and Kristiansen, Monica and Nau, Erich}, month = mar, year = {2018}, note = {Number: 1 Publisher: Ubiquity Press}, keywords = {ground-penetrating radar, graveyard, Norway, portable XRF}, pages = {1--18}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\ZKDLYII2\\jcaa.9.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\E6WWYCIR\\Cannell et al. - 2018 - Delineating an Unmarked Graveyard by High-Resoluti.pdf:application/pdf}, } @article{williams_mapping_2021, title = {Mapping an archaeological site: {Interpreting} portable {X}-ray fluorescence ({pXRF}) soil analysis at {Boroughgate}, {Skelton}, {UK}}, volume = {38}, issn = {2352-409X}, shorttitle = {Mapping an archaeological site}, url = {https://www.sciencedirect.com/science/article/pii/S2352409X21003217}, doi = {10.1016/j.jasrep.2021.103109}, abstract = {Integrating chemical soil analysis with visual inspection of an archaeological excavation may enhance our knowledge of anthropogenic activities from past populations. Elemental distribution of excavated soil from a medieval longhouse at Boroughgate, Skelton, UK was investigated. Soil was extracted from the surface of a longhouse and nearby ditch, analysed using portable X-Ray fluorescence (pXRF), and data were processed into elemental heat maps. The distribution and archaeological associations of magnesium, aluminium, phosphorus, sulphur, potassium, calcium, manganese, iron and zinc were assessed. Elemental concentrations were combined to produce a simplified summary that aided the interpretation of the site, including the delimitation of internal and external zones, clean and refuse zones, and potential animal occupation or waste areas. The application of pXRF was successful at visualising elemental distribution of an excavation to explore the anthropogenic associations through interpretation heat maps.}, language = {en}, urldate = {2022-02-10}, journal = {Journal of Archaeological Science: Reports}, author = {Williams, Rhys and Errickson, David and Taylor, Gillian}, month = aug, year = {2021}, keywords = {Mapping, Activity zones, Elemental analysis, Portable X-ray fluorescence, Soil analysis}, pages = {103109}, file = {Williams et al. - 2021 - Mapping an archaeological site Interpreting porta.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\7F8C66W6\\Williams et al. - 2021 - Mapping an archaeological site Interpreting porta.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\PYLJUL3K\\S2352409X21003217.html:text/html}, } @article{booth_geochemical_2017, title = {Geochemical insight during archaeological geophysical exploration through in situ {X}-ray fluorescence spectrometry}, volume = {24}, issn = {1099-0763}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/arp.1575}, doi = {10.1002/arp.1575}, abstract = {Geophysical techniques are widely applied in archaeological exploration, providing rapid and non-invasive site appraisal. Geochemical analyses contribute significantly in archaeometry, but conventional laboratory apparatus requires that samples are removed from their in situ context. Recent advances in field-portable apparatus facilitate in situ geochemical analysis, and this apparatus is deployed in this paper alongside conventional geophysical analysis to characterize the archaeological prospectivity of a site. The target is subsurface debris at the crash site of a World War II Mosquito aircraft. A 100 m long transect of magnetic, electromagnetic (EM) and in situ X-ray fluorescence (XRF) measurements was acquired in November 2014, with soil samples also collected for laboratory validation. A subset of XRF measurements was repeated in August 2015 alongside a targeted grid, 900 m2 in area, of magnetic gradiometry profiles. Built chiefly from wood, the Mosquito responds weakly in magnetic and EM data; magnetic gradient anomalies of ±10 nT/m are instead attributed to thermoremanence in a burnt layer at 0.2–0.4 m depth, produced by the impact fire following the crash. XRF spectrometry reveals co-located enrichments in copper (Cu) and zinc (Zn) ions (400\% and 200\%, respectively, above background). These metals are alloyed into brass, present in abundance in the ammunition on board the Mosquito. Records from the in situ XRF sampling compare well with laboratory validated data, although a bespoke calibration for the local soil type would improve the reliability of absolute geochemical concentrations. XRF responses vary significantly with ground conditions: the November 2014 acquisition was performed soon after ploughing at the site, potentially providing a fresh charge of metallic contaminants to the ground surface. Where the chemistry of a target is anomalous with respect to host soil and a source-to-surface transport mechanism is present, in situ XRF analysis offers improved understanding of a target compared to geophysical interpretation alone.