An Improved Luminance Contrast Saliency Map for Burned Area Mapping Based on INSAR Coherence Difference Image

Wildfires have attracted considerable attention because of their increasing frequency and severity around the globe. Satellite remote sensing data is a valuable asset for monitoring, and mapping burned areas (BA). However, most global BA products based on optical imagery are limited by cloud coverage and not usable for cloud-prone regions. All-weather Synthetic Aperture Radar (SAR) imagery can be a complement to an optical-based counterpart. In order to exploit the value of phase information of SAR data, this paper aims to propose a framework by developing a visual saliency detection algorithm for BA mapping using Sentinel-1 Interferometric SAR (InSAR) coherence difference image. The results show that the proposed method can effectively improve the coherence difference's accuracy performance. Additionally, we also demonstrate that for C-band Sentinel-1 SAR data, both VV and VH polarized images can be used in BA mapping, but the former would provide slightly better results.