{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T20:39:26Z","timestamp":1781901566784,"version":"3.54.5"},"reference-count":97,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2015,4,1]],"date-time":"2015-04-01T00:00:00Z","timestamp":1427846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, the CropWatch system has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The approach adopts a hierarchical system covering four spatial levels of detail: global, regional, national (thirty-one key countries including China) and \u201csub-countries\u201d (for the nine largest countries). The thirty-one countries encompass more that 80% of both production and exports of maize, rice, soybean and wheat. The methodology resorts to climatic and remote sensing indicators at different scales. The global patterns of crop environmental growing conditions are first analyzed with indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass. At the regional scale, the indicators pay more attention to crops and include Vegetation Health Index (VHI), Vegetation Condition Index (VCI), Cropped Arable Land Fraction (CALF) as well as Cropping Intensity (CI). Together, they characterize crop situation, farming intensity and stress. CropWatch carries out detailed crop condition analyses at the national scale with a comprehensive array of variables and indicators. The Normalized Difference Vegetation Index (NDVI), cropped areas and crop conditions are integrated to derive food production estimates. For the nine largest countries, CropWatch zooms into the sub-national units to acquire detailed information on crop condition and production by including new indicators (e.g., Crop type proportion). Based on trend analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. The hierarchical approach adopted by CropWatch is the basis of the analyses of climatic and crop conditions assessments published in the quarterly \u201cCropWatch bulletin\u201d which provides accurate and timely information essential to food producers, traders and consumers.<\/jats:p>","DOI":"10.3390\/rs70403907","type":"journal-article","created":{"date-parts":[[2015,4,7]],"date-time":"2015-04-07T03:47:46Z","timestamp":1428378466000},"page":"3907-3933","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":93,"title":["Global Crop Monitoring: A Satellite-Based  Hierarchical Approach"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5546-365X","authenticated-orcid":false,"given":"Bingfang","family":"Wu","sequence":"first","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ren\u00e9","family":"Gommes","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongwei","family":"Zeng","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nana","family":"Yan","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wentao","family":"Zou","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Zheng","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ning","family":"Zhang","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng","family":"Chang","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Xing","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Van Heijden","sequence":"additional","affiliation":[{"name":"Division for Digital Agriculture, Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), Olympic Village Science Park,  W. Beichen Road, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,4,1]]},"reference":[{"key":"ref_1","first-page":"1013","article-title":"Latest development of \u201cCropWatch\u201d\u2014An global crop monitoringsystem with remote sensing","volume":"25","author":"Wu","year":"2010","journal-title":"Adv. Earth Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1589","DOI":"10.3390\/rs2061589","article-title":"Monitoring global croplands with coarse resolution earth observations: The global agriculture monitoring (GLAM) project","volume":"2","author":"Justice","year":"2010","journal-title":"Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/17538947.2013.821185","article-title":"Remote sensing-based global crop monitoring: Experiences with China\u2019s CropWatch system","volume":"7","author":"Wu","year":"2014","journal-title":"Int. J. Dig.Earth"},{"key":"ref_4","unstructured":"MinAgri\u2014Argentina. Available online:http:\/\/www.minagri.gob.ar\/site\/."},{"key":"ref_5","first-page":"53","article-title":"Use of remote sensing for crop yield and area estimates in the southern of Brazil","volume":"36","author":"Fontana","year":"2006","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_6","unstructured":"Reichert, G.C., and Caissy, D. A Reliable Crop Condition Assessment Program (CCAP) Incorporating NOAA AVHRR Data, a Geographical Information System and the Internet. Available online:http:\/\/proceedings.esri.com\/library\/userconf\/proc02\/pap0111\/p0111.htm."},{"key":"ref_7","unstructured":"Space Applications Centre (SAC) (1995). Manual for Crop Production Forecasting Using Remotely Sensed Data, a Joint Project of Space and Ministry of Agriculture."