weights of evidence

Data integration can be used to conduct exploratory studies on a regional scale simultaneously on all available data from the study area. The results obtained by considering all the data and the relationship between them are more accurate and reliable. In these cases, mineral potential modeling is utilized to determine promising areas. Although GIS-based mineral prospectivity mapping methods have been established, it is important to review which methods of geochemical data analysis result in anomaly maps that, in turn, lead to better models of mineral prospectivity. In this study, instead of using anomalies of pathfinder elements, using geochemical zonality anomalies as one of the several evidential maps resulted in the improved mapping of mineral prospectivity. In addition, whereas weights-of-evidence analysis was used in this study, other methods of data representation and integration for mineral prospectivity mapping can be used. In this study, a part of Arasbaran metallogenic zone was selected and one-element geochemical control maps, geochemical maps produced by zonality, structural, alteration and geological maps were weighted and produced using the position of known indices by the method of weights-of-evidence. In the next step, weighted layers were combined with logistic regression (LR) method to prepare mineral potential models.

Nowadays، using GIS in exploration of mineral deposits is among the important، and of course، indespensible methods. Accordingly، the algorithm of Weights of Evidence in GIS has been employed in this paper for integrating data from geological، exploration and mining sources in order to detect and discriminate areas bearing high potential of minerals in Irankoh of Isfahan as a case study. In order to obtain and complete some evidential layers the remotely sensed digital imagery from multi-spectral satellites including Landsat ETM+ and Aster sensors of the region were processed in the first stage. Other evidential layers such as geophysical، geochemical، Barite outcrops، surficial ore indications and known deposit training sites were created using information available in many exploratory reports and maps. Using weights of evidence approach، the weights for above eight separate evidential layers including geophysical، geochemical، faulting، dolomitization، baritization، ore indications، oxidation and hydroxylation layers were calculated and in the mean time، the conditional independencies were evaluated using chi-square statistical test. The final favorability map for further follow-up priorities in the frame of systematic exploration was drawn، and based on this map the regions with ranked prospectivities were identified. The results show that parts of Roomarmar region، areas to the west of Gooshfil mine، east of Tappeh-Sorkh mine، north of Kolahdarwazeh mine and lastly west of Tappeh-Sorkh mine with lowest prospectivity are respectively areas to be considered for further exploration programs.