Published Paper Details:

This study delves into the application of multispectral imagery for forest fire monitoring, aiming to enhance early detection, assessment, and management strategies through remote sensing techniques. Key components include an exploration of multispectral image properties, an introduction to Landsat-8 satellite technology, spectral bands analysis, and various applications of multispectral imagery, particularly in forestry. The study examines species identification, deforestation monitoring, and fire detection and management, employing methods such as polygon area index extraction and pattern analysis. Notably, the utilization of vegetation indices like NDVI, NBR, and dNBR enables effective prediction and detection of forest fires. Additionally, through a case study in Simlipal, Orissa, implementation using QGIS software demonstrates practical application and validation of methodologies. The study contributes novel insights into forest fire assessment, highlighting the significance of multispectral imagery in understanding fire impacts. By analyzing average NBR values, the study discerns areas affected by forest fires, providing critical data for post-fire assessment and mitigation efforts. Overall, this research advances forest fire monitoring capabilities, aiding in ecosystem preservation and safeguarding lives and property