Analysing PolSAR data from vegetation by using the subaperture decomposition approach

TL;DR

This paper investigates how vegetation orientation and heterogeneities affect PolSAR backscatter signatures using subaperture decomposition and polarisation analysis across multiple datasets, revealing potential overestimations in volume scattering.

Contribution

It introduces a novel application of subaperture decomposition and 3-D polarisation analysis to assess vegetation backscatter variations across different frequencies and sensor types.

Findings

Depolarising effects can be underestimated in full-resolution images.

Orientation effects significantly influence backscatter signatures.

Implications for improving polarimetric SAR decomposition models.

Abstract

A common assumption in radar remote sensing studies for vegetation is that radar returns originate from a target made up by a set of uniformly distributed isotropic scatterers. Nonetheless, several studies in the literature have noted that orientation effects and heterogeneities have a noticeable impact in backscattering signatures according to the specific vegetation type and sensor frequency. In this paper we have employed the subaperture decomposition technique (i.e. a time-frequency analysis) and the 3-D Barakat degree of polarisation to assess the variation of the volume backscatterig power as a function of the azimuth look angle. Three different datasets, i.e. multi-frequency indoor acquisitions over short vegetation samples, and P-band airborne data and L-band satellite data over boreal and tropical forest, respectively, have been employed in this study. We have argued that despite depolarising effects may be only sensed through a small portion of the synthetic aperture, they can lead to overestimated retrievals of the volume scattering for the full resolution image. This has direct implications in the existing model-based and model-free polarimetric SAR decompositions.