Mappping paddy rice agriculture in southern China using multi-temporal MODIS images


Information on spatial extent and seasonality of inundation and paddy rice fields are needed for water resource management, trace gases emission, and food security. In this study we reported an effort to use images from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA EOS Terra satellite to map inundation and paddy rice fields in southern China. Paddy rice fields are characterized by a period of inundation and open canopy (a mixture of surface water and rice crops). We developed a temporal profile analysis procedure that uses time series data of improved vegetation indices to identify and map inundation and paddy rice fields. The MODIS-based algorithm uses both Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI), and excludes those pixels that are covered by cloud and snow from the analysis. Permanent water body mask and digital elevation model were also used in the analysis. Using multi-temporal 8-day composite of MODIS images at 500-m spatial resolution in 2002, we generated a map of inundation and paddy rice fields in southern China. The MODIS-derived paddy rice map was compared with the other datasets of paddy rice agriculture, including the paddy rice map derived from analysis of Landsat ETM images in 1999/2000. The results from the comparison have indicated that the MODIS-based algorithm could potentially be applied at large spatial scale for mapping and monitoring of inundation and paddy rice agriculture.


Earth Sciences, Earth Systems Research Center

Publication Date


Journal Title

Joint Assembly Meeting, American Geophysical Union


American Geophysical Union Publications

Document Type

Conference Proceeding