Application of the content-area (C-A) fractal model and prediction-area (P-A) plot for mineral prospectivity modeling in the Luchun area of Yunnan Province, China

This method of assigning weights based on expert opinion introduces bias when we are evaluating the relative importance of evidence values. In this paper, we used a prediction-area (P-A) plot method and content-area (C-A) fractal model to estimate the weight of each evidence map. In this paper, we used the content region (C-A) fractal model to divide the evidence maps to the threshold of the corresponding dimensions. The P-A plot approach is an objective data-driven approach for evaluating map weights. Using geochemical layer and remote sensing, hydroxyl layers as weight evidence maps are the highlights of this study. We use the P-A method from which we can evaluate the predictive ability of each evidence map with respect to the known ore occurrences. We used the P-A plot for weighting each evidence map and choosing the appropriate threshold for predictor maps in the Luchun area of Yunnan Province, China. The method adopted in this paper can improve the prediction efficiency of ore prospecting.