MISR Cloud Detection Over Ice and Snow Based on Linear Correlation Matching

Topics:
Electrical and Electronic
Tags:
Detection,
Engineering
Source:
University of California, Berkeley

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Overview: Cloud detection is a crucial step in any climate modelling or prediction. Multi-angle Imaging Spectro-Radiometer (MISR) was launched in 1999 by NASA to provide 9 angle and 4 band data to retrieve or estimate the cloud height and hence cloud detection. However, cloud detection even with MISR data has been proven very difficult over ice and snow. In this paper, they bypass the cloud height estimation step to directly tackle cloud detection by using features of ice and snow (no cloud) pixels from different MISR angles. They propose the linear correlation matching classification (LCMC) algorithm based on Fisher linear correlation tests.

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Format: PDF | Size: 709KB | Date: Oct 2003 | Pages: 14


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