Authors: Dr. Kavita Sharma, Rahul Mehta
Abstract: Forest fires represent a critical ecological disaster, resulting in significant environmental, economic, and social losses. The integration of satellite-based remote sensing technologies offers a rapid, large-scale, and efficient solution for detecting, monitoring, and assessing fire events. This paper presents an in depth study on forest fire detection and damage assessment using multi spectral and thermal satellite imagery, focusing on the application of advanced algorithms such as Normalized Burn Ratio (NBR) and thermal anomaly detection. The methodology employs data from sensors like MODIS, VIIRS, and Sentinel-2 to identify active fire locations, estimate burnt areas, and evaluate post-fire vegetation loss. A case study on the 2023 Uttarakhand forest fire event demonstrates the efficacy of the approach, highlighting the advantages of remote sensing over traditional ground-based monitoring. This study emphasizes the importance of integrating satellite imagery with GIS based analytics to develop early warning systems, thus minimizing the ecological and socio-economic impact of forest fires.
Keywords: Forest fire detection, Remote sensing, Satellite imagery, Burn severity, Damage assessment, NBR index, Thermal anomaly detection
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