基于FY2E可见光波段的北部湾白天海雾检测

利用2012年国产FY2-E静止卫星数据,结合地面能见度观测资料,分析北部湾地区晴天海雾、云、洋面的辐射性质、光谱及纹理特征,利用面向对象分类方法对白天海雾进行检测提取。结果表明:FY2-E卫星影像对北部湾地区晴天海雾的区分度较高,其光谱及纹理特性与洋面、中高云多无交叠现象;但大雾与低云区有部分混淆。利用面向对象分类方法,在选择合适分割尺度的基础上根据光谱Spectral_Mean和纹理Texture_Mean两个影像特征可将海雾进行有效分离。精度分析结果表明,2012年全年晴空海雾监测误警率为9.1%,命中率为76.9%,成功指标为71.4%,总体监测效果较理想。

Beibuwan Sea Fog Detection using FY2E Visible Band Images

In this paper, domestic FY2E geostationary satellite data, combining with ground visibility observation data are used to analyze radiation, spectrum and texture features of sea fog, cloud and ocean of sunny days. Then, object-oriented classification method is applied to sea fog detection and extraction. The results show that: FY2E satellite images possess a relative strong ability to distinguish of sea fog. Overlap regions of spectrum and texture features between sea fog and middle/high clouds and sea surface are rare but low cloud area and fog are easily to confuse in some regions. With object-oriented classification method and appropriate segmentation scale, sea fog can be effectively separated based on spectrum feature of spectral_mean and texture feature of texture_mean. The overall sea fog monitoring effect for the whole year 2012 is ideal with false alarm ratio 9.1%, probability of detection 76.9%, critical success index 71.4%.