A Modified Approach for Mapping Forest Fire Severity Using Sentinel-2 Time Series in the Indian Himalayan Region

Forest fire is an important phenomenon that influences forest ecosystems. Mapping forest fire and its severity is important for forest fire management and restoration of fire affected areas. A study was implemented in Himalayan moist temperate forest dominated region of Indian Western Himalaya which faces frequent fire. Identification of burned area is crucial for understanding various ecological processes associated with forest fire. We mapped forest fire severity using remotely sensed images. Sentinel 2 data was used to obtain differenced normalised burn ratio (dNBR) to map burned area during 2017-2022 which was calculated as difference between pre- and post-fire normalised burn ratio. A protocol was developed to identify areas that were severely affected by fire over a long observation period. The temporal dNBR maps were classified into different fire severity classes to match with percentage of active fire points detected in burnt class by Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) to validate our classification. We observed that 74 to 92% of active fire points fall in the burnt severity classes during different years of assessment. The developed protocol will be helpful in identifying forest spatial representation of burnt severity categories to understand various ecological processes and to implement fire mitigation plans.