摘要
利用ASTER多光谱卫星数据,根据研究区内蚀变矿物的波谱特性,采用特征波段组合的主成分分析方法进行蚀变矿物组合信息提取,分别提取了绢云母、高岭石、蒙脱石、伊利石和明矾石等Al-OH类蚀变矿物组合信息,以及绿泥石、绿帘石和碳酸盐化(方解石和白云石)等青磐岩化类蚀变矿物组合信息。同时采用人机交互解译技术在研究区开展了遥感地质解译,结合区域成矿地质特征,综合分析了研究区控矿线性构造、环形构造、赋矿岩层和蚀变矿物组合等遥感示矿信息,并基于遥感示矿信息进行了综合找矿预测,圈定出遥感找矿有利区,经地面水系沉积物化探填图和高分辨卫星影像佐证,研究表明圈定的遥感找矿有利区为研究区开展地面矿产勘查工作提供重要的参考依据。
The study area is located in Lima South Central,Peru,and the south of Andean porphyry belt northern,with good copper polymetallic mineralization geological conditions.Based on ASTER multispectral satellite data and the spectral characteristics of altered minerals region,using characteristic band combination of principal component analysis method completed the altered minerals assemblage information extraction.Using this method,extracted Al-OH altered minerals information,such as sericite,kaolinite,montmorillonite,illite,alunite,et al,and propylitization alteration minerals information,such as chlorite,epidote and carbonate(calcite and dolomite).While using interactive interpretation technique in the study area to carry out geological interpretation of remote sensing,which combined with regional geological characteristics,had a comprehensive analysis of remote sensing indicator mineral information including ore-controlling linear structures,circular structures,ore-bearing strata and alteration mineral assemblages.In addition,remote sensing indicator mineral information conducted a comprehensive prospecting prediction,and delineated favorable prospecting area.Comparing with the ground stream sediment geochemical mapping and highresolution satellite images,which indicates that the delineation of remote sensing prospecting area provides important reference basis for exploration in the development of ground mineral.
出处
《遥感技术与应用》
CSCD
北大核心
2015年第1期33-42,共10页
Remote Sensing Technology and Application
基金
国家863计划项目"全球巨型成矿带矿产资源与能源遥感专题产品生产体系"(2013AA12A302)
国土资源部杰出青年科技人才培养计划(201302065)资助
关键词
ASTER卫星数据
蚀变矿物组合信息
遥感示矿信息
找矿预测
ASTER satellite data
Alteration mineral assemblage information
Remote sensing indicator mineral information
Prospecting prediction