}, language = {en}, number = {4}, urldate = {2022-02-10}, journal = {Archaeological Prospection}, author = {Booth, Adam D. and Vandeginste, Veerle and Pike, Dominic and Abbey, Russell and Clark, Roger A. and Green, Chris M. and Howland, Nathan}, year = {2017}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/arp.1575}, keywords = {magnetometry, conflict archaeology, geochemistry, geophysics, air crash, XRF spectrometry}, pages = {361--372}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\EVIUWNUK\\arp.html:text/html;Full Text PDF:C\:\\Users\\Edify 01\\Zotero\\storage\\KMS7ELUG\\Booth et al. - 2017 - Geochemical insight during archaeological geophysi.pdf:application/pdf}, } @misc{noauthor_geophysical_2019, title = {The {Geophysical} {Signatures} of {Soil} {Structure}}, url = {http://eos.org/editors-vox/the-geophysical-signatures-of-soil-structure}, abstract = {Geophysical methods may offer new opportunities for soil structure characterization over varied spatial and temporal scales.}, language = {en-US}, urldate = {2022-02-11}, journal = {Eos}, month = jan, year = {2019}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\RWE572BV\\the-geophysical-signatures-of-soil-structure.html:text/html}, } @article{galambosova_determining_2020, title = {Determining {Trafficked} {Areas} {Using} {Soil} {Electrical} {Conductivity} – {A} {Pilot} {Study}}, volume = {23}, issn = {1338-5267}, url = {https://www.sciendo.com/article/10.2478/ata-2020-0001}, doi = {10.2478/ata-2020-0001}, abstract = {Abstract Increase in machinery size and its random traffic at fields cause soil compaction resulting in damage of soil structure and degradation of soil functions. Nowadays, rapid methods to detect soil compaction at fields are of high interest, especially proximal sensing methods such as electrical conductivity measurements. The aim of this work was to investigate whether electromagnetic induction (EMI) could be used to determine trafficked areas in silty clay soil. Results of randomized block experiment showed a high significant difference ( p {\textless}0.01) in EMI data measured between compacted and non-compacted areas. EMI readings from compacted areas were, on average, 11\% (shallow range) and 9\% (deep range) higher than non-compacted areas, respectively. This difference was determined in both shallow and deep measuring ranges, indicating that the difference in soil compaction was detected in both topsoil and subsoil. Furthermore, the data was found to have a significant spatial variability, suggesting that, in order to detect the increase in EMI (which shows the increase in soil compaction), data within close surrounding area should be included in the analyses. Correlation coefficient of EMI and penetration resistance (average moisture content 32.5\% and 30.8\% for topsoil and subsoil) was found to be 0.66.}, language = {en}, number = {1}, urldate = {2022-02-11}, journal = {Acta Technologica Agriculturae}, author = {Galambošová, Jana and Macák, Miroslav and Rataj, Vladimír and Barát, Marek and Misiewicz, Paula}, month = mar, year = {2020}, pages = {1--6}, file = {Galambošová et al. - 2020 - Determining Trafficked Areas Using Soil Electrical.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\YBS2EGIM\\Galambošová et al. - 2020 - Determining Trafficked Areas Using Soil Electrical.pdf:application/pdf}, } @article{beamish_low_2011, title = {Low induction number, ground conductivity meters: {A} correction procedure in the absence of magnetic effects}, volume = {75}, issn = {0926-9851}, shorttitle = {Low induction number, ground conductivity meters}, url = {https://www.sciencedirect.com/science/article/pii/S0926985111001492}, doi = {10.1016/j.jappgeo.2011.07.005}, abstract = {Ground conductivity meters, comprising a variety of coil–coil configurations, are intended to operate within the limits provided by a low induction number (LIN), electromagnetic condition. They are now routinely used across a wide range of application areas and the measured apparent conductivity data may be spatially assembled and examined/correlated