Separating the Influence of Vegetation Changes in Polarimetric Differential SAR Interferometry

Abstract

Soil moisture and wet biomass changes between two non-instantaneous SAR observations markedly affect the displacement estimates obtainable with Differential SAR Interferometry (DInSAR). The separation, the modelling of these influences besides their uncoupling from the displacement signal and atmospheric disturbances are still unsolved issues for several repeat-pass interferometric applications. This paper focuses on the separation of vegetation changes from the other phase contributions affecting repeat-pass measurements over vegetated areas. These phase terms mainly relate to changes in soil moisture, atmospheric delays, and surface deformation. The separation is achieved with a first-order scattering solution decomposing the observed HH and VV DInSAR phases in the sum of several phase terms. The latter mainly consider changes in soil surface scattering and in the two-way propagation through a vertically-oriented vegetation canopy. No assumption is made on the spatiotemporal evolution of the displacement and atmosphere. The overall approach is tested on an L-band airborne SAR dataset acquired over an agricultural area. Upon calibration, the model allows for estimating changes in wet biomass based on the non-zero HH-VV D In SAR phase difference observed over several bi refringent agricultural fields. The obtained biomass estimates provide then a correction for the effect of vegetation changes on the observed HH and VV D In SAR phases. Deprived of the vegetation contribution, the remainder phase terms can be more easily explored for further analyses, e.g. estimation of soil moisture changes and/or surface movements in vertically-oriented vegetated areas.