1887

Abstract

Summary

The prime focus of mineral prospectivity mapping (MPM) is the identification, delineation and level of potential for an area to host feasible mineral resources. In general, GIS-based MPM can be either data driven or knowledge-driven. Methods of data-driven MPM, which involve quantitative analysis of spatial relationships among anomalies (i.e., indicators of mineralization) and existing occurrences of mineral deposits of the type sought, is suitable for “brownfields” or well-explored regions, wherein the objective is to define additional targets for exploration.

One of the main objectives of WP3 in the FRAME project (www.frame.lneg.pt) is to produce a map of Strategic and Critical Raw Materials (SCRM) for Europe. Another objective is to produce predictive targeting based on GIS exploration tools at continental scale.

in this presentation we will review the state of the art for the MPM and show example of the favourability maps using CBA method and hybride fuzzy weight of evidence produced in the FRAME project.

This methodology represents different development stages, scales and progress of economic geology surveys which could be a tool to improve effectiveness and efficiency of future investments in exploration. Improved understanding and support for a balance management of competitive land-usage interests is an additional benefit.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202089003
2020-09-17
2024-03-29
Loading full text...

Full text loading...

/deliver/fulltext/2214-4609/2020/mineral-exploration-symposium/Sadeghi_et_al-FRAME_project-3-67-Sadeghi-Martiya.html?itemId=/content/papers/10.3997/2214-4609.202089003&mimeType=html&fmt=ahah

References

  1. Carranza, E.J.M.
    (2017). Natural Resources Research Publications on Geochemical Anomaly and Mineral Potential Mapping, and Introduction to the Special Issue of Papers in These Fields.Natural Resources Research, 26, 379–410.
    [Google Scholar]
  2. Porwal, A., Carranza, E. J. M., & Hale, M.
    (2006). A hybrid fuzzy weights-of-evidence model for mineral potential mapping.Natural Resources Research, 15(1), 1–14. http://doi.org/10.1007/s11053-006-9012-7
    [Google Scholar]
  3. Tourlière, B., Pakyuz-Charrier, E., Cassard, D., Barbanson, L., & Gumiaux, C.
    (2015). Cell Based Associations: A procedure for considering scarce and mixed mineral occurrences in predictive mapping.Computers and Geosciences, 78, 53–62. http://doi.org/10.1016/j.cageo.2015.01.012
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.202089003
Loading
/content/papers/10.3997/2214-4609.202089003
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error