alongside information obtained from many other earth science, environmental, soil and land use assessments. The theoretical behaviour of the common systems is examined in relation to both the prevailing level of subsurface conductivity and the instrument elevation. It is demonstrated that, given the inherent high level of accuracy of modern instruments, the prevailing LIN condition may require operation in environments restricted to very low ({\textless}12 mS/m) conductivities. Beyond this limit, non-linear departures from the apparent conductivity that would be associated with a LIN condition occur and are a function of the coil configuration, the instrument height and the prevailing conductivity. Using both theory and experimental data, it is demonstrated that this has the potential to provide biased and spatially distorted measurements. A simple correction procedure that can be applied to the measured data obtained from any of the LIN instruments is developed. The correction procedure would, in the limit of a uniform subsurface, return the same (correct) conductivity, irrespective of the ground conductivity meter used, the prevailing conductivity or the measurement height.}, language = {en}, number = {2}, urldate = {2022-02-14}, journal = {Journal of Applied Geophysics}, author = {Beamish, David}, month = oct, year = {2011}, keywords = {Electromagnetic induction, Ground conductivity meter, Low induction number}, pages = {244--253}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\A3MF6KRK\\S0926985111001492.html:text/html;Accepted Version:C\:\\Users\\Edify 01\\Zotero\\storage\\A79P2H8A\\Beamish - 2011 - Low induction number, ground conductivity meters .pdf:application/pdf}, } @article{callegary_vertical_2007, title = {Vertical {Spatial} {Sensitivity} and {Exploration} {Depth} of {Low}-{Induction}-{Number} {Electromagnetic}-{Induction} {Instruments}}, volume = {6}, issn = {1539-1663}, url = {https://onlinelibrary.wiley.com/doi/abs/10.2136/vzj2006.0120}, doi = {10.2136/vzj2006.0120}, abstract = {Vertical spatial sensitivity and effective depth of exploration (de) of low-induction-number (LIN) instruments over a layered soil were evaluated using a complete numerical solution to Maxwell's equations. Previous studies using approximate mathematical solutions predicted a vertical spatial sensitivity for instruments operating under LIN conditions that, for a given transmitter–receiver coil separation (s), coil orientation, and transmitter frequency, should depend solely on depth below the land surface. When not operating under LIN conditions, vertical spatial sensitivity and de also depend on apparent soil electrical conductivity (σa) and therefore the induction number (β). In this new evaluation, we determined the range of σa and β values for which the LIN conditions hold and how de changes when they do not. Two-layer soil models were simulated with both horizontal (HCP) and vertical (VCP) coplanar coil orientations. Soil layers were given electrical conductivity values ranging from 0.1 to 200 mS m−1 As expected, de decreased as σa increased. Only the least electrically conductive soil produced the de expected when operating under LIN conditions. For the VCP orientation, this was 1.6s, decreasing to 0.8s in the most electrically conductive soil. For the HCP orientation, de decreased from 0.76s to 0.51s Differences between this and previous studies are attributed to inadequate representation of skin-depth effect and scattering at interfaces between layers. When using LIN instruments to identify depth to water tables, interfaces between soil layers, and variations in salt or moisture content, it is important to consider the dependence of de on σa}, language = {en}, number = {1}, urldate = {2022-02-14}, journal = {Vadose Zone Journal}, author = {Callegary, James B. and Ferré, Ty P. A. and Groom, R. W.