An Improved Forest Fire Monitoring Algorithm With Three-Dimensional Otsu

Forest fires can destroy millions of acres land at shockingly fast speeds. The forest fire points identification algorithm is the most critical step in monitoring process. Most traditional methods use fixed thresholds, ignoring background pixels, and have low recognition rates, which could lead to many problems, such as false reporting rate. This paper proposes tests an adaptive using Himawari-8 data. By calculating three-dimensional histogram brightness temperature, threshold that automatically identify potential obtained. Based on this Otsu method, contextual test has also been adopted specify points. experimental results show omission rate improved about 10% lower than previous small-scale incidents. quickly effectively extract point information, it sensitive small low-temperature fires, provides efficient means for disasters.