Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B8, 181-186, 2012
https://doi.org/10.5194/isprsarchives-XXXIX-B8-181-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
28 Jul 2012
WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS
D. D. Nguyen Department of Environmental Information Study and Analysis, Institute of Geography, 18 Hoang Quoc Viet Rd., Cau Giay, Hanoi, Vietnam
Keywords: Remote sensing, Hydrology, Classification, Automation, Spectral pattern Abstract. 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.
Conference paper (PDF, 941 KB)


Citation: Nguyen, D. D.: WATER BODY EXTRACTION FROM MULTI SPECTRAL IMAGE BY SPECTRAL PATTERN ANALYSIS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B8, 181-186, https://doi.org/10.5194/isprsarchives-XXXIX-B8-181-2012, 2012.

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