Estimation of Vegetation Structure Parameters From SMAP Radar Intensity Observations

摘要: In this article, we present a multipolarimetric estimation approach for two model-based vegetation structure parameters (shape ${A}_{P}$ and orientation distribution ${\psi }$ of the main canopy elements). The is based on reduced observation set three incoherent (no phase information) polarimetric backscatter intensities ( $| {S}_{\mathrm{ HH}} |^{2}$ , HV}} VV}} ) combined with two-parameter discrete scatterer model vegetation. objective to understand whether confined observations contains enough information estimate from L-band radar signals. order disentangle soil scattering influences these signals ultimately perform vegetation-only retrieval shape use subpixel spatial heterogeneity expressed by covariation co- cross-polarized ${\Gamma }_{{{\mathrm{PP-PQ}}}}$ neighboring cells assume it indicative amount co-to-cross-polarized ratio ${\mu . ratio-based enables relative absolute backscatter) which more robust compared retrievals terms. application developed algorithm global Soil Moisture Active Passive (SMAP) data acquired April July 2015 indicates potential limitations estimating when no fully are available. A focus study six different regions interest, spanning land cover barren tropical rainforest, shows steady increase in toward randomly oriented volumes continuous decrease arriving at dipoles comparison independent sets height above-ground biomass confirms consistent meaningful retrieved shapes distributions represent elements matching literature results decompositions SMAP resolution. Based our findings, can be directly applied parameterizing component decompositions. This should facilitate decomposition into ground components improve (moisture roughness) under