S., A., S., E. (2024). Utilizing remote sensing and aerogeophysical data for spatial decision support system for optimal gold mineralization site identification in North-Central Nigeria. , 42(10), 1220-1241. doi: 10.30684/etj.2024.146400.1681
Abdullahi S.; Ejepu J. S.. "Utilizing remote sensing and aerogeophysical data for spatial decision support system for optimal gold mineralization site identification in North-Central Nigeria". , 42, 10, 2024, 1220-1241. doi: 10.30684/etj.2024.146400.1681
S., A., S., E. (2024). 'Utilizing remote sensing and aerogeophysical data for spatial decision support system for optimal gold mineralization site identification in North-Central Nigeria', , 42(10), pp. 1220-1241. doi: 10.30684/etj.2024.146400.1681
S., A., S., E. Utilizing remote sensing and aerogeophysical data for spatial decision support system for optimal gold mineralization site identification in North-Central Nigeria. , 2024; 42(10): 1220-1241. doi: 10.30684/etj.2024.146400.1681

Utilizing remote sensing and aerogeophysical data for spatial decision support system for optimal gold mineralization site identification in North-Central Nigeria

Engineering and Technology Journal
Volume 42, Issue 10, October 2024, Pages 1220-1241    PDF (4.43 M)
Document Type: Research Paper
DOI: 10.30684/etj.2024.146400.1681
Authors
Abdullahi S.; Ejepu J. S.*
Department of Geology, School of Physical Sciences, Federal University of Technology Minna, Niger State, Nigeria.
Abstract
This study presents a comprehensive investigation utilizing remote sensing data and aerogeophysical datasets to identify potential economic gold mineralization sites in Zungeru, North-Central Nigeria. The research objectives include understanding the structural setting, mapping lithologic contacts, and detecting hydrothermally altered zones. Spatial suitability analysis was conducted on processed datasets. Feature-Oriented Principal Component Analysis (Crosta approach) was applied to selected Landsat 8 OLI imagery bands for mapping hydroxyl and iron oxide alterations. Additionally, regional topographic lineaments were mapped using SRTM DEM, and subsurface lineaments were identified using aeromagnetic data. Interpretation of the aeromagnetic data revealed complex anomalies associated with various structural characteristics, such as faults, folds, and fractures. The investigation of hydrothermal alteration zones through gamma-ray spectrometry data and K/eTh ratio analysis demonstrated a significant connection with igneous intrusions, further supported by ternary maps of the radioelements. Five thematic maps representing factors that control gold mineralization were integrated using GIS modeling to identify prospective zones. Five distinct mineral-prospective zones are delineated, showing varying levels of mineralization potential. The "Very Good" to "Good" zones are predominantly aligned in the NNE direction, with some occurrence in the NW quadrant. The spatial correlation with lithological characteristics and lineament features suggests their strong influence on mineral prospectivity. Around 76% of gold mineralization is within the most favorably projected zones. Both models show considerable reliability, with predictive accuracies surpassing 70%, as validated using the ROC/AUC metric. The Fuzzy Logic model showcases the highest predictive efficacy, with a prediction level of 78.3%. The validation results of gold mining sites from the models indicate a percentage agreement of 75%. The study guides future exploration efforts, directing them toward areas with the highest promise of finding gold. This work is instrumental in optimizing resource allocation and maximizing the efficiency of exploration endeavors, paving the way for more targeted and successful gold prospecting in the region.

Highlights
  • Remote sensing is employed to detect potential gold reserves in the study.
  • The research facilitates comprehension of structural geology and its mapping.
  • FOPCA and aeromagnetic techniques are utilized for advanced interpretation.
  • GIS modeling enhances the understanding of zones with mineral prospects.
