Mineral potential mapping with fuzzy models in the Kerman-Kashmar Tectonic Zone, Central Iran

Abstract

Fuzzy model as a knowledge-driven approach relies on the geologist's input to weight the importance of each data layer as it relates to the particular exploration model being used. In this paper we described a fuzzy model that uses a linear membership function for deriving fuzzy membership values of input evidential maps. The five multiclass evidential maps described were fuzzified using the linear membership function. The evidential maps and classes were ranked on the basis of our knowledge and information about REE mineralization in the study area. The model is demonstrated for mapping REE mineralization potential in an area in the Kerman-Kashmar Tectonic Zone (KKTZ), which separates the Yazd block to the west and the Tabas block to the east in Central Iran. At the fuzzy model described in this paper, we used four γ values to decrease the noise, and we applied selected optimum γ to predict potentially mineralized zones, which occupy less than 6 % of the study area. © Società Italiana di Fotogrammetria e Topografia (SIFET) 2012.