The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in China.Paddy rice fields were extracted by identifying the unique char-acteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar regionalization.The characteristic could be reflected by the enhanced vegetation index(EVI) and the land surface water index(LSWI) derived from MODIS sensor data.Algorithms for single,early,and late rice identification were obtained from selected typical test sites.The algorithms could not only separate early rice and late rice planted in the same fields,but also reduce the uncertainties.The areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics,and the spatial matching was examined by ETM+(enhanced thematic mapper plus) images in a test region.Major factors that might cause errors,such as the coarse spatial resolution and noises in the MODIS data,were discussed.Although not suitable for monitoring the inter-annual variations due to some inevitable factors,the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale,and they might provide reference for further studies.
Hua-sheng SUNJing-feng HUANGAlfredo R. HUETEDai-liang PENGFeng ZHANG
The tasseled cap transformation of remote sensing data has been widely used in agriculture,forest,ecology,and landscape.In this paper,tasseled cap transformation coefficients appropriate for data from a new sensor(China & Brazil Earth Resource Satellite(CBERS-02B)) are presented.The first three components after transformation captured 98% of the four-band variance,and represent the physical characteristics of brightness(coefficients:0.509,0.431,0.330,and 0.668),greenness(coefficients:0.494,0.318,0.324,and 0.741),and blueness(coefficients:0.581,0.070,0.811,and 0.003),respectively.We hope these results will enhance the application of CBERS-02B charge-coupled device(CCD) data in the areas of agriculture,forest,ecology,and landscape.
