Boletín de la Sociedad Geológica Mexicana

Volumen 72, núm. 3, A090520, 2020


Cartografía digital predictiva del potencial mineral mediante SIG de depósitos de fluorita en el noreste de México


Digital prospectivity mapping of fluorite deposits in northeast Mexico using GIS


Roberto Díaz-Martínez1,*, Leonela Aimme González-Martínez1, José Alberto Batista-Rodríguez1, Alberto Hernández-Rosales1, Jesús Antonio Blanco-Moreno1, Ramón Yosvanis Batista-Cruz1,Yuri Almaguer Carmenates1, Antonio Rodríguez Vega1, Felipe de Jesús López Saucedo1, Alberto Ramón Vila Sánchez2


1Escuela Superior de Ingeniería “Lic. Adolfo López Mateos”, UADEC, Boulevard Adolfo López Mateos s/n, Nueva Rosita, Coahuila de Zaragoza. 26800, Coahuila, México.

2Minera Águila Plateada SA. de CV, Calle Jaime Balmes No. 11. Torre A, Planta Alta Local 111. Piso 3. Colonia Los Morales, Polanco, Miguel Hidalgo,11510, CDMX, México.

* Autor para correspondencia: (R. Díaz-Martínez) This email address is being protected from spambots. You need JavaScript enabled to view it.


How to cite this article:

Díaz-Martínez, R., González-Martínez, L.A., Batista-Rodríguez, J. A., Hernández-Rosales, A., Blanco-Moreno, J. A., Batista-Cruz, R. Y., Almaguer Carmenates, Y., Rodríguez Vega, A., López Saucedo, F. J., Vila Sánchez, A. R., 2020, Cartografía digital predictiva del potencial mineral mediante SIG de depósitos de fluorita en el noreste de México: Boletín de la Sociedad Geológica Mexicana, 72 (3), A090520. v72n3a090520




Prospectivity maps are based on probability models of occurrence of mineral deposits. It is the basis for the metallogenic prognosis and the delimitation of perspective areas. Different geological surveys have covered the northeastern region of Mexico, mining exploration works, and regional metallogenic studies and more than 160 deposits and manifestations of fluorite are currently reported. However, the methods that allow the manipulation, analysis and integration of the exploration guides used in the predictive cartography of mining potential have not been used. In this context, there is a need to start predictive mapping work in Mexico, which helps to minimize the costs of mineral exploration by optimizing areas potentially favourable to the occurrence of mineral deposits and discarding those areas without economic interest. The geological, structural, geochemical and geophysical information available is adequate to the application of prospectivity mapping supported by geographic information systems and based on the structuring of the primary data, the weighted overlap and the integration and analysis of the data through Boolean logic and maximum entropy models. Results indicate that the mineral potential mapping offers a good predictor because the areas with high prospectivity are correctly delimited as the most favourable for the occurrence of fluorite deposits. The structural density is the parameter that most influences with 28.8% of contribution to the mineral potentiality model.

Keywords: Mineral prospectivity mapping, fluorite, GIS, weighted overlap, Boolean logic, maximum entropy.