Mapping Paddy Rice Biomass Using ALOS/PALSAR Imagery

Accurately estimating rice biomass and yield is important not only for rice cropping management, but also for quantitatively understanding carbon cycle in agricultural ecosystem. This study integrated a rice canopy scattering model with Genetic Algorithm Optimization Tool (GAOT) to simulate rice biophysical parameters and to estimate rice biomass from L-band, HH polarization mode ALOS/PALSAR radar imagery. Plant height and density, the two most determinant biophysical parameters related to rice biomass, could be retrieved with the error of less than 6 cm and 30/m², respectively. The simulated biomass was within adjusted residual of 200 g/m² of the measured value. The results demonstrated the potentials of new ALOS SAR data to mapping paddy rice biomass with the microwave canopy scattering model.