There are different exploration methods, each of which may introduce a number of promising exploration targets. However, due to the financial and time constraints, only a few of them are selected as the exploration priorities. Instead of the individual use of any exploration method, it is common to integrate the results of different methods in an interdependent framework in order to recognize the best targets for further exploration programs. In this work, the continuously-weighted evidence maps of proximity to intrusive contacts, faults density, and stream sediment geochemical anomalies of a set of porphyry copper deposits in the Jiroft region of the Kerman Province in Iran are first generated using the logistic functions. The weighted evidence maps are then integrated using the union score integration function in order to model the deposit type in the studied area. The weighting and integration approaches applied avoid the disadvantages of the traditional methods in terms of carrying the bias and error resulting from the weighting procedure. Evaluation of the ensuing prospectivity model generated demonstrate that the prediction rate of the model is acceptable, and the targets generated are reliable to follow up the exploration program in the studied area.
