Accurate and rapid mapping of fire damaged areas is fundamental to support fire management, account for environmental loss, define planning strategies and monitor the restoration of vegetation. Under climate change conditions, drought severity may trigger tough fire regimes, in terms of number and dimension of fires. Year 2017 was characterized by a harsh fire season in the Mediterranean area, especially for Portugal, Italy, Spain, Croatia, Bosnia and Herzegovina. Satellite data play a major role in supporting knowledge about fire severity by delivering rapid information to map areas damaged by fire in a accurately and prompt way.
Burnt Area Index (BAI), Normalized Burn Ratio (NBR) and its relative versions have been largely employed in the past to map burnt areas from high resolution optical satellite data, employing their spectral domains. New Sentinel-2 satellites carry more spectral information recorded in the red-edge spectral region, opening the way to the development of new indexes for burnt area mapping.
This study present a processing chain developed to perform post-fire mapping using Sentinel-2 data. It makes use of a newly developed Burnt Area Index for Sentinel-2 (BAIS2), based on Sentinel-2 spectral bands to detect burnt areas at 20 m spatial resolution. The new index has been tested on various study cases in Italy for summer 2017 fires, and compared to already existing indexes for detecting burnt areas. Results show a good performance of the index and highlighted critical issues related to the Sentinel-2 data preprocessing, that have been taken into account in the development of the processing chain. Such improvements significantly reduce the number of false positives detected in the post-fire mapping, using both a single image or a multitemporal approach based on change detection.