融合光谱阈值与图像技术的静止卫星夜间云检测方法

Geostationary satellite nighttime cloud detection method by fusing spectral threshold and image techniques

针对夜间云检测问题,本文基于静止气象卫星Himawari-8影像数据,分析了云像元光谱特征与图像特征,提出了融合光谱阈值与图像技术的静止卫星夜间云检测方法,实现了静止卫星夜间云的快速、准确检测。利用MODIS云产品和CALIPSO雷达数据,对云检测结果进行定性分析与定量验证。结果表明:①云检测结果与MODIS的云产品MYD06分布基本一致;②算法夜间平均云检测精度达到80.3%;③不同季节夜间的云检测精度随季节变化较明显,夏季最高达到83.3%,可以区分不同季节夜间的云与非云区域。因此,融合光谱阈值与图像技术的静止卫星夜间云检测方法能有效实现夜间云检测,为夜间云检测应用提供了新思路。

To address the problem of nighttime cloud detection,based on the geostationary meteorological satellite Himawari-8 image data,we analyze the spectral characteristics of cloud image elements and image features,and propose a geostationary satellite nighttime cloud detection method that integrates spectral thresholding and image technology,realizing the rapid and accurate detection of geostationary satellite nighttime clouds.Using MODIS cloud products and CALIPSO radar data,the cloud detection results are qualitatively analyzed and quantitatively verified.The results show that:①The cloud detection results are basically consistent with the distribution of MODIS‘s cloud product MYD06;②The algorithm‘s average cloud detection accuracy at night reaches 80.3%;③The cloud detection accuracy at night in different seasons varies more obviously with the seasons,and reaches up to 83.3%in summer,which can distinguish between cloudy and non-cloudy regions at night in different seasons.Therefore,the geostationary satellite nighttime cloud detection method that integrates spectral thresholding and image technology can effectively realize nighttime cloud detection and provides a new idea for nighttime cloud detection applications.