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Proceedings Paper

A new method for MODIS cloud classification
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Paper Abstract

A new technique called the local region of influence (LROI) scheme for supervised cloud classification of the Moderate Resolution Imaging Spectroradiometer (MODIS) is proposed. The classification of each observation is performed within the LROI, where the center of each class is calculated as a weighted average of its training class members with respect to each new observation. The probability of each class is assigned to each observation. The proposed LROI scheme is applied to the MODIS radiances observed from the scenes of clear skies, ice clouds, or water clouds. The classification results are compared with those from the maximum likelihood (ML) classification method, the multicategory support vector machine (MSVM) and the operational MODIS cloud mask algorithm. The lowest misclassification error rates show the advantage of the LROI scheme.

Paper Details

Date Published: 29 August 2005
PDF: 7 pages
Proc. SPIE 5890, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: Numerical Atmospheric Prediction and Environmental Monitoring, 58900X (29 August 2005); doi: 10.1117/12.619885
Show Author Affiliations
Bormin Huang, CIMSS, Univ. of Wisconsin-Madison (United States)
Steven A. Ackerman, CIMSS, Univ. of Wisconsin-Madison (United States)
W. Paul Menzel, NOAA, NESDIS (United States)


Published in SPIE Proceedings Vol. 5890:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: Numerical Atmospheric Prediction and Environmental Monitoring
Hung-Lung Allen Huang; Hal J. Bloom; Xiaofeng Xu; Gerald J. Dittberner, Editor(s)

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