WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS
Water is one of the vital components of the Earth environment which needs to be frequently monitored. Satellite multispectral remote sensing image has been used over decades for water body extraction. Methodology of water body extraction can be summarized to three groups: feature extraction, supervi...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2012-07-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/181/2012/isprsarchives-XXXIX-B8-181-2012.pdf |
| Summary: | Water is one of the vital components of the Earth environment which needs to be frequently monitored. Satellite multispectral remote
sensing image has been used over decades for water body extraction. Methodology of water body extraction can be summarized to
three groups: feature extraction, supervised and unsupervised classification and data fusion. These methods, however, are of pure
mathematical and statistical approach and little of them explore essential characteristics of multispectral image which is based on
ground object radiance absorption behaviour in each sensing spectral bands. The spectral absorption characteristics of water body in
visible and infrared bands differ very much from the other ground objects. They depend only on the used spectral bands and can be
considered as invariant and sensor independent. In this paper the author proposed an application of spectral pattern analysis for water
body extraction using spectral bands green, red, near infrared NIR and short wave infrared SWIR. The proposed algorithm has been
used for water body extraction by Spot 5 and Landsat 5 TM images. Ground truth validation was carried out in Hanoi City. The
advantage of this algorithm does not base on water body extraction only but it allows to asses also water quality. Different level of
turbidity and organic matter contents could be classified by using additional index. |
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| ISSN: | 1682-1750 2194-9034 |