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Mapping Cropping Practices of a Sugarcane-Based Cropping System in Kenya Using Remote Sensing

Betty Mulianga, Agnès Bégué, Pascal Clouvel, Pierre Todoroff
<span title="2015-10-30">2015</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
The crop map will inform better planning decisions for the sugar industry operations, while the harvest mode map will be used to plan for sensitizations forums on best management and environmental practices  ...  We developed an original method for mapping cropping practices: crop type and harvest mode, in a sugarcane landscape of western Kenya using remote sensing data.  ...  Special thanks to Kibos-Miwani sugar mill for providing data on cropping practices and availing a field assistant during fieldwork.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs71114428">doi:10.3390/rs71114428</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x2qppav7bngprfskm3i3q64o6e">fatcat:x2qppav7bngprfskm3i3q64o6e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170811081504/http://africanremotesensing.org/resources/Archive/November2015/remotesensing-07-14428.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/da/aa/daaafd067e135e1eff7e534eb3598e3e946d3883.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs71114428"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Object-based Classification of High Resolution SAR Images for Within Field Homogeneous Zone Delineation

Jiangui Liu, Elizabeth Pattey, Michel C. Nolin
<span title="2008-09-01">2008</span> <i title="American Society for Photogrammetry and Remote Sensing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kdyocotdxbbllpnjlbhkgfpogi" style="color: black;">Photogrammetric Engineering and Remote Sensing</a> </i> &nbsp;
The SAR data classification produced interpretable patterns of soil and crop spatial variability, which can be used to infer withinfield management zones.  ...  Results were evaluated using analysis of variance and variance reduction of soil electrical conductivity (EC), leaf area index (LAI), and crop yield.  ...  Bob Hawkins (CCRS) for data collection and analyses (ECORC contribution number: 06-694).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14358/pers.74.9.1159">doi:10.14358/pers.74.9.1159</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h7fadrclpfec7nk2flhb6ppp7i">fatcat:h7fadrclpfec7nk2flhb6ppp7i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20101008004811/http://asprs.org/publications/pers/2008journal/september/2008_sep_1159-1168.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/27/f7/27f7d5f93109c9542148284f3490db8dfe22ad8f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14358/pers.74.9.1159"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

In-season early mapping of rice area and flooding dynamics from optical and SAR satellite data

D. Stroppiana, Mirco Boschetti, R. Azar, M. Barbieri, F. Collivignarelli, L. Gatti, G. Fontanelli, L. Busetto, F. Holecz
<span title="">2019</span> <i title="Informa UK Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wati364qdnf5ppl2xsj2domo6i" style="color: black;">European Journal of Remote Sensing</a> </i> &nbsp;
The approach relies on a-priori knowledge on crop dynamics to adapt time horizons for TSD computation and thresholds to local conditions.  ...  A rule-based algorithm was applied to synthetic statistical metrics (TSDs-Temporal Spectra Descriptors) computed from temporal datasets of optical spectral indices and SAR backscattering coefficient.  ...  Cadastral polygons over Lombardy were provided the framework of the Space4Agri project (http://space4agri.irea. cnr.it/it). We acknowledge anonymous reviewers for their valuable comments.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/22797254.2019.1581583">doi:10.1080/22797254.2019.1581583</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/d2no5biiybeu7nawemusqmez4e">fatcat:d2no5biiybeu7nawemusqmez4e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200306195245/https://repository.rothamsted.ac.uk/download/2c20eed1d86d808718fc174aa8f9eefe90b0c59015038c8735740d895e14124b/7071851/In%20season%20early%20mapping%20of%20rice%20area%20and%20flooding%20dynamics%20from%20optical%20and%20SAR%20satellite%20data.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/84/d5/84d5542737c8534838505f1d61cadb0ac8c34aa9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/22797254.2019.1581583"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> tandfonline.com </button> </a>

