Analytical hierarchical prospectivity mapping using integration of exploratory data in the Anarak region, Central Iran

Abstract

This paper aims to show the kind of corporations, Analytical Hierachy Process (AHP) for determining significant weights of evaluation criteria with Technique for Order Preference by Similarity to Ideal (TOPSIS) and Simple Additive Weighting (SAW) methods for ranking of geo-dataset for Mineral Prospectivity Mapping (MPM) of Cu in Anarak region, Central Iran. This operation was carried out by integration of remote sensing, geophysical, geochemical and geological data. The Anarak region has a high potential for copper mineralization because the studied district is located in the NW of the Central East Iranian Microplate (CEIM) that is an important ore mineralized zone in Central Iran. The integration approaches are complex, Multi-Criteria Decision Making (MCDM), and knowledge-driven methods that they named AHP-TOPSIS and AHP-SAW. In addition, there are three variant models of TOPSIS method including conventional, adjusted and modified. The AHP has been carried out on geological/alteration data, structural data, airborne geophysical data and stream sediment geochemical layer in the studied area. These data are classified by fractal modeling for the generation of geo-dataset layers to a relationship of copper occurrences in the Anarak region. Consequently, the produced MPMs by the AHP-TOPSIS and AHP-SAW have adequately matching and sufficient correlation with copper mines and main copper deposits/occurrences in the Anarak region.