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/S0168-1923(00)00115-5","article-title":"Agrometeorology and sustainable agriculture","volume":"103","author":"Sivakumar","year":"2000","journal-title":"Agric. For. Meteorol."},{"key":"ref_9","unstructured":"Gommes, R. (2001, January 12\u201315). Agrometeorological models and remote sensing for crop monitoring and forecasting. Proceedings of the Report of the Asia-Pacific Conference on Early Warning, Preparedness, Prevention and Management of Disasters, Chiang-Mai, Thailand."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/S0168-1923(02)00201-0","article-title":"The benefits to Mexican agriculture of an El Ni\u00f1o-southern oscillation (ENSO) early warning system","volume":"115","author":"Adams","year":"2003","journal-title":"Agric. For. Meteorol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.proenv.2010.09.020","article-title":"Managing climatic risks for enhanced food security: Key information capabilities","volume":"1","author":"Balaghi","year":"2010","journal-title":"Procedia Environ. Sci."},{"key":"ref_12","first-page":"11","article-title":"Space technology for crop monitoring of Bangladesh","volume":"2","author":"Begum","year":"2013","journal-title":"Res. J. Sci. IT Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.ijdrr.2014.04.008","article-title":"A case study for early warning and disaster management in Thailand","volume":"9","author":"Fakhruddin","year":"2014","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.wace.2014.03.005","article-title":"Information systems in a changing climate: Early warnings and drought risk management","volume":"3","author":"Pulwarthy","year":"2014","journal-title":"Weather Clim. Extremes"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.gfs.2012.11.007","article-title":"From complexity to food security decision-support: Novel methods of assessment and their role in enhancing the timeliness and relevance of food and nutrition security information","volume":"2","author":"Mock","year":"2013","journal-title":"Glob. Food Sec."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.wace.2014.03.008","article-title":"AGRHYMET: A drought monitoring and capacity building center in the West Africa region","volume":"3","author":"Traore","year":"2014","journal-title":"Weather Clim. Extremes"},{"key":"ref_17","unstructured":"FAO GIEWS\u2014The Global Information and Early Warning System on Food and Agriculture. Avaialable online:http:\/\/www.fao.org\/giews\/english\/giews_en.pdf."},{"key":"ref_18","unstructured":"Foreign Agricultural Service Crop Explorer for Major Crop Regions, Available online:http:\/\/www.pecad.fas.usda.gov\/cropexplorer\/."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.3390\/rs5031091","article-title":"Enhanced processing of 1-km spatial resolution fAPAR time series for sugarcane yield forecasting and monitoring","volume":"5","author":"Duveiller","year":"2013","journal-title":"Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Yang, Z.W., Di, L.P., Yu, G.P., and Chen, Z.Q. (2011, January 24\u201329). Vegetation condition indices for crop vegetation condition monitoring. Proceedings of the 2001 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, BC, Canada.","DOI":"10.1109\/IGARSS.2011.6049984"},{"key":"ref_21","unstructured":"National Aeronautics and Space Administration (NASA) Large Area Crop Inventory Experiment (LACIE) Phase I and Phase II Accuracy Assessment Final Report, Available online:http:\/\/www.nass.usda.gov\/Education_and_Outreach\/Reports,_Presentations_and_Conferences\/GIS_Reports\/Phase%20I%20and%20II%20Accuracy%20Assessment%20Final%20Report%20(Pages%201\u2013100).pdf."},{"key":"ref_22","unstructured":"Chhikara, R.S., and Feiveson, A.H. Landsat-Based Large Area Crop Acreage Estimation\u2014An Experimental Study. Available online:https:\/\/www.amstat.org\/sections\/srms\/proceedings\/papers\/1978_030.pdf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"670","DOI":"10.1126\/science.208.4445.670","article-title":"Global crop forecasting","volume":"208","author":"MacDonald","year":"1980","journal-title":"Science"},{"key":"ref_24","unstructured":"BlackBridge Satellite Imagery Product Specifications, Version 6.0. Available online:http:\/\/blackbridge.com\/rapideye\/upload\/RE_Product_Specifications_ENG.pdf."},{"key":"ref_25","unstructured":"ESA About Proba-V, Proba-V Facts and Figures. Available online:http:\/\/www.esa.int\/Our_Activities\/Technology\/Proba_Missions\/About_Proba-V."},{"key":"ref_26","unstructured":"Shenzhen Institute of Advanced Technology Chinese Academy of Sciences. Available online:http:\/\/www.siat.ac.cn\/xwzx\/zkyxw\/200801\/t20080129_2094573.html."},{"key":"ref_27","unstructured":"China Centre for Resources Satellite Data and Application. Available online:http:\/\/www.cresda.com\/n16\/n1130\/n188475\/188494.html."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","article-title":"Sentinel-2: ESA\u2019s optical high-resolution mission for GMES operational services","volume":"120","author":"Drusch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1080\/07038992.1982.10855029","article-title":"NOAA-AVHRR crop condition monitoring","volume":"8","author":"Brown","year":"1982","journal-title":"Can. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1109\/36.20292","article-title":"MODIS\u2014Advanced facility instrument for studies of the earth as a system","volume":"27","author":"Salomonson","year":"1989","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Pulitini, P., Barillot, M., Gentet, T., and Reulet, J.F. (1994, January 1). VEGETATION payload. Proceedings of the International Society for Optical Engineering (SPIE) 2209, Garmisch-Partenkirchen, Germany.","DOI":"10.1117\/12.185251"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1175\/1520-0477(1988)069<0278:APTRMM>2.0.CO;2","article-title":"A proposed tropical rainfall measuring mission (TRMM) satellite","volume":"69","author":"Simpson","year":"1988","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1016\/S0273-1177(97)00883-1","article-title":"Global drought and flood-watch from NOAA polar-orbiting satellites","volume":"21","author":"Kogan","year":"1998","journal-title":"Adv. Space Res."},{"key":"ref_34","unstructured":"FAO Global Ecological Zones for FAO Forest Reporting: 2010 Update. Available online:http:\/\/www.fao.org\/geonetwork\/srv\/en."},{"key":"ref_35","unstructured":"Grieser, J., Gommes, R., Cofield, S., and Bernardi, M. New Gridded Maps of Koeppen\u2019s Climate Classification. Avaiable online:http:\/\/www.juergen-grieser.de\/downloads\/Koeppen-Climatology\/Koeppen_Climatology.pdf."},{"key":"ref_36","unstructured":"FAO\/CLIMPAG VasClimo Data. Available online:http:\/\/www.fao.org\/nr\/climpag\/globgrids\/npp_en.asp."},{"key":"ref_37","unstructured":"Fischer, G., Velthuizen, H.V., Medow, S., and Nachtergaele, F. Global Agro-Ecological Assessment for Agriculture in the 21st Century: Methodology and Results, Avaiable online:http:\/\/ipcc-wg2.gov\/njlite_download.php?id=7117."},{"key":"ref_38","unstructured":"USDA Major World Crop Areas and Climatic Profiles, Avaiable online:www.usda.gov\/oce\/weather\/pubs\/Other\/MWCACP\/MajorWorldCropAreas.pdf."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1046\/j.1466-822x.2002.00294.x","article-title":"The global distribution of cultivable lands: Current patterns and sensitivity to possible climate change","volume":"11","author":"Ramankutty","year":"2002","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2007GB002947","article-title":"Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000","volume":"22","author":"Monfreda","year":"2008","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_41","unstructured":"Gommes, R., Wu, B., Li, Z., and Zeng, H. (2015). Design and characterisation of global crop monitoring and reporting units. Agr. Ecosyst. Environ., submitted."},{"key":"ref_42","unstructured":"Sun, H. (1994). Agricultural Natural Resources and Regional Development of China, Jiangsu Science and Technology Press."},{"key":"ref_43","unstructured":"FAOSTAT FAO Global Production and Trade Statistics. Available online:http:\/\/faostat3.fao.org\/home\/E."},{"key":"ref_44","unstructured":"NASA TRMM-Based Precipitation Estimates, Available online:ftp:\/\/trmmopen.gsfc.nasa.gov\/pub\/merged\/mergeIRMicro\/."},{"key":"ref_45","unstructured":"European Commission, Joint Research Center Agrometeorological Data. Available online:http:\/\/spirits.jrc.ec.europa.eu\/?page_id=2869."},{"key":"ref_46","unstructured":"NOAA National Climatic Data Centre, Global Summary of the day (GlobalSOD), Available online:ftp:\/\/ftp.ncdc.noaa.gov\/pub\/data\/gsod."},{"key":"ref_47","first-page":"5","article-title":"Modeling the primary productivity of the earth","volume":"2","author":"Lieth","year":"1972","journal-title":"Nat. Resour."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Gommes, R., Wu, B., Zhang, N., Feng, X., Zeng, H., Li, Z., and Chen, B. (2015). CropWatch Agroclimatic Indicators (CWAIs) for weather impact assessment on global agriculture. Int. J. Biometeorol., submitted.","DOI":"10.1007\/s00484-016-1199-7"},{"key":"ref_49","unstructured":"Chen, B., Gommes, R., Li, Z., and Wu, B. (2015). Environment indices processing software and implementation. Sin. J. Remote Sens., in preparation."},{"key":"ref_50","first-page":"628","article-title":"A methodology for retrieving croppingindex from NDVI profile","volume":"8","author":"Fan","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and differentiation of data by simplified least squares procedures","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"ref_52","unstructured":"Zhang, M., Wu, B., Yu, M., Zou, W., and Zheng, Y. (2015). Monthly monitoring of uncropped arable land: concepts and implementation\u2014A case study in Argentina. Sin. J. Remote Sens., in press."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1080\/01431169008955102","article-title":"Remote sensing of weather impacts on vegetation in non-homogenous area","volume":"11","author":"Kogan","year":"1990","journal-title":"Int. J. Remote Sen."