Mineral Potential Mapping Using RF, Fuzzy AHP and Their Ensemble Model: A Case Study of the Daping Gold Deposits, Yunnan Province, China

Abstract

Analyzing and integrating evidential layers is essential for mineral prospectivity mapping. Remote sensing data from Landsat 8 and PALSAR-2/ALOS-2 were used to extract information about hydrothermal alterations and lineaments in a vegetation-covered study area. After integrating geological data, five evidential layers were identified, associated with gold mineralization, including lithology, hydrothermal alterations, lineaments, quartz veins, and geochemical anomalies. Based on these layers, prospective maps for mineralization were generated using RF and Fuzzy AHP models, as well as their ensemble. The P-A plot was used to evaluate the capability of model prediction. The results indicated that the three models yielded similar predictions, with areas of high mineralization potential located in the central part of the Daping area. The ensemble model demonstrated superior predictive performance.

Keywords

remote sensing / random forest / fuzzy AHP / ensemble model / mineral prospectivity mapping / economic geology

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