- 责任者：Zhang Fei (College of Resources and Environment Science ; Xinjiang University ; Urumqi 830046 ; China) ; Tashpolat Tiyip
- 刊名：Arid Land Geography
- 出版年：2009
- 卷期：31(1)
- 关键词：遥感 ; remote sensing ; 支持向量机 ; support vector machine ; 土壤盐渍化 ; salinization ; 塔里木盆地 ; Tarim Basin
- 页码：p.57-66
- 图表：4 illus., 2 tables, 33 refs.
- 分类号：1600
- issnNo：1000-6060
- isbnNo：65-1103/X
In this paper, the author takes the North Oasis of the Tarim Basin (the delta Oasis of Weigan and Kuqa Rivers) for example, in virtue of ENVI software and using ETM+ data; discussing the method of extracting of soil salinization information. The results indicate that on the windows of 3×3, 5×5, 7×7, 9×9, 11×11, 13×13, the precision of classification is very high, up to above 93 %, and when validating the result of classification, the authors have found that the result of classification by the SVM method based on spectrum and texture information on 9×9 windows is in accordance with the fact. So the authors can say that joining with the texture character can easily extract the soil salinization information (severely salinized soil, moderately salinized soil, slightly salinized soil), and increases its precision. Therefore, the classification method by SVM (Support Vector Machines) based on texture characteristic can be adapted to RS image classification and monitoring of soil salinization, furthermore provide an effective way for remote sensing information extraction.