{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T05:21:54Z","timestamp":1775193714652,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2015,7,14]],"date-time":"2015-07-14T00:00:00Z","timestamp":1436832000000},"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>A large-area map of the spatial distribution of rice is important for grain yield estimations, water management and an understanding of the biogeochemical cycling of carbon and nitrogen. In this paper, we developed the Normalized Weighted Difference Water Index (NWDWI) for identifying the unique characteristics of rice during the flooding and transplanting period. With the aid of the ASTER Global Digital Elevation Model and the phenological data observed at agrometeorological stations, the spatial distributions of single cropping rice and double cropping early and late rice in the Yangtze River Delta region were generated using the NWDWI and time-series Enhanced Vegetation Index data derived from MODIS\/Terra data during the 2000\u20132010 period. The accuracy of the MODIS-derived rice planting area was validated against agricultural census data at the county level. The spatial accuracy was also tested based on a land use map and Landsat ETM+ data. The decision coefficients for county-level early and late rice were 0.560 and 0.619, respectively. The MODIS-derived area of late rice exhibited higher consistency with the census data during the 2000\u20132010 period. The algorithm could detect and monitor rice fields with different cropping patterns at the same site and is useful for generating spatial datasets of rice on a regional scale.<\/jats:p>","DOI":"10.3390\/rs70708883","type":"journal-article","created":{"date-parts":[[2015,7,14]],"date-time":"2015-07-14T10:53:35Z","timestamp":1436871215000},"page":"8883-8905","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Monitoring Spatio-Temporal Distribution of Rice Planting Area in the Yangtze River Delta Region Using MODIS Images"],"prefix":"10.3390","volume":"7","author":[{"given":"Jingjing","family":"Shi","sequence":"first","affiliation":[{"name":"Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, China"},{"name":"School of Electronic and Information Engineering, Ningbo University of Technology,  Ningbo 315016, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4627-6021","authenticated-orcid":false,"given":"Jingfeng","family":"Huang","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, China"}]}],"member":"1968","published-online":{"date-parts":[[2015,7,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11103-005-2159-5","article-title":"What it will take to feed 5.0 billion rice consumers in 2030?","volume":"59","author":"Khush","year":"2005","journal-title":"Plant Mol. Biol."},{"key":"ref_2","unstructured":"Food and Agriculture Organziation of the United Nations (2013). Statistical Yearbook 2013: World Food and Agriculture, FAO."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1029\/2001GB001425","article-title":"Combining remote sensing and ground census data to develop new maps of the distribution of rice agriculture in China","volume":"16","author":"Frolking","year":"2002","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_4","unstructured":"Huke, R.E., and Huke, E.H. (1997). Rice Area by Type of Culture: South, Southeast, and East Asia. A Review and Updated Data Base, IRRI."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"GB1009","DOI":"10.1029\/2003GB002108","article-title":"Geographic distribution of major crops across the world","volume":"18","author":"Leff","year":"2004","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1360\/03yd9033","article-title":"Study on spatial pattern of land-use change in China during 1995\u20132000","volume":"46","author":"Liu","year":"2003","journal-title":"Sci. China Ser. D: Earth Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"741","DOI":"10.1080\/01431168708948685","article-title":"Monitoring rice areas using Landsat MSS data","volume":"8","author":"McCloy","year":"1987","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2223","DOI":"10.1016\/S0273-1177(03)90546-1","article-title":"Monitoring of a rice field using Landsat-5 TM and Landsat-7 ETM+ data","volume":"32","author":"Oguro","year":"2003","journal-title":"Adv. Space Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1080\/01431169608948736","article-title":"Estimation of paddy field area using the area ratio of categories in each mixel of Landsat TM","volume":"17","author":"Okamoto","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","first-page":"125","article-title":"Study on methods of rice planting area estimation at regional scale using NOAA\/AVHRR data","volume":"2","author":"Li","year":"1998","journal-title":"J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1115","DOI":"10.1080\/01431169408954145","article-title":"Fourier analysis of multi-temporal AVHRR data applied to a land cover classification","volume":"15","author":"Andres","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3009","DOI":"10.1080\/01431160110107734","article-title":"Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data","volume":"23","author":"Xiao","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1080\/01431169208904172","article-title":"Towards continental scale crop area