Advances in Unmanned Aerial System Remote Sensing for Precision Viticulture

Alberto Sassu, Filippo Gambella, Luca Ghiani, Luca Mercenaro, Maria Caria, Antonio Luigi Pazzona
<span title="2021-02-01">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
New technologies for management, monitoring, and control of spatio-temporal crop variability in precision viticulture scenarios are numerous.  ...  Remote sensing relies on sensors able to provide useful data for the improvement of management efficiency and the optimization of inputs. unmanned aerial systems (UASs) are the newest and most versatile  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21030956">doi:10.3390/s21030956</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33535445">pmid:33535445</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/o4kjaxk3g5bkjpmbqvxpkmealu">fatcat:o4kjaxk3g5bkjpmbqvxpkmealu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210203013625/https://res.mdpi.com/d_attachment/sensors/sensors-21-00956/article_deploy/sensors-21-00956.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f2/3b/f23be4eddef38155d514abc3f84b45d2f19b07e5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21030956"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time Series [article]

Félix Quinton, Loic Landrieu
<span title="2021-11-16">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
While annual crop rotations play a crucial role for agricultural optimization, they have been largely ignored for automated crop type mapping.  ...  In this paper, we take advantage of the increasing quantity of annotated satellite data to propose the first deep learning approach modeling simultaneously the inter- and intra-annual agricultural dynamics  ...  Indeed, Sentinel-2 offers multi-spectral observations at a high revisit time of five days on average, which are particularly appropriate for characterizing the complex spectral and temporal characteristics  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2110.08187v2">arXiv:2110.08187v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/imedafp3zfdjtc7t47zwilh564">fatcat:imedafp3zfdjtc7t47zwilh564</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211130092934/https://arxiv.org/pdf/2110.08187v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/53/16/5316ac8443e8ab5518065cc61acf387721f27e2e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2110.08187v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya

Kyalo Richard, Elfatih M. Abdel-Rahman, Sevgan Subramanian, Johnson O. Nyasani, Michael Thiel, Hosein Jozani, Christian Borgemeister, Tobias Landmann
<span title="2017-11-03">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
Further research is needed on the feasibility of using freely available 10-20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models  ...  Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s17112537">doi:10.3390/s17112537</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29099780">pmid:29099780</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5713137/">pmcid:PMC5713137</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/otk4juz3jrdmnhr5uivuazbrfu">fatcat:otk4juz3jrdmnhr5uivuazbrfu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190427100343/https://elib.dlr.de/115508/1/sensors-17-02537-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e4/12/e412641041187a43a0c268e8444dd0d6c07c39cb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s17112537"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5713137" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time Series

Félix Quinton, Loic Landrieu
<span title="2021-11-16">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
While annual crop rotations play a crucial role for agricultural optimization, they have been largely ignored for automated crop type mapping.  ...  Along with simple training adjustments, our model provides an improvement of over 6.3% mIoU over the current state-of-the-art of crop classification, and a reduction of over 21% of the error rate.  ...  Acknowledgments: We thanks the SIMV department of IGN for their logistic support and data expertise. We thank the ASP for their continuous expertise and for initiating this project.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs13224599">doi:10.3390/rs13224599</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gqa6keupufcjdcxymo5n4sd5dy">fatcat:gqa6keupufcjdcxymo5n4sd5dy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220426071702/https://mdpi-res.com/d_attachment/remotesensing/remotesensing-13-04599/article_deploy/remotesensing-13-04599-v2.pdf?version=1637216890" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7d/4a/7d4a3c5a527a2aee450ef76e27678381d4b9889e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs13224599"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Estimating plant area index for monitoring crop growth dynamics using Landsat-8 and RapidEye images

