基于多灰度共生矩阵特征值的黄渤海白天海雾识别算法

本文基于多灰度共生矩阵特征值，即相关性、对比度、同质性和能量，进行联合海雾遥感判识，提出一种高准确率黄渤海白天海雾识别算法。采用第二代静止气象卫星FY-4A可见光、近红外和红外数据，将该算法应用于黄渤海区域白天海雾判识，并利用2019—2020年沿黄渤海气象站点能见度实测数据及CALIPSO卫星数据产品对本算法识别结果进行精度验证。结果表明：海雾识别平均检测率(POD)为92%,误报率(FAR)为27%,临近成功指数(CSI)为69%,可以实现对海雾的动态监测，为海上交通等领域提供较好的数据支持。

Daytime sea fog recognition algorithm over the Yellow Sea and Bohai Sea based on multi-gray co-occurrence matrix eigenvalues

Based on the characteristic values of multi-gray co-occurrence matrix,namely correlation,contrast,contrast sub-matrix and entropy,this paper carried out joint sea fog remote sensing identification,and proposed a high accuracy algorithm for daytime sea fog identification over the Yellow Sea and Bohai Sea area of China.By using visible,near infrared and infrared data of FY-4A,the second generation of geostationary meteorological satellite,the algorithm was used to identify sea fog over the Yellow Sea and Bohai Sea area of China.The visibility data measured by meteorological stations along the Yellow Sea and Bohai Sea during 2019-2020 and CALIOP satellite data products were used to verify the accuracy of remote sensing recognition products.Results show that:the sea fog recognition algorithm is applied to FY-4A data,recognition results and the measured visibility site data accuracy of inspection,the sea fog recognition average shooting (POD) was 92%,the missed detection rate (FAR) was 27%,and the absolute success index (CSI) was 69%.The algorithm can realize the dynamic monitoring of sea fog and provide better data support for maritime traffic and other fields.