Prediction–area (P–A) plot and C–A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling
Yousefi, Mahyar, and Carranza, Emmanuel John M. (2015) Prediction–area (P–A) plot and C–A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling. Computers & Geosciences, 79. pp. 69-81.
PDF (Published Version)
- Published Version
Restricted to Repository staff only |
Abstract
There are methods of mineral prospectivity mapping whereby, besides assignment of weights to classes of evidence in an evidential map, every evidential map is also given a weight based on expert opinion. In this regard, evaluating the relative importance of every evidential map derived from particular spatial data sets is a highly subjective exercise and the assignment of meaningful weights to evidential maps usually involves a trial-and-error procedure. In this paper, we used a prediction–area (P–A) plot and normalized density to estimate weights of every evidential map. The method of P–A plot is a data-driven way, rather than using expert opinion, to evaluate and weight evidential maps.
Item ID: | 39056 |
---|---|
Item Type: | Article (Research - C1) |
ISSN: | 1873-7803 |
Keywords: | prediction–area (P–A) plot; C–A fractal model; evidential maps; normalized density; weighting; mineral prospectivity modeling |
Date Deposited: | 02 Jun 2015 22:54 |
FoR Codes: | 04 EARTH SCIENCES > 0403 Geology > 040399 Geology not elsewhere classified @ 30% 08 INFORMATION AND COMPUTING SCIENCES > 0899 Other Information and Computing Sciences > 089999 Information and Computing Sciences not elsewhere classified @ 70% |
SEO Codes: | 84 MINERAL RESOURCES (excl. Energy Resources) > 8401 Mineral Exploration > 840199 Mineral Exploration not elsewhere classified @ 50% 97 EXPANDING KNOWLEDGE > 970108 Expanding Knowledge in the Information and Computing Sciences @ 50% |
Downloads: |
Total: 2 |
More Statistics |