Multifrequency microwave emission for estimating optical depth and vegetation biomass

Vegetation features have been assessed by using microwave radiometric data (AMSR-E/2, SMAP) in order to retrieve vegetation biomass maps on a global scale. The tau-omega model has been used for estimating the vegetation optical depth (tau, ?) from microwave data at different frequencies. An algorithm based on Artificial Neural Networks (ANN) and able to ingest data from different frequency channels has been implemented for the inversion of the model and the retrieval of vegetation biomass. The algorithm validation, carried out on the available experimental data, confirmed that microwave emission, and in particular the use of the two polarizations, H and V, can be legitimately used to produce vegetation maps on a global and local scale by separating several levels of biomass, without any need of further information from other sensors.