Global Sentinel-1 Insar Coherence: Opportunities for Model-Based Estimation of Land Parameters

Abstract

In this paper, we assess the estimation of bio-physical land parameters from time-series of interferometric SAR coherence supported by a physical model. The random-motion-over-ground model (RMoG) is revisited to partially capture the short-and long-term temporal variability of the coherence caused by motion of the scatterers and changes in their dielectric properties. The recently-published global Sentinel-1 interferometric coherence dataset is used to compare model predictions with observations and evaluate the need for additional model assumptions or ancillary data sets. Space-borne lidar data acquired by GEDI are also considered to further constrain the parameter estimation. This work is particularly relevant to upcoming SAR missions such as NISAR and ROSE-L that will generate global and dense time-series of interferometric temporal coherence at L-band. © 2022 IEEE.