Quantitative prediction and evaluation of mineral resources based on GIS: A case study in Sanjiang region, southwestern China

15Citations
Citations of this article
16Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Quantitative prediction and evaluation of mineral resources are one of the important topics of mathematical geology. On the basis of GIS technologies and weights of evidence modeling, MapGIS is integrated with GIS and mineral-resource prediction and evaluation. The final product is a predictor map of posterior probabilities of occurrence of the discrete event within a small unit cell. Predictor layers were created on a digital database that includes 1:200,000 scale geological, and geochemical, and geophysical maps, and remote-sensing images in study area. According to metallogenetic factors extractiont and weights of evidence modeling, there are four main metal ore belts in the study area: (1) the Batang belt; (2) the Lei Wuqi belt; (3) the Basu-Chayu belt; and (4) the Ganzi-Litang belt. The predictor map of posterior probabilities show that 29% of study area as zones with potential for porphyry copper, and 81% known mineral occurrences success rate is circled in the metallogenetic posterior probabilities map. The results demonstrate plausibility of weights-of-evidence modeling of mineral potential in large areas with small number of mineral prospects. © 2005 International Association for Mathematical Geology.

Cite

CITATION STYLE

APA

Chen, J., Wang, G., & Hou, C. (2005). Quantitative prediction and evaluation of mineral resources based on GIS: A case study in Sanjiang region, southwestern China. Natural Resources Research, 14(4), 285–294. https://doi.org/10.1007/s11053-006-9005-6

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free