Pixels' edges can yield useful information on physical properties of objects featured on satellite images. These properties can be derived through the use of the imagery spatial contrast techniques. To differentiate various cloud types based on their shapes, one of these techniques is applied on thermal products from a polar orbiting satellite, the National Oceanic and Atmospheric Administration/Advanced Very-High-Resolution Radiometer (NOAA-AVHRR). Edge gradients extracted from daily global cloud temperature images of this satellite and the spatial relationship between these gradients permit the distinction of nine major cloud shapes distributed along three cloud pressure levels (high, middle and low). The cloud shape differentiation method utilized is a histogram-based gradient scheme describing the occurrence of different gradients' levels (high, middle and low) in each block of pixels. A detailed analysis of the distribution of the cloud shapes obtained is conducted, and the frequency of each cloud shape is evaluated with another cloud classification method (based on cloud optical properties) for validation purposes. Finally, implications of the results obtained, on the estimation of the impact of cloud shapes variations on the recent climate are discussed.
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