Jiali Shang, Jiangui Liu, Ted Huffman, Budong Qian, Elizabeth Pattey, Jinfei Wang, Ting Zhao, Xiaoyuan Geng, David Kroetsch, Taifeng Dong, Nicholas Lantz
<span title="2014-11-12">2014</span> <i title="SPIE-Intl Soc Optical Eng"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/432bmec4lfhu5cxeshhodwkttm" style="color: black;">Journal of Applied Remote Sensing</a> </i> &nbsp;
This study investigates the use of two different optical sensors, the multispectral imager (MSI) onboard the RapidEye satellites and the operational land imager (OLI) onboard the Landsat-8 for mapping  ...  A linear relationship could be used for crop green effective PAI estimation from EVI2, with a coefficient of determination (R 2 ) of 0.85 and root-mean-square error of 0.53.  ...  Acknowledgments This study was funded by Agriculture and Agri-Food Canada and the Canadian Space Agency through a research project on land productivity using Earth observation and crop modeling.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/1.jrs.8.085196">doi:10.1117/1.jrs.8.085196</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fq47wzijznbfrmdkpsw3fpsupi">fatcat:fq47wzijznbfrmdkpsw3fpsupi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180722070908/https://www.spiedigitallibrary.org/journals/Journal-of-Applied-Remote-Sensing/volume-8/issue-1/085196/Estimating-plant-area-index-for-monitoring-crop-growth-dynamics-using/10.1117/1.JRS.8.085196.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ec/9a/ec9a9831a361aa7f85c9a3dd0069b7d2abbf9754.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/1.jrs.8.085196"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Rice Crop Monitoring and Yield Estimation Through Cosmo Skymed and TerraSAR-X: A SAR-Based Experience in India

S. Pazhanivelan, P. Kannan, P. Christy Nirmala Mary, E. Subramanian, S. Jeyaraman, A. Nelson, T. Setiyono, F. Holecz, M. Barbieri, M. Yadav
<span title="2015-04-28">2015</span> <i title="Copernicus GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/i74shj7anreaxjo327fokng66m" style="color: black;">The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</a> </i> &nbsp;
Recent and planned launches of SAR sensors coupled with automated processing can provide sustainable solutions to the challenges on mapping and monitoring rice systems.  ...  A simple, robust, rule-based classification for mapping rice area with multi-temporal, X-band, HH polarized SAR imagery from COSMO Skymed and TerraSAR X and site specific parameters were used.  ...  ACKNOWLEDGEMENTS This work has been undertaken within the framework of the Remote Sensing-based Information and Insurance for Crops in Emerging economies (RIICE) program, financially supported by the Swiss  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/isprsarchives-xl-7-w3-85-2015">doi:10.5194/isprsarchives-xl-7-w3-85-2015</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bbebz453pbevnkrnrhsokeetay">fatcat:bbebz453pbevnkrnrhsokeetay</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170815020610/https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/85/2015/isprsarchives-XL-7-W3-85-2015.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/da/f8/daf814193b52e788266dd833346888593709ea2f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/isprsarchives-xl-7-w3-85-2015"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Monitoring Complex Integrated Crop–Livestock Systems at Regional Scale in Brazil: A Big Earth Observation Data Approach

Patrick Calvano Kuchler, Margareth Simões, Rodrigo Ferraz, Damien Arvor, Pedro Luiz Oliveira de Almeida Machado, Marcos Rosa, Raffaele Gaetano, Agnès Bégué
<span title="2022-03-30">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
systems (iCL) constitute a very complex target and a challenge for automatic mapping of cropping practices based on remote sensing data.  ...  The overall objective of this study was to develop a classification strategy for the annual mapping of integrated Crop–Livestock systems (iCL) at a regional scale.  ...  We also thank the Bom Futuro Group and the consulting Adriano da Paz for providing field data. Conflicts of Interest: The authors declare no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs14071648">doi:10.3390/rs14071648</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/od3tysfkirfmzfgphjkjvayixa">fatcat:od3tysfkirfmzfgphjkjvayixa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220622000444/https://mdpi-res.com/d_attachment/remotesensing/remotesensing-14-01648/article_deploy/remotesensing-14-01648-v2.pdf?version=1649314713" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/18/30/1830ab5f0d35044a0f44eafa8c50381449547964.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs14071648"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015

