Global sentinel-1 insar coherence. Opportunities for model-based estimation of land parameters

In this paper, we assess the estimation of bio-physical land parameters from time-series of interferometric SAR coher- ence 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 di- electric properties. The recently-published global Sentinel-1 interferometric coherence dataset is used to compare model predictions with observations and evaluate the need for ad- ditional model assumptions or ancillary data sets. Space- borne lidar data acquired by GEDI are also considered to fur- ther constrain the parameter estimation. This work is partic- ularly 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