Keywords
Gold mineralization Hydrothermal alteration Mineral; prospective zones Analytic Hierarchy Process Fuzzy Overlay
References
  1. L. Adebiyi, A. Eluwole, F. Akindeji, N. Salawu, Integrated geophysical methods for delineating crustal structures and hydrothermal alteration zones for mineral exploration projects in parts of west-central, Nigeria, Earth Syst., Environ., 8 (2021) 2977–2989. http://dx.doi.org/10.1007/s40808-021-01275-5
  2. Sabins, Remote Sensing for Mineral Exploration, Ore Geol. Rev., 14 (1999) 157-183. http://dx.doi.org/10.1016/S0169-1368(99)00007-4
  3. Okeke, V. Ukaegbu, N. Egesi , Remote sensing signature of geological structures inferred on Landsat imagery of Afikpo area Southeastern Nigeria, J. Geol. Min. Res., 11 (2019) 1-13. http://dx.doi.org/10.5897/JGMR2018.0305
  4. Oyawale, F. Adeoti, T. Ajayi, A. Omitogun, Applications of remote sensing and geographic information system (GIS) in regional lineament mapping and structural analysis in Ikare Area, Southwestern Nigeria, J. Geol. Min. Res., 12 (2020) 13-24. http://dx.doi.org/10.5897/JGMR2019.0310
  5. Pour, B. Zoheir, B. Pradhan, M. Hashim, Editorial for the special issue: multispectral and hyperspectral remote sensing data for mineral exploration and environmental monitoring of mined areas, Remote, Sens., 13 (2021) 519. https://doi.org/10.3390/rs13030519
  6. Okpoli, J. Ogbole, O. Victor, G. Okanlawon, Mineral exploration of Iwo-Apomu Southwestern Nigeria using aeromagnetic and remote sensing, Egypt. J. Remote. Sens. Space .Sci. , 25 (2022) 371-385. https://doi.org/10.1016/j.ejrs.2022.03.004
  7. Ruitenbeek, T. Cudahy, F. Meer, M. Hale, Characterization of the hydrothermal systems associated with Archean VMS-mineralization at Panorama, Western Australia, using hyperspectral, geochemical and geothermometric data, Ore Geol. Rev., 45 (2012) 33-46. https://doi.org/10.1016/j.oregeorev.2011.07.001
  8. Uwiduhaye, J. Ngaruye, H. Saibi, Defining potential mineral exploration targets from the interpretation of aeromagnetic data in western Rwanda, Ore Geol. Rev., 128 (2021) 103927. https://doi.org/10.1016/j.oregeorev.2020.103927
  9. Frutuoso, A. Lima, A. Teodoro, Application of remote sensing data in gold exploration: Targeting hydrothermal alteration using Landsat 8 imagery in northern Portugal, Arab. J. Geosci., 14 (2021) 1-18. https://doi.org/10.1007/s12517-021-06786-0
  10. Fustic, R. Nair, A. Wetzel, R. Siddiqui, W. Matthews, et al., Bioturbation, heavy mineral concentration, and high gamma-ray activity in the Lower Cretaceous McMurray Formation, Canada, Palaeogeogr. Palaeoclimatol. Palaeoecol., 564 (2021) 110187. https://doi.org/10.1016/j.palaeo.2020.110187
  11. Rowan, A. Goetz, R. Ashley, Discrimination of hydrothermally altered and unaltered rocks in visible and near infrared multispectral images, Geophysics, 42 (1977) 522-535. https://doi.org/10.1190/1.1440723
  12. Pour, M. Hashim, Hydrothermal alteration mapping from Landsat-8 data, Sar Cheshmeh copper mining district, south-eastern Islamic Republic of Iran, J. Taibah Univ. Sci., 9 (2015) 155-166. https://doi.org/10.1016/j.jtusci.2014.11.008
  13. Fuertes-Fuente, A. Cepedal, A. Lima, A. Doria, M. dos Anjos Ribeiro, A. Guedes, The Au-bearing vein system of the Limarinho deposit (northern Portugal): Genetic constraints from Bi-chalcogenides and Bi–Pb–Ag sulfosalts, fluid inclusions and stable isotopes, Ore Geol. Rev., 72 (2016) 213-231. https://doi.org/10.1016/j.oregeorev.2015.07.009
  14. Nikolakopoulos, P. Lampropoulou, D. Papoulis, A. Rogkala, P. Giannakopoulou, P. Petrounias, Combined use of remote sensing data, mineralogical analyses, microstructure studies and geographic information system for geological mapping of Antiparos Island (Greece), Geosciences, 8 (2018) 96. https://doi.org/10.3390/geosciences8030096
