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.