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Proceedings Paper

The universal cloud detection algorithm of MODIS data
Author(s): Wei Li; Deren Li
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Paper Abstract

In order to extract objective information more effectively, cloud should be removed from these remote sensing images contaminated by clouds. High accurate and automatic detection of clouds in satellite multi-spectral data lays a good foundation for the cloud classification or cloud removing. This paper is established in studying a simple, quick, automatic and efficient cloud detection algorithm based on spectral characteristic for different earth's surface. The authors take account of the spectrums specificity of different objects (cloud, snow, desert, land, plateau, vegetation, water and so on) and the MODIS instrument channel characteristic. We experiment on a lot of MODIS data including different times (spring, summer, autumn and winter) and different earth's surface (snow, desert, land, plateau, vegetation, water and so on). The experimental results indicate that the multi-spectral synthesis algorithm of the composite normalization algebraic operation for cloud detection is very useful. It can detect most clouds of MODIS data, including very thin cloud, on the different earth's surfaces, especially snow and desert.

Paper Details

Date Published: 28 October 2006
PDF: 6 pages
Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64190F (28 October 2006); doi: 10.1117/12.712722
Show Author Affiliations
Wei Li, Wuhan Univ. (China)
Deren Li, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 6419:
Geoinformatics 2006: Remotely Sensed Data and Information
Liangpei Zhang; Xiaoling Chen, Editor(s)

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