}, year = {2007}, note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.2136/vzj2006.0120}, pages = {158--167}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\TDIXIMBB\\vzj2006.html:text/html;Submitted Version:C\:\\Users\\Edify 01\\Zotero\\storage\\J5G7TL5U\\Callegary et al. - 2007 - Vertical Spatial Sensitivity and Exploration Depth.pdf:application/pdf}, } @article{hanssens_improving_2019, title = {Improving the reliability of soil {EC}-mapping: {Robust} apparent electrical conductivity ({rECa}) estimation in ground-based frequency domain electromagnetics}, volume = {337}, issn = {0016-7061}, shorttitle = {Improving the reliability of soil {EC}-mapping}, url = {https://www.sciencedirect.com/science/article/pii/S001670611831721X}, doi = {10.1016/j.geoderma.2018.11.030}, abstract = {The use of frequency domain electromagnetic (FDEM) instrumentation in ground-based near-surface applications is continually expanding. In soil studies, FDEM is mainly deployed to inform on soil properties such as salinity, texture, moisture or compaction by evaluating the low induction number (LIN) apparent electrical conductivity (ECa). However, advanced FDEM applications face terrains and conditions in which these LIN approximations are no longer valid. Under such conditions, the aforementioned instrumentation output systematically underestimates ECa values; making semi-qualitative data analysis, representation and practical interpretation impossible. For this reason, methods have to be developed to relate the complex FDEM responses to a reliable ECa, beyond the limitations of the LIN approximation. In this work, we present a quadrature-phase algorithm (i.e. excluding the in-phase signal from the estimation) to obtain a robust apparent electrical conductivity at both low and high induction numbers. In addition, the algorithm classifies the ECa estimations as either robust or non-robust based on instrument noise, desired precision of the ECa estimation and the effect of subsurface magnetic variations. The algorithm accounts for electrical conductivity, instrument elevation, coil geometry, operating frequency, subsurface magnetic variation and random errors. The presented procedure, which was tested on synthetic and experimental data, consists a robust and straightforward approach to increase reliability of ECa derived soil mapping.}, language = {en}, urldate = {2022-02-14}, journal = {Geoderma}, author = {Hanssens, Daan and Delefortrie, Samuël and Bobe, Christin and Hermans, Thomas and De Smedt, Philippe}, month = mar, year = {2019}, keywords = {Precision agriculture, ECa, Electromagnetic induction (EMI), Ground conductivity meter (GCM), Soil salinity}, pages = {1155--1163}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\3ZINJR48\\S001670611831721X.html:text/html}, } @misc{noauthor_environment_nodate, title = {Environment systems - {Agriculture}}, url = {https://www.envsys.co.uk/agriculture/}, abstract = {Trials Business Intelligence Drone Data Analysis Data Services Demonstrator Agri-track Overview We provide satellite and drone data to governments, research institutes, growers and industry. Our range of products includes application ready maps to monitor crop performance, estimate production, improve management practices, resource planning and market intelligence as well as metrics for breeding, agchem, phenomics and […]}, language = {en-US}, urldate = {2022-02-14}, journal = {Environment Systems}, file = {UAV-Field-Trials-FIN.pdf:C\:\\Users\\Edify 01\\Zotero\\storage\\24BZW7PR\\UAV-Field-Trials-FIN.pdf:application/pdf;Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\DV8IWTSV\\agriculture.html:text/html}, } @misc{noauthor_sustainable_2022, title = {Sustainable {Farming} and {Land} {Management}}, url = {https://envsys.co.uk/sence-case-study/sustainable-land-managment/}, abstract = {SENCE Case Study – Sustainable Farming and Land Management Key to the future of sustainable farming and land management is an understanding of existing habitat types, extent and value together with the use of data modelling to establish the potential for new habitats that can deliver multiple environmental benefits. In two recent projects, one led […]}, language = {en-US}, urldate = {2022-02-14}, journal = {Environment Systems}, month = feb, year = {2022}, file = {Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\4YX3GC57\\sustainable-land-managment.html:text/html}, } @article{doolittle_use_2014, title = {The use of electromagnetic induction techniques in soils studies}, volume = {223-225}, issn = {0016-7061}, url = {https://www.sciencedirect.com/science/article/pii/S0016706114000548}, doi = {10.1016/j.geoderma.2014.01.027}, abstract = {Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales.}, language = {en}, urldate = {2022-02-15}, journal = {Geoderma}, author = {Doolittle, James A. and Brevik, Eric C.