静止卫星图像热带气旋云系自动识别

Tropical cyclone auto-recognition from stationary satellite imagery

目的热带气旋对我国东南沿海地区国民经济和人民生命财产威胁巨大,静止卫星云图是热带气旋实时监测的主要数据源。热带气旋在卫星云图上的纹理特征与其他云系相似度高,为气旋云系的自动准确提取带来困难。本文在矢量矩概念的基础上,提出旋转系数的概念来表征热带气旋的形态本质特征,从而实现热带气旋的自动识别。方法建立了基于静止卫星图像,运用最大类间方差法确定目标云系分割阈值,结合云系面积和亮温分布特性,利用旋转系数进行热带气旋云系的自动识别。结果以1211台风海葵为例,在台风生成发展期、成熟期以及消亡期内,进行了改进前后方法识别率的对比实验,统计发现改进方法的识别率分别为76%、95%、78%,均高于原始方法的59%、90%、63%。结论实验结果表明,改进方法分割的热带气旋云系更为完整,对各阶段的热带气旋云系识别率均更高。

Objective Tropical cyclones pose a serious threat to the economy as well as people＇s life and property in the southeast coastal areas of China. Stationary satellite imagery is the main data source for tropical cyclone real-time monitoring. On the satellite cloud image, the textures of tropical cyclones are similar to that of other cloud structures, which makes the automatic extraction of tropical cyclones difficult. Base on a vector square, a concept of rotation coefficient is proposed to describe the characteristics of tropical cyclones. Additionlly, a tropical cyclone auto-recognition method is also presented. Method The Otsu algorithm is used to obtain the segmentation threshold, then rotation coefficient combined with cyclone area and brightness temperature features are implied to recognize tropical cyclone. Result The contrast experiment of the original vector square method and the improved method was carried on, using the imagery of typhoon HAIKUI. The statistics results generated throughout the life cycle stage shows that, the recognition rate of the improved method are 76% , 95% and 78% respectively, which are higher than that of the original＇ method. Conclusion Experiments show that relative to the vector square algorithm, the segmentations of tropical cyclone are more complete and the recognition rate of tropical cyclones in different development stages is higher.