{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,13]],"date-time":"2026-11-13T11:53:02Z","timestamp":1794570782484,"version":"4.9.1"},"reference-count":74,"publisher":"Elsevier BV","issue":"9","license":[{"start":{"date-parts":[[2018,9,1]],"date-time":"2018-09-01T00:00:00Z","timestamp":1535760000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2019,7,12]],"date-time":"2019-07-12T00:00:00Z","timestamp":1562889600000},"content-version":"vor","delay-in-days":314,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Integrative Agriculture"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1016\/s2095-3119(17)61859-8","type":"journal-article","created":{"date-parts":[[2018,8,10]],"date-time":"2018-08-10T11:05:30Z","timestamp":1533899130000},"page":"1915-1931","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":401,"title":["Agricultural remote sensing big data: Management and applications"],"prefix":"10.1016","volume":"17","author":[{"given":"Yanbo","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhong-xin","family":"CHEN","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"YU","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang-zhi","family":"HUANG","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xing-fa","family":"GU","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/S2095-3119(17)61859-8_bib1","author":"Anonymous"},{"key":"10.1016\/S2095-3119(17)61859-8_bib2","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/S0378-3774(00)00080-9","article-title":"Remote sensing for irrigated agriculture: Examples from research and possible applications","volume":"46","author":"Bastiaanssen","year":"2000","journal-title":"Agricultural Water Management"},{"key":"10.1016\/S2095-3119(17)61859-8_bib3","series-title":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","first-page":"1","article-title":"DeepSat \u2014 A learning framework for satellite imagery","author":"Basu","year":"2015"},{"key":"10.1016\/S2095-3119(17)61859-8_bib4","doi-asserted-by":"crossref","first-page":"10395","DOI":"10.3390\/rs61110395","article-title":"Estimating biomass of barley using crop surface models (CSMs) derived from UAV-based RGB imaging","volume":"6","author":"Bendig","year":"2014","journal-title":"Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib5","series-title":"Proceedings of 1st International Conference on Next Generation Computing Technologies (NGCT)","first-page":"744","article-title":"Big data in precision agriculture: Weather forecasting for future farming","author":"Bendre","year":"2015"},{"key":"10.1016\/S2095-3119(17)61859-8_bib6","first-page":"1","article-title":"A proposed architecture for big data driven supply chain analytics","volume":"6","author":"Biswas","year":"2016","journal-title":"International Journal of Supply Chain Management (IUP)"},{"key":"10.1016\/S2095-3119(17)61859-8_bib7","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS Journal of Photogrammetry and Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib8","doi-asserted-by":"crossref","first-page":"4026","DOI":"10.3390\/rs70404026","article-title":"Evaluating multispectral images and vegetation indices for precision farming applications from UAV images","volume":"7","author":"Candiago","year":"2015","journal-title":"Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib9","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.ins.2014.01.015","article-title":"Data-intensive applications, challenges, techniques and technologies: A survey on big data","volume":"275","author":"Chen","year":"2014","journal-title":"Information Sciences"},{"key":"10.1016\/S2095-3119(17)61859-8_bib10","doi-asserted-by":"crossref","first-page":"2094","DOI":"10.1109\/JSTARS.2014.2329330","article-title":"Deep learning-based classification of hyperspectral data","volume":"7","author":"Chen","year":"2014","journal-title":"IEEE Journal of Selected Topics in Applied Erath Observations and Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib11","series-title":"Proceedings of the IEEE International Geoscience and Remote Sensing Symposium","article-title":"CHARMS \u2014 China agricultural remote sensing monitoring system","author":"Chen","year":"2011"},{"key":"10.1016\/S2095-3119(17)61859-8_bib12","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1109\/JPROC.2016.2598228","article-title":"Big data for remote sensing: Challenges and opportunities","volume":"104","author":"Chi","year":"2016","journal-title":"Proceedings of the IEEE"},{"key":"10.1016\/S2095-3119(17)61859-8_bib13","series-title":"Proceedings of EuroVis06 Joint Eurographics\u2014IEEE-VGTC Symposium on Visualization","first-page":"91","article-title":"Terrain rendering using spherical