  15. Cardoso-Fernandes, A. Teodoro, A. Lima, M. Perrotta, E. Roda-Robles, Detecting Lithium (Li) mineralization from space: Current research and future perspectives, Appl. Sci., 10 (2020) 1785. https://doi.org/10.3390/app10051785
  16. Funedda, S. Naitza, C. Buttau, F. Cocco, A. Dini, Structural controls of ore mineralization in a polydeformed basement: Field examples from the Variscan Baccu Locci shear zone (SE Sardinia, Italy), Minerals, 8 (2018) 456. https://doi.org/10.3390/min8100456
  17. Tuduri, A. Chauvet, L. Barbanson, M. Labriki, M. Dubois, P. Trapy, L. Maacha, et al., Structural control, magmatic-hydrothermal evolution, and formation of hornfels-hosted, intrusion-related gold deposits: Insight from the Thaghassa deposit in Eastern Anti-Atlas, Morocco, Ore Geol. Rev., 97 (2018) 171-198. https://doi.org/10.1016/j.oregeorev.2018.04.023
  18. Chauvet, Structural control of ore deposits: The role of pre-existing structures on the formation of mineralized vein systems, Minerals, 9 (2019) 56. https://doi.org/10.3390/min9010056
  19. Meer, et al., Multi- and hyperspectral geologic remote sensing: A review,  Int. J. Appl. Earth Obs. Geoinf., 14 (2012) 112-128. https://doi.org/10.1016/j.jag.2011.08.002
  20. Wambo, et al., Identifying high potential zones of gold mineralization in a sub-tropical region using Landsat-8 and ASTER remote sensing data: a case study of the Ngoura-Colomines goldfield, eastern Cameroon, Ore Geol. Rev., 122 (2020) 103530. https://doi.org/10.1016/j.oregeorev.2020.103530
  21. Shebl, M. Abdellatif, S. Elkhateeb, Á. Csámer, Multisource data analysis for gold potentiality mapping of Atalla area and its environs, Central Eastern Desert, Egypt, Minerals, 11 (2021) 641. https://doi.org/10.3390/min11060641
  22. Pour, M. Hashim, Identification of hydrothermal alteration minerals for exploring of porphyry copper deposit using ASTER data, SE Iran, J. Asian Earth Sci., 42 (2011) 1309-1323. https://doi.org/10.1016/j.jseaes.2011.07.017
  23. Misi, et al, Review of the geological and geochronological framework of the Vazante sequence, Minas Gerais, Brazil: Implications to metallogenic and phosphogenic models, Ore Geol. Rev., 63 (2014) 76-90. https://doi.org/10.1016/j.oregeorev.2014.05.002
  24. Monsef, et al., Role of Magmatism and Related-Exsolved Fluids during Ta-Nb-Sn Concentration in the Central Eastern Desert of Egypt: Evidences from Mineral Chemistry and Fluid Inclusions, J. Earth Sci., 34 (2023) 674-689. https://doi.org/10.1007/s12583-022-1778-y
  25. Hunt, Spectral signatures of particulate minerals in the visible and near infrared, Geophysics, 42 (1977) 468- 671. https://doi.org/10.1190/1.1440721
  26. Girija, S. Mayappan, Mapping of mineral resources and lithological units: A review of remote sensing techniques, Int. J. Image Data Fusion., 10 (2019) 79-106. https://doi.org/10.1080/19479832.2019.1589585
  27. Hamisi, D. MacKenzie, et al., Hydrothermal footprint of the Birthday reef, Reefton goldfield, New Zealand , New Zealand J. Geol. Geophys., 60 (2017) 59-72. https://doi.org/10.1080/00288306.2016.1274332
  28. Groves, M. Santosh, R. Goldfarb, L. Zhang, Structural geometry of orogenic gold deposits: Implications for exploration of world-class and giant deposits, Geosci. Front., 9 (2018) 1163-1177. https://doi.org/10.1016/j.gsf.2018.01.006
  29. Pour, et al., Evaluation of ICA and CEM algorithms with Landsat-8/ASTER data for geological mapping in inaccessible regions, Geocarto Int., 34 (2019) 785-816 https://doi.org/10.1080/10106049.2018.1434684
  30. Liu, Y. Li, J. Zhou, et al., Gold-copper deposits in Wushitala, Southern Tianshan, Northwest China: Application of ASTER data for mineral exploration, Geol. J., 53 (2018) 362–371. https://doi.org/10.1002/gj.2989
