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- W2378611355 abstract "Xinjiang is the most desertification affected province in China.And desertification information extraction is one of the difficulties of remote sensing thematic information extraction.So to explore suitable desertification remote sensing classification method can provide support for the policy-making of relevant departments.In this paper,TM ETM remote sensing image is used to compare applications of several major classification methods——Maximum likelihood,minimum distance,decision trees,etc.,in desertification classification.The results showed that: ①Traditional maximum likelihood classification method is better than SVM,the minimum distance and decision tree method at accuracy and plot effects.Total classification accuracy and Kappa coefficient of maximum likelihood classification method respectively reached to 96.43% and 0.95.The classification accuracy reduced with the increase of priori probability.It has low degree of confusion,clear results figure,and it is able to respond to the real desertification distribution.②SVM radial basis function classification can achieve the purposes of classification.The classification accuracy gradually increased with increases of γ.It has a little more serious confusion classification,and can reflect real desertification distribution.③Minimum distance has lower classification accuracy,and serious missing phenomenon.It can reflect desertification distribution in a certain extent.④Decision tree classification has lower classification accuracy too,and complex filter of sub-index but it can not reflect real desertification distribution." @default.
- W2378611355 created "2016-06-24" @default.
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- W2378611355 date "2012-01-01" @default.
- W2378611355 modified "2023-09-27" @default.
- W2378611355 title "Comparative Analysis of Remote Sensing Classification Method about Desertification——Take the downstream of Tahe in Xinjiang as an example" @default.
- W2378611355 hasPublicationYear "2012" @default.
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