Analysis of Temporal Decorrelation in Dual-Baseline Polinsar Vegetation Parameter Estimation

Abstract

Vegetation parameters can be estimated using the single-baseline polarimetric synthetic aperture radar interferometry (POLinSAR) data based on the random volume over ground (RVoG) model. Temporal decorrelation, which is the coherence loss due to scene changes within the time between radar data acquisitions, will decrease the estimation accuracy and needs to be compensated. The RVoG+VTD model is a simple model incorporating a temporal decorrelation term into the RVoG model. The inversion of RVoG+VTD model can not perform due to the limited number of single-baseline POLinSAR observables. Dual-baseline POLinSAR approach provides more observables and hence can be used to invert the model. This paper introduces and analyzes the dual-baseline inversion procedure of RVoG+VTD model and validates them using simulated data.