Polarimetric optimization for biophysical parameter estimation

This paper explores polarization optimization of synthetic aperture radar (SAR) data, constrained to maximize some biophysical data conditions, such as the residual sum of squares (RSS). Based on a-priori information, the optimization helps to identify the polarization most sensitive (and least sensitive) to the quantity of interest, with best predictive characteristics. In this presentation, the relationship of SAR polarimetry to forest biomass is considered. The results are presented over boreal forest using DLR´s airborne E-SAR sensor data at Land P-band frequencies.