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Cloud screening algorithms often use fixed thresholds for reflectances and temperatures and are not applicable to regions with a great varibility in surface reflectance characteristics. A dynamic threshold algorithm was developed for application to a broad spectrum of earth surfaces, such as desert areas with very high reflectances and areas with dense vegetation. No a priori information is needed to activate the unsupervised algorithm. Using the maximum Normalized Difference Vegetation Index (NDVI) composites of a ten-day period, the corresponding reflectance and temperature maps are used as dynamic thresholds. Empirically derived nadir correction factors reduce the influence of surface anisotropy and tighten the algorithm considerably. Thus the only use of reflectance data results in a reliable, surface independent, cloud screening. Additionally, tests with thermal channels can be applied for confirmation and classification of questionable mixed pixels. Since there is no need for input data, the method can be used on a near global scale. The algorithm was developed for NDVI evaluation. No attempts were made so far to distinguish between clouds and snow or ice. (C) 1997 COSPAR.