Estimation of Vegetation Structure Parameters From SMAP Radar Intensity Observations

T. Jagdhuber, C. Montzka, C. López-Martínez, M. J. Baur, M. Link, M. Piles, N. N. Das and F. Jonard, “Estimation of Vegetation Structure Parameters From SMAP Radar Intensity Observations,” in IEEE Transactions on Geoscience and Remote Sensing, Early Access, 2020

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

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