estimation","volume":"13","author":"Quarmby","year":"1992","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.agee.2011.06.010","article-title":"Temporal changes in rice-growing area and their impact on livelihood over a decade: A case study of Nepal","volume":"142","author":"Gumma","year":"2011","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Gumma, M.K., Nelson, A., Thenkabail, P.S., and Singh, A.N. (2011). Mapping rice areas of south Asia using MODIS multitemporal data. J. Appl. Remote Sens., 5.","DOI":"10.1117\/1.3619838"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.rse.2005.03.008","article-title":"A crop phenology detection method using time-series MODIS data","volume":"96","author":"Sakamoto","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/S0034-4257(02)00135-9","article-title":"Monitoring vegetation phenology using MODIS","volume":"84","author":"Zhang","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"466","DOI":"10.2307\/1311906","article-title":"Methane emission from rice fields","volume":"43","author":"Neue","year":"1993","journal-title":"Bioscience"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1080\/01431169308904332","article-title":"The use of multi-temporal NDVI measurements from AVHRR data for crop yield estimation and prediction","volume":"14","author":"Quarmby","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.rse.2006.06.018","article-title":"Land-cover change detection using multi-temporal MODIS NDVI data","volume":"105","author":"Lunetta","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/S0034-4257(96)00112-5","article-title":"A comparison of vegetation indices over a global set of TM images for EOS-MODIS","volume":"59","author":"Huete","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1080\/01431169608948714","article-title":"The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features","volume":"17","author":"McFeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of Normalised Difference Water Index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1016\/j.rse.2004.12.009","article-title":"Mapping paddy rice agriculture in southern China using multi-temporal MODIS images","volume":"95","author":"Xiao","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.ecolind.2015.03.039","article-title":"Mapping paddy rice areas based on vegetation phenology and surface moisture conditions","volume":"56","author":"Qiu","year":"2015","journal-title":"Ecol. Indic."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1938","DOI":"10.3390\/rs6031938","article-title":"Development of a remote sensing-based \u201cBoro\u201d rice mapping system","volume":"6","author":"Mosleh","year":"2014","journal-title":"Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1501","DOI":"10.1016\/S0277-3791(03)00080-5","article-title":"Vegetation and climate changes in the Changjiang (Yangtze river) delta, China, during the past 13,000 years inferred from pollen records","volume":"22","author":"Yi","year":"2003","journal-title":"Quat. Sci. Rev."},{"key":"ref_29","unstructured":"Vermote, E.F., and Vermeulen, A. (1999). Atmospheric Correction Algorithm: Spectral Reflectance (MOD09), MODIS Algorithm Technical Background Document, version 4.0, University of Maryland."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/S0034-4257(96)00072-7","article-title":"Use of a green channel in remote sensing of global vegetation from EOS-MODIS","volume":"58","author":"Gitelson","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.rse.2010.09.013","article-title":"Assessment of MODIS NDVI time series data products for detecting forest defoliation by gypsy moth outbreaks","volume":"115","author":"Spruce","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1495","DOI":"10.1080\/01431169308953983","article-title":"NDVI\u2014Crop monitoring and early yield assessment of Burkina Faso","volume":"14","author":"Groten","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","first-page":"4039","article-title":"Study on the regionalization of paddy rice information acquirement through remote sensing technology in China","volume":"41","author":"Sun","year":"2008","journal-title":"Sci. Agric. Sin."},{"key":"ref_34","first-page":"89","article-title":"Estimation of the rice planting area using digital elevation model and multitemporal moderate resolution imaging spectroradiometer","volume":"21","author":"Cheng","year":"2005","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1080\/014311600210254","article-title":"The 250 m global land cover change product from the Moderate Resolution Imaging Spectroradiometer of NASA\u2019s Earth Observing System","volume":"21","author":"Zhan","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","first-page":"175","article-title":"Regionalization for rice yield estimation by remote sensing in Zhejiang Province","volume":"11","author":"Xu","year":"2001","journal-title":"Pedosphere"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/7\/8883\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:49:09Z","timestamp":1760215749000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/7\/8883"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,7,14]]},"references-count":36,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2015,7]]}},"alternative-id":["rs70708883"],"URL":"https:\/\/doi.org\/10.3390\/rs70708883","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,7,14]]}}}