},{"key":"ref_54","unstructured":"Yan, N.N., Wu, B.F., and Chang, S. (2015). Agriculture drought monitoring and assessment based on noaa vhi products: A case study in north america. Sin. J. Remote Sens., in preparation."},{"key":"ref_55","first-page":"515","article-title":"A method to extract regional crop growth information with time series of NDVI data","volume":"8","author":"Zhang","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_56","first-page":"945","article-title":"Study on the crop condition monitoring methods with remote sensing","volume":"37","author":"Meng","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_57","unstructured":"Zou, W.T., Wu, B.F., Zhang, M., and Zheng, Y. (2015). Synthetic method for crop condition analysis-a case study in india. Sin. J. Remote Sens., in press."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Romani, L.A.S., Goncalves, R.R.V., Amaral, B.F., Chino, D.Y.T., Zullo, J., Traina, C., Sousa, E.P.M., and Traina, A.J.M. (2011, January 12\u201314). Clustering analysis applied to NDVI\/NOAA multitemporal images to improve the monitoring process of sugarcane crops. Proceedings of the International Work Shop on the Analysis of Multi-temporal Remote Sensing Images\u2014MultiTemp, Trento, NJ, USA.","DOI":"10.1109\/Multi-Temp.2011.6005040"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1805","DOI":"10.1016\/j.patrec.2012.06.009","article-title":"Spatio-temporal reasoning for the classification of satellite image time series","volume":"33","author":"Petitjean","year":"2012","journal-title":"Pattern Recognit. Lett."},{"key":"ref_60","unstructured":"Zheng, Y., Gommes, R, Zhang, M., Zou, W.T., and Wu, B.F. (2015). Crop condition monitoring based on the time-series remote sensing clustering. Sin. J. Remote Sens., in preparation."},{"key":"ref_61","first-page":"551","article-title":"Crop acreage estimation using two individual samplingframeworks with stratification","volume":"8","author":"Wu","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_62","first-page":"101","article-title":"Crop planting and type proportion method for crop acreageestimation of complex agricultural landscapes","volume":"16","author":"Wu","year":"2012","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_63","first-page":"283","article-title":"Design and implementation of cropyield forecasting system","volume":"34","author":"Xu","year":"2008","journal-title":"Comput. Eng."},{"key":"ref_64","unstructured":"Du, X., Wu, B., Li, Q., Meng, J., and Jia, K. (2009, January 23\u201327). A method to estimated winterwheat yield with the meris data. Proceedings of the Progress in Electromagnetics Research Symposium(PIERS), Beijing, China."},{"key":"ref_65","unstructured":"Du, X., Wu, B., Meng, J., and Li, Q. (2009, January 4\u20138). Estimation of harvest index of winterwheat based on remote sensing data. Proceedings of the 33rd International Symposium on Remote Sensing of Environment, Stresa, Italy."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1080\/17538947.2011.623189","article-title":"Generation of high spatial and temporal resolution NDVI and its application in crop biomass estimation","volume":"6","author":"Meng","year":"2013","journal-title":"Int. J. Digit. Earth"},{"key":"ref_67","unstructured":"Office of the Chief Economist Major World Crop Areas and Climate Profiles (MWCACP), Available online:http:\/\/www.usda.gov\/oce\/weather\/pubs\/Other\/MWCACP\/index.htm."},{"key":"ref_68","unstructured":"FAO Global Information and Early Warning System on Food and Agriculture (GIEWS) Country Briefs. Available online:http:\/\/www.fao.org\/giews\/countrybrief\/index.jsp."},{"key":"ref_69","first-page":"403","article-title":"Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China","volume":"10","author":"Ren","year":"2008","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1312","DOI":"10.1016\/j.rse.2010.01.010","article-title":"A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data","volume":"114","author":"Vermote","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_71","first-page":"192","article-title":"Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models","volume":"23","author":"Kogan","year":"2013","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Huang, J., Wang, X., Li, X., Tian, H., and Pan, Z. (2013). Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA\u2019s-AVHRR. PLoS One, 8.","DOI":"10.1371\/journal.pone.0070816"},{"key":"ref_73","unstructured":"National Agricultural Statistics Service Crop Production Reports Released April 9 and May 9, 2014, Available online:http:\/\/usda.mannlib.cornell.edu\/MannUsda\/viewDocumentInfo.do?documentID=1046."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1175\/1520-0450(2003)042<1355:VOTAOR>2.0.CO;2","article-title":"Validation of TRMM and other rainfall estimates with a high-density gauge dataset for West Africa. Part II: Validation of TRMM rainfall products","volume":"42","author":"Nicholson","year":"2003","journal-title":"J. Appl. Meteorol."