Combing Wildfire Danger Index and Geo-Kompsat-2A Geostationary Meteorological Satellite Data for Wildfire Detection

The exploration of wildfire detection stands as a crucial part within the realm of wildfire prevention and control. However, previous studies have often leaned heavily only on remote sensing data to detect wildfires, overlooking essential factors like slope, wind speed, fuel moisture content, and other variables closely tied to wildfires, leading to a decline in wildfire detection accuracy. To fill this gap, this study focused on wildfire detection from the Geo-Kompsat-2A satellite remote sensing data with the consideration of a wildfire danger index (WDI). The WDI was produced based on wildfire-related weather, fuel, and topography factors, including wind speed, precipitation, fuel moisture content, slope, aspect, elevation, temperature, relative humidity, and leaf area index. This study shows that by consideration of WDI, the wildfire detection accuracy was researched to FI = 0.64, which is higher than the result that ignored the WDI (FI =0.22). This advancement underscores the efficacy of our approach in bolstering the precision of wildfire detection.