Damage mapping based on coherence model using multi-temporal polarimetric-interferometric UAVSAR data

This study aims to evaluate the potential of coherent change detection using multi-temporal polarimetric interferometric SAR data. One of the limitations in damage area extraction is that the decorrelation caused by the disaster is commonly coupled with the natural changes. Also, the interpretation of the coherence is troublesome and requires the coherence model. The approach used in this study is based on the modified coherence model for a case of long-temporal and zero-spatial baseline. The inversion processes yield the temporal decorrelation contributions of ground and volume, respectively, having the physical meaning. We additionally applied simple statistical probability estimation method for the damage area to isolate the contributions of disaster from the natural changes. In this study, we used UAVSAR data acquired over Lake fire which occurred in June, 2015.