Indirect estimation of vegetation contribution to microwave backscatter via triple-frequency sar data
IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM(2023)
Abstract
A coupled snow physics-radiative transfer forward-inversion modeling system was applied over snow-covered terrain in Grand Mesa and the Senator Beck Basin, Colorado, USA to estimate vegetation contributions to the total backscatter from the ground-snow-vegetation system from dual-frequency airborne SnowSAR (X- and Ku-bands) and Sentinel-1 C-band measurements. A simplified but comprehensive first-order microwave emission model (MEMLS-V) was iteratively inverted by a global optimizer using simulated annealing to retrieve unknown parameters and backscatter components from double-bounce, snowpack volume, and snow-ground interface. The retrieved parameters demonstrate high correlation with the observed SnowSAR signal dynamics tied to vegetation and snowpack heterogeneities. This suggests that the forward-inversion system accounting for complex multiple scattering within the ground-snow-vegetation system reliably regulated compensation effects of vegetation and backscatter at the snow-ground interface. The findings have useful practical implications for retrieving large-scale SWE in the northern hemisphere boreal forests from satellite-based radar measurements.
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Key words
forward-inversion modeling system,MEMLS,simulated annealing,SnowSAR,vegetation heterogeneities
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