Lithologic Classification from Remote Sensing Images Based on Spectral Index
Yu Yafeng
Yang Jinzhong
Chen Shengbo
Wang Nan
Abstract：In order to solve the problem of interference factors of the rock radiated in traditional lithologic classification with the phenomenon of the different spectra for the same substance and the same spectrum for different substances,and the low lithol-ogic classification accuracy,A study based on the in-depth analysis of spectrum characteristics of mineral rock,taking monzo-nitic granite,quartz-syenite and syenite of West Kunlun metallogentic belt as the research object is presented in the paper.We set up two spectral index RI and SI on the basis of measured spectral data of three kinds of lithology and the characteristics of ASTER imaging data.Two spectral index methods are used to classify ASTER remote sensing data,and the results show that the accuracy in monzonitic granite extraction with RI and SI spectral index method is above 70%,about 80% in quartz-syenite extraction.The precision of the two kinds of lithology has been significantly increased compared with the classification results of maximum likelihood method.
Keywords：spectral index methodASTERWest Kunlun metallogenic beltmaximum likelihood methodremote sensing
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 1415-1419 )