Principal component analysis(PCA)was employed to analyze the feature vector matrix of ASTER data in Ruoqiang area,Xinjiang,identifying principal components reflecting iron oxides(such as goethite,hematite,and magnetite),Al(OH)minerals(in-cluding kaolinite,alunite,muscovite,and illite),and Fe,Mg(OH)minerals(such as chlorite and carbonate minerals like calcite,dolomite,and siderite).The absorption and reflection spectral characteristics of determined principal components and altered mineral association were utilized to extract alteration mineral information in northern slope area of Xinjiang.Combined with remote sensing geo-logical interpretation maps,ore-bearing strata of the lower subformation(C1ha)of Hongliuyuan Formation,quartz veins associated with mineralization,and NE-trending fault structures controlling mineral distribution,prospective ore zones were predicted,providing funda-mental data for remote sensing geological exploration in Pobei area of Xinjiang.
关键词
ASTER数据/主成分分析法/蚀变矿物信息提取/成矿远景区/新疆若羌
Key words
ASTER data/principal component analysis/extraction of alteration mineral information/metallogenic prospect area/Ruoqiang,Xinjiang
维普
万方数据