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Remote Sensing Technology and Application  2008, Vol. 23 Issue (4): 398-404    DOI: 10.11873/j.issn.1004-0323.2008.4.398
    
Contrast Study on Extracting of Soil Salinization in Arid Area of Xinjiang Oasis
ZHANG Fei 1,2,3,Tashpolat•Tiyip 1,2,DING Jian-li 1,2,Ilyas.Nurmuhammat 1,2,TIAN Yuan 1,2
(1.College of Resources and Environment Science,Xinjiang University Urumqi,Urumqi 830046,China;2.Key Laboratory of Oasis Ecology,Xinjiang University Urumqi,Urumqi 830046,China|3.Graduate school of Xinjiang University with Academic Degrees Committee,Urumqi 830046,China)
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Abstract  

The non-spectral characteristics play an important role in assisting the image classification in remote sensing,as these characteristics can avoid the mistake classification made by the "the same object with different spectrum" phenomenon.The texture characteristic is one kind non-spectral characteristic.It is also helpful to improve the classification precision.In this paper,the author takes the Delta Oasis of Weigan and Kuqa rivers for example,using ETM+ data; discussing the method of extracting of soil salinization.This paper reports the classification method based on support vector machine(SVM),and introduced the fundamental theory of SVM algorithm,then incorporating of spectrum and texture information.The classification result is compared with minimum distance classification,maximum likelihood classification,neural net classification and single data source(spectrum)SVM classification qualitatively and quantitatively.The research result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification,it has high spread ability toward higher array input,the overall accuracy is 93.1795%,which increases by 3.1618% comparing with single data source SVM and increases by 4.8252% comparing with maximum likelihood classification,and increase by 7.4756% comparing with neural net classification,even increases by 11.1029% comparing wit minimum distance classification and thus acquires good effectiveness.The classification results were easier interpreted when compared with the conventional classification method.Therefore,the classification method based on SVM(Support Vector Machine)and incorporate the spectrum and texture information can be adapted to RS image classification and monitoring of soil salinization,furthermore,provides and effectives way for the things remote sensing information extraction.

Key words:  Support vector machines(SVM)      Soil salinization      Gray co-occurrence matrix      Texture information     
Received:  16 January 2008      Published:  03 November 2011
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ZHANG Fei,Tashpolat?Tiyip,DING Jian-li,Ilyas.Nurmuhammat,TIAN Yuan. Contrast Study on Extracting of Soil Salinization in Arid Area of Xinjiang Oasis. Remote Sensing Technology and Application, 2008, 23(4): 398-404.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2008.4.398     OR     http://www.rsta.ac.cn/EN/Y2008/V23/I4/398

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