A Hybrid Fuzzy Weights-of-Evidence Model for Mineral Potential Mapping |
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Authors: | Alok Porwal Emmanuel John M Carranza Martin Hale |
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Institution: | (1) International Institute for Geo-information Science and Earth Observation (ITC), Enschede, The Netherlands;(2) Department of Mines and Geology, Govt. of Rajasthan, Udaipur, India;(3) Faculty of Geoscience, Utrecht University, Utrecht, The Netherlands;(4) ITC, Hengelosestraat 99, 7500 AA Enschede, The Netherlands |
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Abstract: | This paper describes a hybrid fuzzy weights-of-evidence (WofE) model for mineral potential mapping that generates fuzzy predictor
patterns based on (a) knowledge-based fuzzy membership values and (b) data-based conditional probabilities. The fuzzy membership
values are calculated using a knowledge-driven logistic membership function, which provides a framework for treating systemic
uncertainty and also facilitates the use of multiclass predictor maps in the modeling procedure. The fuzzy predictor patterns
are combined using Bayes’ rule in a log-linear form (under an assumption of conditional independence) to update the prior
probability of target deposit-type occurrence in every unique combination of predictor patterns. The hybrid fuzzy WofE model
is applied to a regional-scale mapping of base-metal deposit potential in the south-central part of the Aravalli metallogenic
province (western India). The output map of fuzzy posterior probabilities of base-metal deposit occurrence is classified subsequently
to delineate zones with high-favorability, moderate favorability, and low-favorability for occurrence of base-metal deposits.
An analysis of the favorability map indicates (a) significant improvement of probability of base-metal deposit occurrence
in the high-favorability and moderate-favorability zones and (b) significant deterioration of probability of base-metal deposit
occurrence in the low-favorability zones. The results demonstrate usefulness of the hybrid fuzzy WofE model in representation
and in integration of evidential features to map relative potential for mineral deposit occurrence. |
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Keywords: | Fuzzy membership conditional probability base-metal deposits GIS Aravalli province |
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