Study on extracting of soil salinization by remote sensing based on SVM method with spectrum and texture information
Abstract
In this paper,in order to overcome the different thing with same spectrum and the same thing with different spectrum phenomenon,taking the Delta Oasis of Weigan and Kuqa rivers for example,using ETM+ data,the method of extracting of soil salinization is discussed.The classification method based on support vector machine(SVM) and combination of spectrum and texture information is proposed.The classification result is compared with minimum distance classification,maximum likelihood 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.Therefore,this method is adapted to RS image classification and monitoring of soil salinization,furthermore,provides an efficient way for remote sensing information extraction.