climaps","author":"Clasen","year":"2006"},{"issue":"B2","key":"10.1016\/S2095-3119(17)61859-8_bib14","first-page":"147","article-title":"NASA standards for earth remote sensing data","volume":"XXXIII","author":"Di","year":"2000","journal-title":"International Archives of Photogrammetry and Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib15","series-title":"Web GIS: Principles and Applications","author":"Fu","year":"2010"},{"key":"10.1016\/S2095-3119(17)61859-8_bib16","first-page":"1","article-title":"Some essential questions in remote sensing science and technology","volume":"13","author":"Gong","year":"2009","journal-title":"Journal of Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib17","unstructured":"Gu X, Yu T, Xie D, Guo H, Hu X, Li J, Cheng T. 2013. A Hierarchically Organized Method Based on the Latitude and Longitude Grid Data. China Patent. No. CN102346923 B. 2013-10-23. (in Chinese)"},{"key":"10.1016\/S2095-3119(17)61859-8_bib18","series-title":"Handbook of Multisensor Data Fusion: Theory and Practice","first-page":"1","article-title":"Multisensor data fusion","author":"Hall","year":"2009"},{"key":"10.1016\/S2095-3119(17)61859-8_bib19","doi-asserted-by":"crossref","first-page":"4060","DOI":"10.1109\/JSTARS.2015.2403135","article-title":"Jointly assimilating MODIS LAI and ET products into SWAP model for winter wheat yield estimation","volume":"8","author":"Huang","year":"2015","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib20","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.agrformet.2015.10.013","article-title":"Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation","volume":"216","author":"Huang","year":"2015","journal-title":"Agricultural and Forest Meteorology"},{"key":"10.1016\/S2095-3119(17)61859-8_bib21","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.agrformet.2015.02.001","article-title":"Improving winter wheat yield estimation by assimilation of the leaf area index from Landsat TM and MODIS data into the WOFOST model","volume":"204","author":"Huang","year":"2015","journal-title":"Agricultural and Forest Meteorology"},{"key":"10.1016\/S2095-3119(17)61859-8_bib22","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1080\/10798587.2008.10643307","article-title":"Extraction of plaingting areas of major crops and crop growth monitoring in Northeast China","volume":"18","author":"Huang","year":"2012","journal-title":"Intelligent Automation & Soft Computing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib23","doi-asserted-by":"crossref","first-page":"973","DOI":"10.3390\/algor2030973","article-title":"Advances in artificial neural networks \u2014 methodological development and applications","volume":"2","author":"Huang","year":"2009","journal-title":"Algorithms"},{"key":"10.1016\/S2095-3119(17)61859-8_bib24","first-page":"1563","article-title":"Cotton yield estimation using very high-resolution digital images acquired on a low-cost small unmanned aerial vehicle","volume":"59","author":"Huang","year":"2017","journal-title":"Transactions of the ASABE"},{"key":"10.1016\/S2095-3119(17)61859-8_bib25","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.compag.2010.01.001","article-title":"Development of soft computing and applications in agricultural and biological engineering","volume":"71","author":"Huang","year":"2010","journal-title":"Computers and Electronics in Agriculture"},{"key":"10.1016\/S2095-3119(17)61859-8_bib26","unstructured":"Huang Y, Reddy K N. 2015. Unmanned aerial vehicles: A unique platform for low-altitude remote sensing for crop management. In: Proceedings of the Plenary and Lead Papers of the 25th Asian-Pacific Weed Science Society Conference. Hyderabad, India. pp. 185\u2013192."},{"key":"10.1016\/S2095-3119(17)61859-8_bib27","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1002\/ps.3839","article-title":"Assessment of soybean injury from glyphosate using airborne multispectral remote sensing","volume":"71","author":"Huang","year":"2015","journal-title":"Pesticide Management Science"},{"key":"10.1016\/S2095-3119(17)61859-8_bib28","first-page":"37","article-title":"Estimation of cotton yield with varied irrigation and nitrogen treatments using aerial multispectral imagery","volume":"6","author":"Huang","year":"2013","journal-title":"International Journal of Agricultural and Biological Engineering"},{"key":"10.1016\/S2095-3119(17)61859-8_bib29","first-page":"1","article-title":"Development and prospect of unmanned aerial vehicles for agricultural production management","volume":"6","author":"Huang","year":"2013","journal-title":"International Journal of Agricultural and Biological Engineering"},{"key":"10.1016\/S2095-3119(17)61859-8_bib30","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.biosystemseng.2010.08.003","article-title":"Airborne