  31. Abdelnasser, et al., REE geochemical char- acteristics and satellite-based mapping of hydrothermal alteration in Atud gold deposit, Egypt, J. African Earth Sci., 145 (2018) 317–330. https://doi.org/10.1016/j.jafrearsci.2018.01.013
  32. Fagbohun, et al., Identifying geochemical anomalies and spatial distribution of gold and associated elements in the Zuru Schist Belt, northwest Nigeria, Arab. J. Geosc., 14 (2021) 1-20. https://doi.org/10.1007/s12517-021-06828-7
  33. Garba, S. Akande, The origin and significance of non-aqueous CO2 fluid inclusions in the auriferous veins of Bin Yauri, northwestern Nigeria, Miner. Deposita, 27 (1992) 249-255. https://doi.org/10.1007/BF00202550
  34. Darma, et al., Appraisal of lead (Pb) contamination and potential exposure risk associated with agricultural soils and some cultivated plants in gold mines,  Environ. Syst. Res., 11 (2022) 1-12. https://doi.org/10.1186/s40068-022-00259-3
  35. Ohioma, Detection of Sulphide Deposit Using Uranium/Potassium Ratio Map, Ghana J. Geogr., 12 (2020) 145-158. https://doi.org/10.4314/gjg.v12i1.8
  36. Burke, K. C & Dewey, J. F. Orogeny in Africa, In Dessauvagie, T. F. J. and Whiteman, A. J. (Eds.). African Geology (1972) 583-608
  37. Grant , Geochronology of Precambrian basement rocks of Ibadan, SouthWestern Nigeria, Earth Planet. Sci. Lett., 10 (1970) 29-38. https://doi.org/10.1016/0012-821X(70)90061-0
  38. Bertrand, R. Caby, Geodynamic evolution of the Pan-African orogenic belt: a new interpretation of the Hoggar Shield (Algerian Sahara), Geol. Rundsch, 67 (1978) 357-388. https://doi.org/10.1007/BF01802795
  39. Rahaman, Recent advances in the study of the Basement Complex of Nigeria. Precambrian Geology of Nigeria, Geol. Survey of Nigeria Publications, (1988) 11-43.
  40. Oyawoye, The Geology of the Nigerian Basement Complex, Nigeria, J. Mining Geol. Metal Soc., 1 (1972) 7-102.
  41. Mccurry, P. Geology of degree Sheet 21 (Zaria). Overseas Geology and Mineral Resources, 45 HMSO, London. (1973).
  42. Olade, A. Elueze, Petrochemistry of the Ilesha amphibolites and Precambrian crustal evolution in the Pan-African domain of SW Nigeria,  Precambrian Res., 8 (1979) 303-318. https://doi.org/10.1016/0301-9268(79)90033-0
  43. Grant, Structural distinction between a metasedimentary cover and an underlying basement in the 600 Ma old in the Pan-African domain of north-western Nigeria, Bulletin, 89 (1978) 50–58. https://doi.org/10.1130/0016-7606(1978)89<50:SDBAMC>2.0.CO;2
  44. Holt, R. The Geotectonic Evolution of the Anka Belt in the Precambrian Basement Complex of N.W. Nigeria, Unpublished Ph. D. Thesis, The Open University. 1982. https://doi.org/10.21954/ou.ro.000100d8
  45. Turner, Upper Proterozoic schist belts in the Nigerian sector of the Pan-African province of West Africa, Precambrian Res. , 21(1983) 55-79. https://doi.org/10.1016/0301-9268(83)90005-0
  46. Ajibade, A. C., Anyanwu, N. P. C., Okoro, A. U., & Nwajide, C. S. The Geology of Minna Area (Explanation of 1: 250,000 Sheet 42, Minna). Bulletin, (43) (2008).
  47. Ajibade, M. Woakes, M. Rahaman, Proterozoic crustal development in the Pan-African regime of Nigeria, In Kroner, A. (Ed.), Precambrian Plate Tectonics, Elsevier, Amsterdam, 17 (1981). https://doi.org/10.1029/GD017p0259
  48. Obaje, N. Geology and mineral resources of Nigeria Berlin: Springer, 120, 2009, 221.
  49. Oluyede, et al., Field occurrence, petrography, and structural characteristics of basement rocks of the northern part of Kushaka and Birnin Gwari schist belts, northwestern Nigeria, J. Natural Sci. Res., 12 (2021) 2224-3186. https://doi.org/10.7176/jnsr%2F12-12-02
  50. Agbor, Geology, and geochemistry of Zungeru amphibolites, north Central Nigeria, Univers. J. Geosci., 2 (2014) 116-122. https://doi.org/10.13189/ujg.2014.020402
  51. Ogezi, A. Geochemistry and Geochronology of Basement Rocks from Northwestern, Ni geria, Ph.D. Thesis, Leeds University, 1977.
