Development of the false alarm filtering method for GEO-KOMPSAT-2A wildfire detection product

Wildfires have caused significant damage to the economy, human health, and ecosystems over extended periods. Satellites offer advantages as wildfire detection tools because they provide near real-time, continuous observations in areas that are difficult to manage directly by humans. But in previous studies, satellite active wildfire detection products were prone to generating false alarms in areas with high reflectance, such as bare soils, urban regions, water bodies, and clouds. This issue arises because infrared channels were used for wildfire detection, but their observations include both solar and thermal radiances. In this study, we apply a calculation, based on a previous study, to wildfire detection that reduces solar reflectance radiance and propose a filtering method to eliminate false alarms occurring in cloud edge areas. South Korea, where detailed annual wildfire information is available, was selected as the study area to develop a region-specific false alarm filtering algorithm for wildfire detection product. The filtering algorithm was compared to the GEO-KOMPSAT-2A operational product using data from 62 wildfire cases that occurred in 2022. As a result, the number of false alarms was significantly reduced from 896 to 25, the False alarm ratio (FAR) decrease from 96.34–47.17% and the Probability of Detection (POD) showed a slight decrease from 53.23–45.16%. The results of this study are expected to contribute to more efficient disaster and risk management by enabling more accurate wildfire detection.