remote sensing assessment of the damage to cotton caused by spray drift from aerially applied glyphosate through spray deposition measurements","volume":"107","author":"Huang","year":"2010","journal-title":"Biosystems Engineering"},{"key":"10.1016\/S2095-3119(17)61859-8_bib31","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/0034-4257(90)90100-Z","article-title":"PROSPECT: A model of leaf optical properties spectra","volume":"34","author":"Jacquemoud","year":"1990","journal-title":"Remote Sensing of Environment"},{"key":"10.1016\/S2095-3119(17)61859-8_bib32","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1016\/j.rse.2008.01.026","article-title":"PROSPECT+SAIL models: A review of use for vegetation characterization","volume":"113","author":"Jacquemoud","year":"2009","journal-title":"Remote Sensing of Environment"},{"key":"10.1016\/S2095-3119(17)61859-8_bib33","series-title":"Proceedings of IEEE International Conference on Geoscience and Remote Sensing Symposium, 2006","first-page":"1992","article-title":"PROSPECT+SAIL: 15 years of use for land surface characterization","author":"Jacquemoud","year":"2006"},{"key":"10.1016\/S2095-3119(17)61859-8_bib34","series-title":"Proceedings of 2016 International Conference on Signal Processing, Communication, Power and Embedded System","first-page":"1912","article-title":"Real-time big data analytics architecture for remote sensing application","author":"Jagannathan","year":"2016"},{"key":"10.1016\/S2095-3119(17)61859-8_bib35","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1080\/17538947.2015.1111952","article-title":"Rapid, high-resolution detection of environmental change overcontinental scales from satellite data \u2014 the Earth Observation Data Cube","volume":"9","author":"Lewis","year":"2016","journal-title":"International Journal of Digital Earth"},{"key":"10.1016\/S2095-3119(17)61859-8_bib36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fenvs.2015.00045","article-title":"A survey of remote-sensing big data","volume":"3","author":"Liu","year":"2015","journal-title":"Frontiers in Environmental Science"},{"key":"10.1016\/S2095-3119(17)61859-8_bib37","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.future.2014.10.029","article-title":"Remote sensing big data computing: Challenges and opportunities","volume":"51","author":"Ma","year":"2015","journal-title":"Future Generation Computer Systems"},{"key":"10.1016\/S2095-3119(17)61859-8_bib38","doi-asserted-by":"crossref","first-page":"2183","DOI":"10.3390\/rs5052164","article-title":"Visualizing and quantifying vineyard canopy LAI using an unmanned aerial vehicle (UAV) collected high density structure from motion point cloud","volume":"5","author":"Mathews","year":"2013","journal-title":"Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fpls.2016.01419","article-title":"Using deep learning for image-based plant disease detection","volume":"7","author":"Mohanty","year":"2016","journal-title":"Frontiers in Plant Science"},{"key":"10.1016\/S2095-3119(17)61859-8_bib40","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/S0034-4257(97)00045-X","article-title":"Opportunities and limitations for image-based remote sensing in precision crop management","volume":"61","author":"Moran","year":"1997","journal-title":"Remote Sensing of Environment"},{"key":"10.1016\/S2095-3119(17)61859-8_bib41","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/j.rse.2015.11.003","article-title":"Water observations from space: Mapping surface water from 25 years of Landsat imagery across Australia","volume":"174","author":"Mueller","year":"2016","journal-title":"Remote Sensing of Environment"},{"key":"10.1016\/S2095-3119(17)61859-8_bib42","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.biosystemseng.2012.08.009","article-title":"Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps","volume":"114","author":"Mulla","year":"2013","journal-title":"Biosystems Engineering"},{"key":"10.1016\/S2095-3119(17)61859-8_bib43","doi-asserted-by":"crossref","first-page":"647","DOI":"10.14358\/PERS.69.6.647","article-title":"Remote sensing for crop management","volume":"69","author":"Pinter","year":"2003","journal-title":"Photogrammetric Engineering and Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib44","unstructured":"Piwowar J M. 2001. Getting your imagery at the right level. Cartouche. No. 41 (Winter)."