A Self-Adaptive Wildfire Detection Algorithm with Two-Dimensional Otsu Optimization

Abstract

The gradual increase in wildfires has caused frequent trips and outages along electrical transmission lines, which is a serious threat to the operational stability of power grids. A self-adaptive wildfire detection algorithm has been developed and tested in this paper. Most of existing wildfire detection methods employed fixed thresholds to identify potential wildfire pixels while the background pixels were ignored. By calculating two-dimensional histogram of the brightness temperatures of mid-infrared channel, the threshold selection is self-adaptive and potential pixels containing scenes of fire can be distinguished automatically. Based on the two-dimensional Otsu method and contextual test algorithm, an improved wildfire detection algorithm that uses multitemporal Visible and Infrared Radiometer (VIRR) data is described. The wildfire detection results within three kilometers of electrical transmission lines demonstrate the effectiveness of the proposed method, which has accurate low-temperature wildfire detection ability.