Information characteristics and band combination of Landsat TM RS image used to terrestrial surface evolution in mining area

Pei-jun DU; Tao Fang; Da-zhi GUO; Pengfei Shi

doi:10.1117/12.477154

31 July 2002 Information characteristics and band combination of Landsat TM RS image used to terrestrial surface evolution in mining area

Pei-jun DU, Tao Fang, Da-zhi GUO, Pengfei Shi

Author Affiliations +

Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477154
Event: Second International Conference on Image and Graphics, 2002, Hefei, China

Abstract

Landsat TM image is the most popular and universal RS information source, and got wide uses in different fields such as resource investigating, environment monitoring, urban planning, disaster preventing and as on. Although TM image has got wide applications, its use in mining area is still in experiment and beginning stage because mining area is a kind of special and complex geographic region. One of the most important issues is to study the information charaéteristics and determine the most effective band combinations oriented to given region and task. In this paper, Xuzhou mining area, located in Northern Jiangsu Province, is taken as the studying area, and Terrestrial Surface Evolution (TSE) as the studying task. According to the specific condition of studying area, the information characteristics of each band of TM image and relations between different bands are analyzed by selecting different sampling area, and relative rules are given. After that, band combination is discussed and the information content is used as the judging rule. Because more bands will require more computer resource and is low speed and cost consuming, three-band combination is used widely. It is found that in all three-band combination schemes, the combination of Band 3, Band 4 and Band 5 is the most effective. Finally, Genetic Algorithm (GA) is used to the band selection in multi-band RS image, and it proved that GA is an effective method to determine the optimal band combination, especially for multi-spectrum and super-spectrum RS information source, and GA is also a good optimized algorithm in Geoscience.

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Pei-jun DU, Tao Fang, Da-zhi GUO, and Pengfei Shi "Information characteristics and band combination of Landsat TM RS image used to terrestrial surface evolution in mining area", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); https://doi.org/10.1117/12.477154

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KEYWORDS

Mining

Remote sensing

Earth observing sensors

Landsat

Genetic algorithms

Statistical analysis

Environmental monitoring

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