  52. Ajayi, T.R. The geochemistry and origin of the amphibolites in Ife-Ilesha area, SW Nigeria, Niger Journal of Mining and Geology 17 (1980) 179–196
  53. Rahaman, M.A. Recent advances in the study of the basement complex of Nigeria. Abstract, 1st Symposium on the Precambrian Geology of Nigeria. (1981).
  54. Egbuniwe, I. Geotectonic evolution of the Maru Belt, NW Nigeria, Unpublished Ph.D. Thesis, University of Wales, Aberystwyth, 1982.
  55. Watkin, D. 30-meter SRTM elevation data downloader, 2024. http://dwtkns.com/srtm30m/
  56. Earth Explorer :United States Geological Survey,2024. https://earthexplorer.usgs.gov
  57. Ranganai, C. Ebinger, Aeromagnetic and Landsat TM structural interpretation for identifying regional groundwater exploration targets, south-central Zimbabwe Craton, J. Appl.Geoph., 65 (2008) 73-83. https://doi.org/10.1016/j.jappgeo.2008.05.009
  58. Fossi, Structural lineament mapping in a sub-tropical region using Landsat-8/SRTM data: a case study of Deng-Deng area in Eastern Cameroon, Arab. J. Geosci., 14 (2021) 2651. https://doi.org/10.1007/s12517-021-08848-9
  59. Mwaniki, M. Moeller, G. Schellmann, A comparison of Landsat 8 (OLI) and Landsat 7 (ETM+) in mapping geology and visualising lineaments: A case study of central region Kenya, Int. Archives Photo. Remote Sens. Spat. Inf. Sci., XL-7/W3 (2015) 897-903. https://doi.org/10.5194/isprsarchives-XL-7-W3-897-2015
  60. Crosta, J. Moore, Geological mapping using Landsat thematic mapper imagery in Almeria Province, South-east Spain, Int. J. Remote Sen., 10 (1989) 505-514. https://doi.org/10.1080/01431168908903888
  61. Q. Hung, N. Q. Dinh, O. Batelaan, V. T. Tam, D. Lagrou, Remote sensing, and GIS-based analysis of cave development in the Suoimuoi catchment (Son La-NW Vietnam), J. Cave Karst Stud., 64 (2002) 23-33.
  62. Mallast, et al., Derivation of groundwater flow-paths based on semi-automatic extraction of lineaments from remote sensing data, Hydrol. Earth Syst. Sci., 15 (2011) 2665-2678. https://doi.org/10.5194/hess-15-2665-2011
  63. Hamath, et. aaal., Mapping mafic dyke swarms, structural features, and hydrothermal alteration zones in Atar, Ahmeyim and Chami areas (Reguibat Shield, Northern Mauritania) using high-resolution aeromagnetic and gamma-ray spectrometry data, J. Afr. Earth. Sci., 163 (2020) 103749. https://doi.org/10.1016/j.jafrearsci.2019.103749
  64. C. Briggs, Machine contouring using minimum curvature, Geophys., 39 (1974) 39-48. https://doi.org/10.1190/1.1440410
  65. J. Blakely, Potential theory in gravity and magnetic applications. Cambridge university press, (1996). https://doi.org/10.1017/CBO9780511549816
  66. N. Nabighian, V. J. S. Grauch, R. O. Hansen, T. R. LaFehr, Y. Li, J. W. Peirce, J. D. Phillips, and M. E. Ruder, The historical development of the magnetic method in exploration. Geophys., 70 (2005) 33ND-61ND. https://doi.org/10.1190/1.2133784
  67. R. Cooper, D. R. Cowan, Filtering using variable order vertical derivatives. Comput. Geosci., 30 (2004) 455-459. https://doi.org/10.1016/j.cageo.2004.03.001
  68. N. Nabighian, The analytic signal of two-dimensional magnetic bodies with polygonal cross-section, its properties and use for automated anomaly interpretation. Geophys., 37 (1972) 507-517. https://doi.org/10.1190/1.1440276
  69. J. Blakely, R. W. Simpson, Approximating edges of source bodies from magnetic or gravity anomalies. Geophys., 51 (1986) 1494–1498. https://doi.org/10.1190/1.1442197
  70. R. Roest, J. Verhoef, M. Pilkington, Magnetic interpretation using the 3-D analytic signal. Geophys., 57 (1992) 116- 125. http://dx.doi.org/10.1190/1.1443174
  71. B. Thurston, R. S. Smith, J. Guillion, A multi-model method for depth estimation from magnetic data, Geophys., 67 (2002) 348-663. https://doi.org/10.1190/1.1468616
  72. G. Miller, V. Singh, Potential field tilt-A new concept for location of potential field sources. J. Appl. Geophys.,  32 (1994) 213–217. https://doi.org/10.1016/0926-9851(94)90022-1
  73. L. Airo, Regional interpretation of aerogeophysical data: Extracting compositional and structural features. In Airo, M. L. (Eds.), Aerogeophysics in Finland 1972–2004: Methods, System Characteristics and Applications. Geological Survey of Finland, Special Paper 39 (2005) 176-197.
