Near Real-Time Wildfire Detection in Southwestern China Using Himawari-8 Data

Wildfire, one of the most serious disasters in the world, making a huge threat to local economic development and residents' life and property safety. Therefore, it is crucial to realize near real time wildfire detection in specific high wildfire risk area. Himawari-8 is a state of art Geostationary Orbit Satellites (GOS), which can realize near-real time wildfire detection and dynamic monitoring of wildfire changes. In this study, three features strategies: spectral, spectral calculated and spectral with spatial were used to extract features from Himawari-8 and Topography data. Next, Random Forest models were trained by these features. And then, we evaluated models on Himawari-8 data generated in March 29, 2020 6:10 UTC, March 30, 2020 5:50 UTC, March 31, 2020 5:30 UTC and April 1,2020 5:50 UTC to detect specific wildfire events in Southwestern China. The results showed an overall precision of 64.24%, 64.08% and 68.07%, and an overall F1-score of 0.737, 0.677, 0.724 based on three different features strategies. This study proved that our models have the ability to detect wildfire point accurately, and model with strategy.3 performed the best when considering precision, omission and F1-score.