}, month = jul, year = {2014}, keywords = {Electromagnetic induction, Apparent conductivity, Soil mapping, Soil spatial characterization}, pages = {33--45}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\3K93M9SN\\S0016706114000548.html:text/html;Full Text:C\:\\Users\\Edify 01\\Zotero\\storage\\QCIZZKCN\\Doolittle and Brevik - 2014 - The use of electromagnetic induction techniques in.pdf:application/pdf}, } @article{bjorn_moller_downscaling_2021, title = {Downscaling digital soil maps using electromagnetic induction and aerial imagery}, volume = {385}, issn = {0016-7061}, url = {https://www.sciencedirect.com/science/article/pii/S0016706120326070}, doi = {10.1016/j.geoderma.2020.114852}, abstract = {Coarse-resolution soil maps at regional to national extents are often inappropriate for mapping intra-field variability. At the same time, sensor data, such as electromagnetic induction measurements and aerial imagery, can be highly useful for mapping soil properties that correlate with electrical conductivity or soil color. However, maps based on these data nearly always require calibration with local samples, as multiple factors can affect the sensor measurements. In this study, we present a downscaling method, which combines coarse-resolution, large extent soil maps with sensor data in order to improve predictions of soil properties. The method modifies values from coarse-resolution soil maps to predict soil properties at a location, using relationships between soil properties and sensor data from other locations. We test this method for predicting clay and soil organic matter contents at five agricultural fields located in Denmark. We test the method for one field at a time, using soil samples from the four other fields to predict soil properties. The maps produced with the method are generally more accurate than the coarse-resolution soil maps, especially for soil organic matter. The method generally overestimates prediction uncertainties, a disadvantage, which will require improvements. Overall, the method is a simple, promising tool for giving a quantitative estimate of soil properties, when no local soil samples are available.}, language = {en}, urldate = {2022-02-24}, journal = {Geoderma}, author = {Bjørn Møller, Anders and Koganti, Triven and Beucher, Amélie and Iversen, Bo V. and Greve, Mogens Humlekrog}, month = mar, year = {2021}, keywords = {Electrical conductivity, Remote sensing, Soil organic matter, Clay, Denmark, Topsoil}, pages = {114852}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\WPMUR9VX\\S0016706120326070.html:text/html;Submitted Version:C\:\\Users\\Edify 01\\Zotero\\storage\\W8MM83JN\\Bjørn Møller et al. - 2021 - Downscaling digital soil maps using electromagneti.pdf:application/pdf}, } @article{pastor_mineral_2016, title = {Mineral soil composition interfacing archaeology and chemistry}, volume = {78}, issn = {0165-9936}, url = {https://www.sciencedirect.com/science/article/pii/S0165993615300224}, doi = {10.1016/j.trac.2015.07.019}, abstract = {In the last decade, different soil types have been analysed to evaluate the effect of human activities from an archaeological point of view. In particular, in the last few years, tremendous advances have been made in sample preparation and analytical methods used in archaeological soil analyses. However, there is still a need to set standardized protocols to achieve different archaeological goals. Therefore, in this study, the analytical methods available to study archaeological soils have been reviewed together with a critical discussion on the challenging archaeological questions, which could be answered by determining their mineral composition. Data on trace elements and rare earth elements, which could provide a fingerprint of the human activities, have been evaluated in different studies and discussed here.}, language = {en}, urldate = {2022-02-24}, journal = {TrAC Trends in Analytical Chemistry}, author = {Pastor, Agustin and Gallello, Gianni and Cervera, M. Luisa and de la Guardia, Miguel}, month = apr, year = {2016}, keywords = {Anthropogenic fingerprints, Diagenesis, Environmental impact, Mineral soil analyses, Palaeoenvironment, Provenance materials}, pages = {48--59}, file = {ScienceDirect Snapshot:C\:\\Users\\Edify 01\\Zotero\\storage\\PS2I27KC\\S0165993615300224.html:text/html}, } @misc{noauthor_headwall_nodate, title = {Headwall {ShareFile} {Page}}, url = {https://headwallphotonics.sharefile.com/share/view/se6cc5b98b2894edebffefb48fc0d6ebe}, urldate = {2022-03-01}, file = {Headwall ShareFile Page:C\:\\Users\\Edify 01\\Zotero\\storage\\QRCUA28B\\se6cc5b98b2894edebffefb48fc0d6ebe.html:text/html}, }