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1175\/2007JHM944.1","article-title":"Evaluation of TRMM multisatellite precipitation analysis (TMPA) and its utility in hydrologic prediction in the La Plata Basin","volume":"9","author":"Su","year":"2008","journal-title":"J. Hydrometeorol."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1175\/1520-0477(1997)078<0621:GDWFS>2.0.CO;2","article-title":"Global drought watch from space","volume":"78","author":"Kogan","year":"1997","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Kogan, F.N. (2002). World droughts in the new millennium from AVHRR-based Vegetation Indices. Eos Trans. AGU, 83.","DOI":"10.1029\/2002EO000382"},{"key":"ref_79","first-page":"23","article-title":"Using NOAA AVHRR and LandsatTM to estimate rice area year-by-year","volume":"12","author":"Fang","year":"1997","journal-title":"Remote Sens. Tech. Appl."},{"key":"ref_80","first-page":"23","article-title":"Operational remote sensing methods for agricultural statistics","volume":"55","author":"Wu","year":"2000","journal-title":"Acta Geogr. Sinica."},{"key":"ref_81","first-page":"1013","article-title":"China CropWatch system with remote sensing","volume":"8","author":"Wu","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_82","first-page":"78","article-title":"Extraction of crop acreage using GVG system and its precision analysis","volume":"25","author":"Jiang","year":"2002","journal-title":"J. Nanjing Inst. Meteol."},{"key":"ref_83","first-page":"46","article-title":"Development of crop yield forecasting system","volume":"24","author":"Fan","year":"2003","journal-title":"Chin. J. Agrometeorol."},{"key":"ref_84","first-page":"766","article-title":"Study of ploughed field information extraction in rice area of Thailand","volume":"18","author":"Zhang","year":"2003","journal-title":"J. Nat. Resour."},{"key":"ref_85","first-page":"602","article-title":"Operational crop yield estimating method foragricultural statistics","volume":"8","author":"Meng","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_86","first-page":"18","article-title":"A method for crop planting structure inventory and its application","volume":"8","author":"Wu","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_87","first-page":"498","article-title":"An integrated method for crop condition monitoring","volume":"8","author":"Wu","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"971","DOI":"10.13031\/2013.30055","article-title":"An integrated crop condition monitoring system with remote sensing","volume":"53","author":"Wu","year":"2010","journal-title":"Trans. ASABE"},{"key":"ref_89","first-page":"570","article-title":"GVG, a crop type proportion sampling instrument","volume":"8","author":"Wu","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_90","first-page":"645","article-title":"A short-term model of grain supply anddemand balance based on remote sensing monitoring and agriculture statistical data","volume":"8","author":"Zeng","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_91","unstructured":"Li, Q. (2008). Validation and Uncertainty Analysis of Large Area Crop Acreage Estimation with Remote Sensing. [Ph.D. Thesis, Institute of Remote Sensing Applications, Chinese Academyof Sciences]."},{"key":"ref_92","first-page":"581","article-title":"Accuracy assessment of planted area proportion using Landsat TM imagery","volume":"8","author":"Li","year":"2004","journal-title":"Sin. J. Remote Sens."},{"key":"ref_93","unstructured":"Jia, K., Li, Q., Tian, Y., Wu, B., Zhang, F., and Meng, J. (2010, January 17\u201321). Crop classification based on fusion of ENVISAT ASAR and HJ CCD data. Proceedings of the Dragon 2 Programme Middle Results (2008\u20132010), Guilin, China."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"9307","DOI":"10.1080\/01431161.2011.554454","article-title":"Vegetation classification methodwith biochemical composition estimated from remote sensing data","volume":"32","author":"Jia","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.compag.2011.07.008","article-title":"Maize acreage estimation using ENVISAT MERIS and CBERS-02B CCD data in the North China Plain","volume":"78","author":"Li","year":"2011","journal-title":"Comput. Electron. Agric."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"5774","DOI":"10.3390\/rs6065774","article-title":"Crop condition assessment with adjusted NDVI using the uncropped arable land ratio","volume":"6","author":"Zhang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_97","unstructured":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences. Available online:http:\/\/www.fao.org\/giews\/countrybrief\/index.jsp."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/4\/3907\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:44:13Z","timestamp":1760215453000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/4\/3907"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,4,1]]},"references-count":97,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2015,4]]}},"alternative-id":["rs70403907"],"URL":"https:\/\/doi.org\/10.3390\/rs70403907","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,4,1]]}}}