Union score and fuzzy logic mineral prospectivity mapping using discretized and continuous spatial evidence values

Yousefi, Mahyar, and Carranza, Emmanuel John M. (2017) Union score and fuzzy logic mineral prospectivity mapping using discretized and continuous spatial evidence values. Journal of African Earth Sciences, 128. pp. 47-60.

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Abstract

Two common problems affect integration of exploration criteria for mineral prospectivity mapping (MPM) in geographic information system (GIS): (a) stochastic error associated with sufficiency in number of known mineral occurrences (KMOs) used to estimate evidential weights and (b) systemic error associated with subjectivity of expert judgment applied to process, analyze, and assign weights to evidential data. In this paper we used logistic sigmoid (or S-shaped) function to transform continuous value evidential data into logistic space without using KMOs as in data-driven MPM and without discretization of evidential data into classes by using arbitrary intervals based on expert judgment as in knowledge-driven MPM. We generated a prospectivity model using discretized evidential data as well. Then, we compared the prospectivity models generated using continuous- and discretized-value evidential data and demonstrated that the former is better model for selecting target areas for further exploration.

Item ID: 50564
Item Type: Article (Research - C1)
ISSN: 1879-1956
Keywords: union score, fuzzy logic, mineral prospectivity mapping, discrete, continuous, spatial evidence values
Date Deposited: 20 Sep 2017 10:04
FoR Codes: 04 EARTH SCIENCES > 0402 Geochemistry > 040201 Exploration Geochemistry @ 50%
04 EARTH SCIENCES > 0403 Geology > 040307 Ore Deposit Petrology @ 50%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970104 Expanding Knowledge in the Earth Sciences @ 100%
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