Biomass mapping using biophysical forest type characterisation of SAR polarimetric images

Statistics – Applications

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Forests

Scientific paper

Studies on the relationship between biomass and radar backscatter have relied on field data to construct empirical relationships with radar backscatter that can be used for biomass estimations and mapping. In general, inversion of radar data for biomass estimations is limited by the variations on backscatter produced by structural parameters and soil moisture and limited to a certain maximum biomass level dependent on the structural class. In this work we created biomass maps of two study sites at the Colombian Amazon (Guaviare and Araracuara) by using results from polarimetric classification algorithm that combines power, phase and correlation of C, L and P band of AirSAR data. Two different approaches were used. For the Guaviare site, (dry and flat) the biomass classes selected are related to Land Cover types and an empirical relationship between biomass and the average backscatter (LHV+PRR)/2) is used to create the biomass map. High consistency with the cover map is found. For the Araracuara site (hilly and flooded) a biomass map is created by reclassifying a biophysical forest structural map with biomass values obtained from field available data. Field data is used to validate maps and to study the behavior of radar polarimetric signatures according to different forest structures. A new approach of analysis is based on the description of the polarimetric coherence according to a physical explanation of the wave-object interactions. The same type of analysis is used to study systematically the influence of different forest structural parameters and soil moisture conditions on the polarimetric signatures. Simulated radar data from the UTARTCAN backscatter model is used.

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