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Spatial and Temporal Varying Thresholds for Cloud Detection in Satellite Imagery

机译：卫星影像中云检测的时空变化阈值

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A new cloud detection technique has been developed and applied to both geostationary and polar orbiting satellite imagery having channels in the thermal infrared and short wave infrared spectral regions. The bispectral composite threshold (BCT) technique uses only the 11 micron and 3.9 micron channels, and composite imagery generated from these channels, in a four-step cloud detection procedure to produce a binary cloud mask at single pixel resolution. A unique aspect of this algorithm is the use of 20-day composites of the 11 micron and the 11 - 3.9 micron channel difference imagery to represent spatially and temporally varying clear-sky thresholds for the bispectral cloud tests. The BCT cloud detection algorithm has been applied to GOES and MODIS data over the continental United States over the last three years with good success. The resulting products have been validated against "truth" datasets (generated by the manual determination of the sky conditions from available satellite imagery) for various seasons from the 2003-2005 periods. The day and night algorithm has been shown to determine the correct sky conditions 80-90% of the time (on average) over land and ocean areas. Only a small variation in algorithm performance occurs between day-night, land-ocean, and between seasons. The algorithm performs least well. during he winter season with only 80% of the sky conditions determined correctly. The algorithm was found to under-determine clouds at night and during times of low sun angle (in geostationary satellite data) and tends to over-determine the presence of clouds during the day, particularly in the summertime. Since the spectral tests use only the short- and long-wave channels common to most multispectral scanners; the application of the BCT technique to a variety of satellite sensors including SEVERI should be straightforward and produce similar performance results.
机译：已经开发了一种新的云探测技术，并将其应用于在热红外和短波红外光谱区域中具有通道的对地静止卫星和极地轨道卫星图像。双光谱复合阈值（BCT）技术仅使用11微米和3.9微米通道，以及从这些通道生成的合成图像，通过四步云检测过程以单像素分辨率生成二进制云掩模。该算法的一个独特方面是使用11微米和11-3.9微米通道差异图像的20天合成来表示双光谱云测试的时空变化的晴空阈值。在过去三年中，BCT云检测算法已应用于美国大陆的GOES和MODIS数据，并取得了成功。已针对2003-2005年各个季节的“真实”数据集（通过从可用卫星图像中手动确定天空条件生成的数据）对所得产品进行了验证。事实证明，白天和黑夜算法可以在陆地和海洋区域（平均）的80-90％的时间内（平均）确定正确的天空条件。在昼夜之间，陆地海洋之间和季节之间，算法性能只有很小的变化。该算法执行效果最差。在冬季，只有80％的天空条件正确确定。发现该算法在夜间和低太阳角时（对地静止卫星数据中）无法确定云，并且在白天（尤其是在夏季）会过度确定云的存在。由于光谱测试仅使用大多数多光谱扫描仪共有的短波和长波通道； BCT技术在包括SEVERI在内的各种卫星传感器上的应用应该简单易行，并产生相似的性能结果。

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