Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images

In this paper, we developed a new geospatial database of paddy rice agriculture for 13 countries in South and Southeast Asia. These countries have ∼ 30% of the world population and ∼ 2/3 of the total rice land area in the world. We used 8-day composite images (500-m spatial resolution) in 2002 from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS Terra satellite. Paddy rice fields are characterized by an initial period of flooding and transplanting, during which period a mixture of surface water and rice seedlings exists. We applied a paddy rice mapping algorithm that uses a time series of MODIS-derived vegetation indices to identify the initial period of flooding and transplanting in paddy rice fields, based on the increased surface moisture. The resultant MODIS-derived paddy rice map was compared to national agricultural statistical data at national and subnational levels. Area estimates of paddy rice were highly correlated at the national level and positively correlated at the subnational levels, although the agreement at the national level was much stronger. Discrepancies in rice area between the MODIS-derived and statistical datasets in some countries can be largely attributed to: (1) the statistical dataset is a sown area estimate (includes multiple cropping practices); (2) failure of the 500-m resolution MODIS-based algorithm in identifying small patches of paddy rice fields, primarily in areas where topography restricts field sizes; and (3) contamination by cloud. While further testing is needed, these results demonstrate the potential of the MODIS-based algorithm to generate updated datasets of paddy rice agriculture on a timely basis. The resultant geospatial database on the area and spatial distribution of paddy rice is useful for irrigation, food security, and trace gas emission estimates in those countries.