TOPSIS vs MIO: Applications to gold prospectivity mapping; a case study of the Basiran-Mokhtaran Area- Eastern Iran

[1]     C. Zheng et al., “Mineral prospectivity mapping based on Support vector machine and Random Forest algorithm – A case study from Ashele copper–zinc deposit, Xinjiang, NW China,” Ore Geol Rev, vol. 159, p. 105567, Aug. 2023, doi: 10.1016/j.oregeorev.2023.105567.

[2]     R. S. Davies, D. I. Groves, A. Trench, and M. Dentith, “Towards producing mineral resource-potential maps within a mineral systems framework, with emphasis on Australian orogenic gold systems,” Ore Geol Rev, vol. 119, no. January, p. 103369, 2020, doi: 10.1016/j.oregeorev.2020.103369.

[3]     S. A. A. S. Mirzabozorg and M. Abedi, “Recognition of mineralization-related anomaly patterns through an autoencoder neural network for mineral exploration targeting,” Applied Geochemistry, vol. 158, p. 105807, Nov. 2023, doi: 10.1016/j.apgeochem.2023.105807.

[4]     S. Sahoo, A. Singh, S. Biswas, and S. P. Sharma, “3D Subsurface Characterization of Banded Iron Formation Mineralization using Large-Scale Gravity Data: A Case Study in Parts of Bharatpur, Dausa and Karauli Districts of Rajasthan, India,” Natural Resources Research, vol. 30, no. 5, pp. 3121–3138, Oct. 2021, doi: 10.1007/s11053-021-09880-y.

[5]     Z. Wang, R. Zuo, and L. Jing, “Fusion of Geochemical and Remote-Sensing Data for Lithological Mapping Using Random Forest Metric Learning,” Math Geosci, vol. 53, no. 6, pp. 1125–1145, Aug. 2021, doi: 10.1007/s11004-020-09897-8.

[6]     Q. Cheng, “Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas,” J Geochem Explor, vol. 122, pp. 55–70, 2012, doi: 10.1016/j.gexplo.2012.07.007.

[7]     Y. Xiong, R. Zuo, and E. J. M. Carranza, “Mapping mineral prospectivity through big data analytics and a deep learning algorithm,” Ore Geol Rev, vol. 102, no. September, pp. 811–817, 2018, doi: 10.1016/j.oregeorev.2018.10.006.

[8]     M. Yousefi, O. P. Kreuzer, V. Nykänen, and J. M. A. Hronsky, “Exploration information systems – A proposal for the future use of GIS in mineral exploration targeting,” Ore Geol Rev, vol. 111, no. July, 2019, doi: 10.1016/j.oregeorev.2019.103005.

[9]     Z. PENGDA, C. QIUMING, and X. QINGLIN, “Quantitative Prediction for Deep Mineral Exploration,” Journal of China University of Geosciences, vol. 19, no. 4, pp. 309–318, Aug. 2008, doi: 10.1016/S1002-0705(08)60063-1.

[10]   E. J. M. Carranza, Geochemical Anomaly and Mineral Prospectivity Mapping in GIS, no. November. 2009.

[11]   M. Yousefi, E. J. M. Carranza, O. P. Kreuzer, V. Nykänen, J. M. A. Hronsky, and M. J. Mihalasky, “Data analysis methods for prospectivity modelling as applied to mineral exploration targeting: State-of-the-art and outlook,” J Geochem Explor, vol. 229, no. April, 2021, doi: 10.1016/j.gexplo.2021.106839.

[12]   A. Shabani, M. Ziaii, M. Monfared, A. Shirazy, and A. Shirazi, “Multi-Dimensional Data Fusion for Mineral Prospectivity Mapping (MPM) Using Fuzzy-AHP Decision-Making Method, Kodegan-Basiran Region, East Iran,” Minerals, vol. 12, no. 12, p. 1629, Dec. 2022, doi: 10.3390/min12121629.

[13]   B. Boadi, P. V. Sunder Raju, and D. D. Wemegah, “Analysing multi-index overlay and fuzzy logic models for lode-gold prospectivity mapping in the Ahafo gold district – Southwestern Ghana,” Ore Geol Rev, vol. 148, p. 105059, Sep. 2022, doi: 10.1016/j.oregeorev.2022.105059.

[14]   S. Riahi, A. Bahroudi, M. Abedi, D. R. Lentz, and S. Aslani, “Application of data-driven multi-index overlay and BWM-MOORA MCDM methods in mineral prospectivity mapping of porphyry Cu mineralization,” J Appl Geophy, vol. 213, p. 105025, Jun. 2023, doi: 10.1016/j.jappgeo.2023.105025.