},{"key":"10.1016\/S2095-3119(17)61859-8_bib45","doi-asserted-by":"crossref","first-page":"4610","DOI":"10.1109\/JSTARS.2015.2424683","article-title":"Real-time big data analytical architecture for remote sensing application","volume":"8","author":"Rathore","year":"2015","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib46","doi-asserted-by":"crossref","first-page":"1910","DOI":"10.1002\/ps.3755","article-title":"Glyphosate-resistant and glyphosate-susceptible Palmer amaranth (Amaranthus palmeri S. Wats.): hyperspectral reflectance properties of plants and potential for classification","volume":"70","author":"Reddy","year":"2014","journal-title":"Pest Management Science"},{"key":"10.1016\/S2095-3119(17)61859-8_bib47","first-page":"257","article-title":"Regional crop yield simulation based on crop growth model and remote sensing data","volume":"27","author":"Ren","year":"2011","journal-title":"Transactions of the Chinese Society of Agricultural Engineering"},{"key":"10.1016\/S2095-3119(17)61859-8_bib48","first-page":"568","article-title":"MODIS vegetation index data used for estimating corn yield in USA","volume":"19","author":"Ren","year":"2015","journal-title":"Journal of Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib49","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/j.jag.2007.11.003","article-title":"Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China","volume":"10","author":"Ren","year":"2008","journal-title":"International Journal of Applied Earth Observation and Geoinformation"},{"key":"10.1016\/S2095-3119(17)61859-8_bib50","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/S1462-9011(03)00070-4","article-title":"A review of remote sensing technology in support of the Kyoto Protocol","volume":"6","author":"Rosenqvist","year":"2003","journal-title":"Environmental Science & Policy"},{"key":"10.1016\/S2095-3119(17)61859-8_bib51","doi-asserted-by":"crossref","first-page":"453","DOI":"10.3390\/s120100453","article-title":"Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera","volume":"12","author":"Rosnell","year":"2012","journal-title":"Sensors"},{"key":"10.1016\/S2095-3119(17)61859-8_bib52","author":"Rubin"},{"key":"10.1016\/S2095-3119(17)61859-8_bib53","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1016\/j.procs.2015.04.134","article-title":"Lowering data dimensionality in big data for the benefit of precision agriculture","volume":"48","author":"Sabarina","year":"2015","journal-title":"Procedia Computer Science"},{"key":"10.1016\/S2095-3119(17)61859-8_bib54","doi-asserted-by":"crossref","first-page":"3289801","DOI":"10.1155\/2016\/3289801","article-title":"Deep neural networks based recognition of plant diseases by leaf image classification","volume":"2016","author":"Sladojevic","year":"2016","journal-title":"Computational Intelligence and Neuroscience"},{"key":"10.1016\/S2095-3119(17)61859-8_bib55","unstructured":"Snipes C E, Nichols S P, Poston D H, Walker T W, Evans L P, Robinson H R. 2005. Current Agricultural Practices of the Mississippi Delta. Mississippi Agricultural & Forestry Experiment Station, Bulletin 1143. Mississippi State, Mississippi, USA. p. 18."},{"key":"10.1016\/S2095-3119(17)61859-8_bib56","series-title":"Flattening the Earth: Two Thousand Years of Map Projections","first-page":"5","author":"Snyder","year":"1993"},{"key":"10.1016\/S2095-3119(17)61859-8_bib57","author":"Song"},{"key":"10.1016\/S2095-3119(17)61859-8_bib58","doi-asserted-by":"crossref","first-page":"11013","DOI":"10.3390\/rs61111013","article-title":"A lightweight hyperspectral mapping system and photogrammetric processing chain for unmanned aerial vehicles","volume":"6","author":"Suomalainen","year":"2014","journal-title":"Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib59","doi-asserted-by":"crossref","first-page":"103","DOI":"10.5539\/jas.v4n4p103","article-title":"Potential and challenges in use of thermal imaging for humid region irrigation system management","volume":"4","author":"Thomson","year":"2012","journal-title":"Journal of Agricultural Science"},{"key":"10.1016\/S2095-3119(17)61859-8_bib60","doi-asserted-by":"crossref","first-page":"1392","DOI":"10.3390\/rs4051392","article-title":"An automated technique for generating georectified mosaics from ultra-high resolution unmanned aerial vehicle (UAV) imagery, based on structure from motion (SfM) point clouds","volume":"4","author":"Turner","year":"2012","journal-title":"Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib61","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/0034-4257(84)90057-9","article-title":"Light scattering by leaf layers with application to canopy reflectance model: The SAIL model","volume":"16","author":"Verhoef","year":"1984","journal-title":"Remote Sensing of Environment"},{"key":"10.1016\/S2095-3119(17)61859-8_bib62","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.isprsjprs.2003.09.007","article-title":"Object-based classification of remote sensing data for change detection","volume":"58","author":"Walter","year":"2004","journal-title":"Journal of Photogrammetry and Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib63","first-page":"1","article-title":"A new parallel algorithm based on five-layer fifteen-level remote sensing data organization","volume":"1","author":"Wang","year":"2012","journal-title":"Microcomputer Information"},{"key":"10.1016\/S2095-3119(17)61859-8_bib64","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1080\/02693799608902068","article-title":"A review of current issues in the integration of GIS and remote sensing data","volume":"10","author":"Wilkinson","year":"1996","journal-title":"International Journal of Geographical Information Systems"},{"key":"10.1016\/S2095-3119(17)61859-8_bib65","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.agsy.2017.01.023","article-title":"Big data in small farming \u2014 a review","volume":"153","author":"Wolfert","year":"2017","journal-title":"Agricultural Systems"},{"key":"10.1016\/S2095-3119(17)61859-8_bib66","doi-asserted-by":"crossref","first-page":"5313","DOI":"10.1080\/01431160802036276","article-title":"MODIS-based remote sensing monitoring of grass production in China","volume":"29","author":"Xu","year":"2008","journal-title":"International Journal of Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib67","doi-asserted-by":"crossref","first-page":"3867","DOI":"10.1080\/01431161.2012.762696","article-title":"MODIS-based remote-sensing monitoring of the spatiotemporal patterns of China's grassland vegetation growth","volume":"34","author":"Xu","year":"2013","journal-title":"International Journal of Remote Sensing"},{"key":"10.1016\/S2095-3119(17)61859-8_bib68","series-title":"Remote Sensing of Natural Resources","first-page":"333","article-title":"Remote sensing applications to precision farming","author":"Yao","year":"2013"},{"key":"10.1016\/S2095-3119(17)61859-8_bib69","unstructured":"Yu T, Li J, Cheng T, Hu X, Xie D, Guo H, Gu X. 2012. Data Grading Organization Method Based on Longitude and Latitude Grid. China Patent. No. CN102346923 A. 2012-02-06. (in Chinese)"},{"key":"10.1016\/S2095-3119(17)61859-8_bib70","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1007\/s11119-012-9274-5","article-title":"The application of small unmanned aerial systems for precision agriculture: a review","volume":"13","author":"Zhang","year":"2012","journal-title":"Precision Agriculture"},{"key":"10.1016\/S2095-3119(17)61859-8_bib71","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MGRS.2016.2540798","article-title":"Deep learning for remote sensing data: A technical tutorial on the state of the art","volume":"4","author":"Zhang","year":"2016","journal-title":"IEEE Geoscience and Remote Sensing Magazine"},{"key":"10.1016\/S2095-3119(17)61859-8_bib72","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/S0168-1699(02)00096-0","article-title":"Precision agriculture \u2014 a worldwide overview","volume":"36","author":"Zhang","year":"2002","journal-title":"Computers and Electronics in Agriculture"},{"key":"10.1016\/S2095-3119(17)61859-8_bib73","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.rse.2009.09.018","article-title":"A spectral directional reflectance model of row crops","volume":"114","author":"Zhao","year":"2010","journal-title":"Remote Sensing of Environment"},{"key":"10.1016\/S2095-3119(17)61859-8_bib74","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.rse.2014.09.011","article-title":"Simulated impact of sensor field of view and distance on field measurements of bidirectional reflectance factors for row crops","volume":"156","author":"Zhao","year":"2014","journal-title":"Remote Sensing of Environment"}],"container-title":["Journal of Integrative Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2095311917618598?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2095311917618598?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2019,8,16]],"date-time":"2019-08-16T06:03:50Z","timestamp":1565935430000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2095311917618598"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9]]},"references-count":74,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["S2095311917618598"],"URL":"https:\/\/doi.org\/10.1016\/s2095-3119(17)61859-8","relation":{},"ISSN":["2095-3119"],"issn-type":[{"value":"2095-3119","type":"print"}],"subject":[],"published":{"date-parts":[[2018,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Agricultural remote sensing big data: Management and applications","name":"articletitle","label":"Article Title"},{"value":"Journal of Integrative Agriculture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/S2095-3119(17)61859-8","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"Copyright \u00a9 2018 CAAS. Publishing services by Elsevier B.V. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}