Hyperspectral Remote Sensing of Forest Fire Breakouts: A Review

Ecosystems, human lives, and property are all seriously threatened by wildfires, hence effective monitoring and management techniques are required. Hyperspectral remote sensing has emerged as a promising tool for detecting and monitoring forest fire breakouts due to its ability to capture detailed spectral information across a wide range of wavelengths. However, despite its potential, several challenges hinder its widespread application in this domain. Challenges include the complexity of spectral data analysis, limited spatial resolution, and the need for robust algorithms for fire detection and monitoring. Existing works in hyperspectral remote sensing of forest fires have made strides in addressing these challenges but are often limited in scope or lack comprehensive analyses. Thus, there is a pressing need for a systematic review that consolidates existing knowledge, identifies gaps, and proposes avenues for future research. This paper aims to fill this gap by providing a comprehensive review of hyperspectral remote sensing techniques for forest fire breakout detection and monitoring. We discuss the key challenges, methodologies, and findings from previous studies, and highlight areas requiring further investigation. By synthesizing existing literature, this review aims to guide researchers and practitioners towards more effective strategies for forest fire management and mitigation.