Abstract
Accurate estimation of rice biomass plays a role in crop growth monitoring and agricultural carbon cycle. Dual- polarization Radarsat-2 data were used in this study for rice biomass inversion. Artificial neural network (ANN) method has been applied to simulate the relation between rice canopy parameters (height, moisture content and biomass etc.) and radar backscattering coefficients. By comparing the network training performance and RMSE of different polarization combinations, HV data had better accuracy which was selected as input of the network for biomass inversion. The distribution of rice biomass was also mapped at regional scale. This study indicated that Radarsat-2 SAR data could be used to estimate rice biomass with the root mean square error (RMSE) of <108 g/m 2 .
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