  74. T. Pham, et. al., Determination of subsurface lineaments in the Hoang Sa islands using enhanced methods of gravity total horizontal gradient, Vietnam J. Earth Sci, 44 (2022) 395-409. https://doi.org/10.15625/2615-9783/17013
  75. E. Ekwok, et. al., Application of High-Precision Filters on Airborne Magnetic Data: A Case Study of the Ogoja Region, Southeast Nigeria. Minerals, 12 (2022) 1227. https://doi.org/10.3390/min12101227
  76. S. Ejepu, et. al., Predictive mapping of the mineral potential using geophysical and remote sensing datasets in parts of Federal Capital Territory, Abuja, north-central Nigeria. Earth Sciences, 9 (2020) 148-163. https://doi.org/10.11648/j.earth.20200905.12
  77. El Galladi, S. Araffa, M. Mekkawi, M. Abd-AlHai, Exploring mineralization zones using remote sensing and aeromagnetic data, West Allaqi Area, Eastern-Desert, Egypt, Egypt. J. Remote Sens. Space Sci., 25 (2022) 417-433. https://doi.org/10.1016/j.ejrs.2022.03.007
  78. S. Haruna,O. W. Osisanya, O. E. Agbalagba, A. I. Korode, T. A. Ibitoye, Application of aeromagnetic in determination of lineament of Hawal basement complex Northeast Nigeria. World News Nat. Sciences, 45 (2022) 58-92.
  79. J. Holden, J. C. Wong, P. Kovesi, D. Wedge, M. Dentith, L. Bagas, Identifying structural complexity in aeromagnetic data: An image analysis approach to greenfields gold exploration. Ore Geol. Rev., 46 (2012) 47-59. https://doi.org/10.1016/j.oregeorev.2011.11.002
  80. D. Phillips, Processing and interpretation of aeromagnetic data for the Santa Cruz Basin-Patagonia Mountains Area. South- central Arizona, US Geological Survey, New York (1998). https://doi.org/10.3133/ofr0298
  81. O. Akinluyi, et. al., Investigation of the influence of lineaments, lineament intersections and geology on groundwater yield in the basement complex terrain of Ondo State, Southwestern Nigeria,  Appl. Water Sci., 8 (2018) 1-13. http://dx.doi.org/10.1007/s13201-018-0686-x
  82. Boadi, et. al., Analysing multi-index overlay and fuzzy logic models for lode-gold prospectivity mapping in the Ahafo Gold District – Southwestern Ghana. Ore Geol. Rev., 148 (2022) 105059. https://doi.org/10.1016/j.oregeorev.2022.105059
  83. O. Sanusi, J. O. Amigun, Structural and hydrothermal alteration mapping related to orogenic gold mineralization in part of Kushaka schist belt, North-central Nigeria, using airborne magnetic and gamma-ray spectrometry data,  SN Appl. Sci., 2 (2020) 1-26. https://doi.org/10.1007/s42452-020-03435-1
  84. de Quadros, T. F., J. C. Koppe, A. J. Strieder, J. F. Costa, Mineral-potential mapping: a comparison of weights-of-evidence and fuzzy methods, Nat. Resour. Res., 15 (2006) 49-65. https://doi.org/10.1007/s11053-006-9010-9
  85. B. Shives, B. K. Charbonneau, and K. L. Ford, The detection of potassic alteration by gamma ray spectrometry recognition of alteration related to mineralization, Fourth Decennial Intern. Conf. Mineral Exploration, (Toronto, Canada), (1997) 345–353. http://dx.doi.org/10.1190/1.1444884
  86. S. Eshanibli, A. U. Osagie, N. A. Ismail, H. B. Ghanush, Analysis of gravity and aeromagnetic data to determine structural trend and basement depth beneath the Ajdabiya Trough in northeastern Libya. SN Appl. Sci., 3 (2021) 1-15. https://doi.org/10.1007/s42452-021-04263-7
  87. W. Saaty, The Analytic Hierarchy Process—What It Is and How It Is Used. Math. Modell., 9, (1987) 161-176. https://doi.org/10.1016/0270-0255(87)90473-8
  88. D. Goepel, Implementation of an Online Software Tool for the Analytic Hierarchy Process (AHP-OS). Int. J. Anal. Hierarchy Process, 10 (2018) 20469-20487. https://doi.org/10.13033/ijahp.v10i3.590
  89. L. Saaty, Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process. RWS Publications, Pennsylvania. (2006). https://doi.org/10.1007/978-94-015-9799-9_2
