Cloud and ice detection using NOAA/AVHRR data

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In the polar region, it is difficult to discriminate between clouds and the ground surface from satellite visible or infrared data, because of the high albedo and low surface temperature of snow and ice cover. In this paper, a method to classify cloud, sea ice and ground is proposed. This study is based upon analysis of the NOAA/AVHRR infrared images in Antarctica. The algorithm consists of two major approaches: extraction of image features and a classification algorithm. A minimum distance classifier was used to classify that region into one of three categories using five image features. To improve the classification accuracy, threshold boundaries for minimum distance classifier were changed. Both classified and misclassified areas were decreased with increasing the threshold levels.

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