BIOMASS RETRIEVAL FROM HIGH-DIMENSIONAL ACTIVE PASSIVE REMOTE-SENSINGDATA BY USING ARTIFICIAL NEURAL NETWORKS/

Retrieval of the biomass parameters from active/passive microwave remo te sensing data is performed based on an iterative inversion of the ar tificial neural network (ANN). The ANN is trained by a set of the meas urements of active and passive remote sensing and the ground truth dat a versus Day of Year during growth. Once the ANN training is complete, the ANN can be used to retrieve the temporal variations of the biomas s parameters from another set of observation data. The retrieved bioma ss include canopy height, canopy water content and dry matter fraction , and the wetness of the underlying land. Two examples for wheat and o at are illustrated. The retrieved biomass parameters agree well with t he real data of the ground truth.