基于Himawari-8卫星的火点判识算法研究

Research on Fire SPOT Detection Algorithm based on the New Generation of Geostationary Meteorological Satellite

利用新一代静止气象卫星Himawari-8数据,提出一种新的自适应阈值决策树低温火点判识方法。该方法基于2.3μm和0.86μm通道数据,以晴空像元和背景像元本地化判识结果为基础进行火点识别。选取山西省作为研究区域,利用2020年4月24日和2021年2月20日数据进行验证,结果表明:①对于森林火灾初期火势较小的火点可以尽早判识(采样点最早提前40 min);②对草地、耕地上范围较小、温度较低的火点判识在时效性和准确率方面均表现良好;③新增的低温火点判识算法有效地解决了火点多判和漏判的矛盾问题,为尽早识别火点信息,实现有效的灾情监测提供了新思路。

Using the new generation of Geostationary Meteorological Satellite Himawari-8 data,a new adaptive threshold decision tree low-temperature fire spot detection algorithm is proposed.The algorithm is based on the localization recognition results of clear sky pixels and background pixels,using data at channel 2.3μm and channel 0.86μm.Taking Shanxi Province as the research area,the identification results were verified using the data on April 24,2020 and February 20,2021.The results of the new algorithm show:(1)the new algorithm can identify small fire spots earlier(sampling point 40 minutes in advance);(2)the new algorithm has better accuracy on identifying the fire spot with small range and low temperature on grassland and cultivated land;(3)the new algorithm solves the problem of false alarms and misses of fire spot,providing a new idea for identifying fire spot as soon as possible and monitoring fire disaster effectively.