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Predictive Mapping of the Mineral Potential Using Geophysical and Remote Sensing Datasets in Parts of Federal Capital Territory, Abuja, North-Central Nigeria
Earth Sciences
Volume 9, Issue 5, October 2020, Pages: 148-163
Received: Jul. 23, 2020; Accepted: Aug. 22, 2020; Published: Sep. 17, 2020
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Ejepu Jude Steven, Department of Geology, School of Physical Sciences, Federal University of Technology, Minna, Nigeria
Abdullahi Suleiman, Department of Geology, School of Physical Sciences, Federal University of Technology, Minna, Nigeria
Abdulfatai Asema Ibrahim, Department of Geology, School of Physical Sciences, Federal University of Technology, Minna, Nigeria
Umar Mohammed Umar, Department of Geology and Mining, Faculty of Applied Sciences and Technology, Ibrahim Badamasi Babangida University, Lapai, Nigeria
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Mineral Prospectivity Mapping (MPM) is a multi-step process that ranks a promising target area for more exploration. This is achieved by integrating multiple geoscience datasets using mathematical tools to determine spatial relationships with known mineral occurrences in a GIS environment to produce mineral prospectivity map. The study area lies within Latitudes 9° 00ʹ N to 9° 15ʹ N and 6° 45ʹ to 7° 00ʹ E and is underlain by rocks belonging to the Basement Complex of Nigeria which include migmatitc gneiss, schist, granite and alluvium. The datasets used in this study consist of aeromagnetic, aeroradiometric, structural, satellite remote sensing and geological datasets. Published geologic map of the Sheet 185 Paiko SE was used to extract lithologic and structural information. Landsat images were used to delineate hydroxyl and iron-oxide alterations to identify linear structures and prospective zones at regional scales. ASTER images were used to extract mineral indices of the OH-bearing minerals including alunite, kaolinite, muscovite and montmorillonite to separate mineralized parts of the alteration zones. Aeromagnetic data were interpreted and derivative maps of First Vertical Derivative, Tilt derivative and Analytic signal were used to map magnetic lineaments and other structural attributes while the aeroradiometric dataset was used to map hydrothermally altered zones. These processed datasets were then integrated using Fuzzy Logic modelling to produce a final mineral prospectivity map of the area. The result of the model accurately predicted known deposits and highlighted areas where further detailed exploration may be conducted.
Geophysical Methods, Mineral Exploration, Fuzzy Logic Models, Geographic Information Systems, Remote Sensing
To cite this article
Ejepu Jude Steven, Abdullahi Suleiman, Abdulfatai Asema Ibrahim, Umar Mohammed Umar, Predictive Mapping of the Mineral Potential Using Geophysical and Remote Sensing Datasets in Parts of Federal Capital Territory, Abuja, North-Central Nigeria, Earth Sciences. Vol. 9, No. 5, 2020, pp. 148-163. doi: 10.11648/
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