Anukesh Krishnankutty Ambika, Brian Wardlow, Vimal Mishra
<span title="2016-12-20">2016</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/a577b42d4nfhddl7kurxnuyzem" style="color: black;">Scientific Data</a> </i> &nbsp;
India is among the countries that uses a significant fraction of available water for irrigation.  ...  for all the agroecological zones in India for the period of 2000-2015.  ...  The work was supported by the ITRA-Water program and Water Advanced Research and Innovation (WARI) fellowship to VM.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/sdata.2016.118">doi:10.1038/sdata.2016.118</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/27996974">pmid:27996974</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5170598/">pmcid:PMC5170598</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/f6rnxm3e7zh7vc7lznvlwjv5s4">fatcat:f6rnxm3e7zh7vc7lznvlwjv5s4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190223202058/http://pdfs.semanticscholar.org/4ca5/e9cfc414ed0ed04d6469bba2075fde082e19.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4c/a5/4ca5e9cfc414ed0ed04d6469bba2075fde082e19.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/sdata.2016.118"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5170598" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Research advances of SAR remote sensing for agriculture applications: A review

Chang-an LIU, Zhong-xin CHEN, Yun SHAO, Jin-song CHEN, Tuya Hasi, Hai-zhu PAN
<span title="">2019</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ryf5lq3knnaq5mo7vtpgbgfn7a" style="color: black;">Journal of Integrative Agriculture</a> </i> &nbsp;
For instance, the spatial resolution and revisiting cycle of the SAR sensors, the accuracy of crop classification, the whole phenological period monitoring of crop growth status, the soil moisture inversion  ...  Synthetic aperture radar (SAR) is an effective and important technique in monitoring crop and other agricultural targets because its quality does not depend on weather conditions.  ...  Acknowledgements This work was supported in part by the National Natural Science Foundation of China (61661136006 and 41371396). Allain S, Ferro-Famil L, Pottier E. 2003.  ... 
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Remote sensing in food production and #8211; a review

Teresa Calvao, Maria Pessoa
<span title="">2015</span> <i title="Faculty of Food and Agriculture, United Arab Emirates University"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xikzjvczcndynnzufhnsfuwvgu" style="color: black;">Emirates Journal of Food and Agriculture</a> </i> &nbsp;
The objective of this paper is to review the contribution of remote sensing techniques in the classification, monitoring of crop phenology and condition and estimation of production.  ...  However, remotely sensed satellite data offer timely, objective, economical, and synoptic information for crop monitoring.  ...  And, in fact, since the early 80s, satellite imagery-based spectral VIs have been extensively used and constitute an important tool in the mapping and monitoring of terrestrial ecosystems because they  ... 
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Dynamic Mapping of Paddy Rice Using Multi-Temporal Landsat Data Based on a Deep Semantic Segmentation Model

Meiqi Du, Jingfeng Huang, Pengliang Wei, Lingbo Yang, Dengfeng Chai, Dailiang Peng, Jinming Sha, Weiwei Sun, Ran Huang
<span title="2022-06-29">2022</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yws6xlpwzjf7llvhkn3wayuvfu" style="color: black;">Agronomy</a> </i> &nbsp;
Timely, accurate, and repeatable crop mapping is vital for food security. Rice is one of the important food crops.  ...  Dynamic mapping is not only essential to assist farms and governments for growth monitoring and production assessment in the growing season, but also to support mitigation and disaster response strategies  ...  Several researchers have worked on temporal Landsat data to monitor growing dynamics for paddy rice and other crop classification.  ... 
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Remote Sensing for Crop Management

Paul J. Pinter, Jr., Jerry L. Hatfield, James S. Schepers, Edward M. Barnes, M. Susan Moran, Craig S.T. Daughtry, Dan R. Upchurch
<span title="2003-06-01">2003</span> <i title="American Society for Photogrammetry and Remote Sensing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kdyocotdxbbllpnjlbhkgfpogi" style="color: black;">Photogrammetric Engineering and Remote Sensing</a> </i> &nbsp;
This knowledge has facilitated the development and use of various remote sensing methods for non-destructive monitoring of plant growth and development and for the detection of many environmental stresses  ...  water, nutrients, and pests in agricultural crops; and assesses the role of remote sensing in yield prediction.  ...  on ways to use the latter for monitoring water stress (Wiegand and Namken 1966; Ehrler, 1973) .  ... 
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