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中文摘要：
用遥远地察觉到的图象的影响盐的土壤分类是在遥感的最普通的应用之一，，并且这个目的在 literature.This 学习作为一个学习区域拿 Weigan 和 Kuqa 河的三角洲绿洲并且从 ETM Landsat data.It 讨论土壤 salinization 的预言基于独立部件 AnalysisICA 和质地 features.Meanwhile 报导支持向量 MachineSVM 分类方法，字母 introduc
英文摘要：
Salt-affected soils classification using remotely sensed images is one of the most common applications in remote sensing,and many algorithms have been developed and applied for this purpose in the literature.This study takes the Delta Oasis of Weigan and Kuqa Rivers as a study area and discusses the prediction of soil salinization from ETM＋ Landsat data.It reports the Support Vector Machine（SVM） classification method based on Independent Component Analysis（ICA） and Texture features.Meanwhile,the letter introduces the fundamental theory of SVM algorithm and ICA,and then incorporates ICA and texture features.The classification result is compared with ICA-SVM classification,single data source SVM classification,maximum likelihood classification（MLC） and neural network classification qualitatively and quantitatively.The 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 98.64%,which increases by 10.2% compared with maximum likelihood classification,even increases by 12.94% compared with neural net classification,and thus acquires good effectiveness.Therefore,the classification method based on SVM and incorporating the ICA and texture features can be adapted to RS image classification and monitoring of soil salinization.
同期刊论文项目
同项目期刊论文
The effects of land-use change on ecosystem service value of desert oasis: a case study in Ugan-Kuqa
Application study of the thermal infrared emissivity spectra in the estimation of salt content of sa
Spectral reflectance properties of major objects in desert oasis: a case study of the Weigan-Kuqa ri
A Method of Soil Salinization Information Extraction with SVM Classfication Based on ICA and Texture
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