  90. H. Tsoukalas, R. E. Uhrig, Fuzzy and neural approaches in engineering, New York: Wiley. (1997).
  91. A. Burrough, R. A. McDonnell, C. D. Lloyd, Principles of Geographical Information Systems, Oxford: Oxford University Press. (1998).
  92. F. Bonham-Carter, Geographic Information Systems for Geoscientists: modelling with GIS (No. 13), Elsevier. (1994).
  93. P. Loughlin, Principal component analysis for alteration mapping. Photogramm. Eng. Remote Sens. , 57 (1991) 1163-1169.
  94. H. Sillitoe, Style of high Sulphidation Gold, Silver, and Copper Mineralisation in Porphyry and Epithermal Environments. Proceeding PACRIM Congress, Bali. (1999)
  95. L. Dickson, K. M. Scott, Interpretation of aerial gamma-ray surveys-adding the geochemical factors. AGSO J. Aust. Geol. Geophys.AGSO, 17 (1997) 187–200.
  96. C. Biondi, N. D. Franke, P. R. Carvalho, S. N. Villanova, Geologia do depósito de Au Cavalo Branco (Botuverá - SC), Revista Brasileira de Geociências, 37 (2007) 445-463. http://dx.doi.org/10.25249/0375-7536.2007373445463
  97. Hueck, M. A. Basei, N. A. Castro, Origin and evolution of the granitic intrusions in the Brusque Group of the Dom Feliciano Belt, south Brazil: petrostructural analysis and whole rock/isotope geochemistry, J. South Am. Earth Sci., 69 (2016) 131-151. https://doi.org/10.1016/j.jsames.2016.04.004
  98. Cudahy, Mineral mapping for exploration: an Australian journey of evolving spectral sensing technologies and industry collaboration. Geosci., 6 (2016) 52. https://doi.org/10.3390/geosciences6040052
  99. Traore, J. D. Wambo, C. P. Ndepete, S. Tekin, A. B. Pour, A. M. Muslim, Lithological and alteration mineral mapping for alluvial gold exploration in the southeast of Birao area, Central African Republic using Landsat-8 Operational Land Imager (OLI) data, J. Afr. Earth. Sci., 170 (2020) 103933. https://doi.org/10.1016/j.jafrearsci.2020.103933
  100. Shirmard, et. al., Integration of selective dimensionality reduction techniques for mineral exploration using ASTER satellite data, Remote Sens., 12 (2020) 1261. https://doi.org/10.3390/rs12081261
  101. Shi, N. Al-Arifi, M. Abdelkareem, F. Abdalla, Application of remote sensing and GIS techniques for exploring potential areas of hydrothermal mineralization in the central Eastern Desert of Egypt,  J. Taibah Univ. Sci., 14 (2020) 1421-1432. https://doi.org/10.1080/16583655.2020.1825184
  102. Moreaus, J. M. Reynoult, B. Deruelle, B. Robineau, A new tectonic model for the Cameroon Line, Central Africa. Tectonophysics, 139 (1987) 317-334. https://doi.org/10.1016/0040-1951(87)90206-X
  103. H. Robertson, Overview of the genesis and emplacement of Mesozoic ophiolites in the Eastern Mediterranean Tethyan region,  Lithos, 65 (2002) 1-67. https://doi.org/10.1016/S0024-4937(02)00160-3
  104. J. Jorgensen, W. Bosworth, Gravity modelling in the Central African Rift System, Sudan: Rift geometries and tectonic significance, J. Afr. Earth Sci., 8 (1989) 283-306. https://doi.org/10.1016/S0899-5362(89)80029-6
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