Many applications using hyperspectral data require cloud-free conditions; a simple cloud cover detection algorithm can be a useful tool to these efforts. Also, the application of a cloud cover detection algorithm on-board the spacecraft, prior to downlink of collected scenes, can provide considerable savings in downlink resources and processing time.
This presentation begins with a simple cloud cover algorithm which utilizes VNIR (0.4 - 1.0 Ám) channels only and expands to include more complete cloud characterization algorithms which also use both NIR and SWIR (1.0 - 2.5 Ám) channels to discriminate cloud types and cloud/surface features. The algorithms are applied to a variety of Hyperion scenes which depict various cloud types, surface features and seasonal conditions. An attempt is made to contrast these algorithms in terms of computational complexity versus performance.