ABSTRACT The geologic features indicative of Cu, Pb, Zn mineral deposits in a area are fractures （structure）, and host rock sediments. Datasets used include Cu, Pb, Zn deposit points record, geological data, remote ...ABSTRACT The geologic features indicative of Cu, Pb, Zn mineral deposits in a area are fractures （structure）, and host rock sediments. Datasets used include Cu, Pb, Zn deposit points record, geological data, remote sensing imagery （Landsat TM5）. The mineral potential of the study area is assessed by means of GIS based geodata integration techniques for generating predictive maps. GIS predictive model for Cu, Pb, Zn potential was carried out in this study area （Weixi） using weight of evidence. The weights of evidence modeling techniques is the data driven method in which the spatial associations of the indicative geologic features with the known mineral occurrences in the area are quantified, and weights statistically assigned to the geologic features. The best predictive map generated by this method defines 24 % the area having potential for Cu, Pb, Zn mineralization further exploration work.展开更多
文摘ABSTRACT The geologic features indicative of Cu, Pb, Zn mineral deposits in a area are fractures （structure）, and host rock sediments. Datasets used include Cu, Pb, Zn deposit points record, geological data, remote sensing imagery （Landsat TM5）. The mineral potential of the study area is assessed by means of GIS based geodata integration techniques for generating predictive maps. GIS predictive model for Cu, Pb, Zn potential was carried out in this study area （Weixi） using weight of evidence. The weights of evidence modeling techniques is the data driven method in which the spatial associations of the indicative geologic features with the known mineral occurrences in the area are quantified, and weights statistically assigned to the geologic features. The best predictive map generated by this method defines 24 % the area having potential for Cu, Pb, Zn mineralization further exploration work.
