论文部分内容阅读
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。
According to the spectral characteristics of altered minerals in the study area, principal component analysis (PCA) based on the combination of characteristic bands was used to extract altered mineral assemblages. Sericite, kaolinite, montmorillonite and Erie were extracted from ASTER multispectral satellite data. Information on Al-OH altered mineral assemblages, such as lithic and alunite, and epidotemalized altered mineral assemblages such as chlorite, epidote, and carbonate (calcite and dolomite). At the same time, remote sensing geologic interpretation was conducted in the study area by human-computer interactive interpretation technology. Combined with the regional geological characteristics of ore-forming, a comprehensive analysis was made on the remote sensing data of ore-controlling structures, circular structures, ore-bearing strata and alteration mineral assemblages in the study area Information, and based on remote sensing information to conduct a comprehensive ore prospecting prediction, delineated a favorable prospecting prospecting area, the ground water sediment geochemical mapping and high resolution satellite imagery evidence that the delineated remote sensing prospecting area for the study area Ground mineral exploration work to provide an important reference.