[15]   D. I. Groves, M. Santosh, and L. Zhang, “A scale-integrated exploration model for orogenic gold deposits based on a mineral system approach,” Geoscience Frontiers, vol. 11, no. 3, pp. 719–738, 2020, doi: 10.1016/j.gsf.2019.12.007.

[16]   M. Yousefi and V. Nykänen, “Introduction to the special issue: GIS-based mineral potential targeting,” Journal of African Earth Sciences, vol. 128, pp. 1–4, Apr. 2017, doi: 10.1016/j.jafrearsci.2017.02.023.

[17]   A. Aryafar and B. Roshanravan, “Improved index overlay mineral potential modeling in brown- and green-fields exploration using geochemical, geological and remote sensing data,” Earth Sci Inform, vol. 13, no. 4, pp. 1275–1291, 2020, doi: 10.1007/s12145-020-00509-x.

[18]   G. F. Bonham-Carter, “Geographic information systems for geoscientists: Modelling with GIS,” Comput Geosci, vol. 21, no. 9, pp. 1110–1112, 1995, doi: 10.1016/0098-3004(95)90019-5.

[19]   M. Abedi, S. B. Mostafavi Kashani, G. H. Norouzi, and M. Yousefi, “A deposit scale mineral prospectivity analysis: A comparison of various knowledge-driven approaches for porphyry copper targeting in Seridune, Iran,” Journal of African Earth Sciences, vol. 128, pp. 127–146, 2017, doi: 10.1016/j.jafrearsci.2016.09.028.

[20]   E. J. M. Carranza, “Geocomputation of mineral exploration targets,” Comput Geosci, vol. 37, no. 12, pp. 1907–1916, Dec. 2011.

[21]   M. Yousefi and E. J. M. Carranza, “Geometric average of spatial evidence data layers: A GIS-based multi-criteria decision-making approach to mineral prospectivity mapping,” Comput Geosci, vol. 83, pp. 72–79, Oct. 2015, doi: 10.1016/j.cageo.2015.07.006.

[22]   M. Krstić, S. Tadić, M. Kovač, V. Roso, and S. Zečević, “A Novel Hybrid MCDM Model for the Evaluation of Sustainable Last Mile Solutions,” Math Probl Eng, vol. 2021, pp. 1–17, Oct. 2021, doi: 10.1155/2021/5969788.

[23]   V. Nykänen and V. J. Ojala, “Spatial analysis techniques as successful mineral-potential mapping tools for orogenic gold deposits in the northern Fennoscandian shield, Finland,” Natural Resources Research, vol. 16, no. 2, pp. 85–92, Jun. 2007, doi: 10.1007/S11053-007-9046-5.

[24]   S. Riahi, A. Bahroudi, M. Abedi, S. Aslani, and D. R. Lentz, “Evidential data integration to produce porphyry Cu prospectivity map, using a combination of knowledge and data‐driven methods,” Geophys Prospect, vol. 70, no. 2, pp. 421–437, Feb. 2022, doi: 10.1111/1365-2478.13169.

[25]   M. Alavi, “Sedimentary and structural characteristics of the paleo-Tethys remnants in northeastern Iran,” Geol Soc Am Bull, vol. 103, pp. 983–992, 1991.

[26]   A. Aghanabati, Geology of Iran. Tehran: Geological Survey of Iran, 2005.

[27]   V. E. Camp, R. J. Griffis, G. R. Camp V, V. E. Camp, and R. J. Griffis, “Character, genesis and tectonic setting of igneous rocks in the Sistan suture zone, eastern Iran,” Lithos, vol. Lithos 15, no. 3, pp. 221–239, 1982, doi: 10.1016/0024-4937(82)90014-7.

[28]   R. Tirrul, I. R. Bell, R. J. Griffis, and V. E. Camp, “The Sistan suture zone of eastern Iran,” GSA Bulletin, vol. 94, no. 1, pp. 134–150, Jan. 1983, doi: 10.1130/0016-7606(1983)94<134:TSSZOE>2.0.CO;2.

[29]   B. Meyer and K. Le Dortz, “Strike-slip kinematics in Central and Eastern Iran: Estimating fault slip-rates averaged over the Holocene,” Tectonics, vol. 26, no. 5, p. n/a-n/a, Oct. 2007, doi: 10.1029/2006TC002073.

[30]   J. Jackson and D. McKenzie, “Active tectonics of the Alpine--Himalayan Belt between western Turkey and Pakistan,” Geophys J Int, vol. 77, no. 1, pp. 185–264, Apr. 1984, doi: 10.1111/j.1365-246X.1984.tb01931.x.

[31]   M. Ghorbani, Geological Setting and Crustal Structure of Iran. 2021. doi: 10.1007/978-3-030-71109-2_1.

[32]   R. Walker and J. Jackson, “Active tectonics and late Cenozoic strain distribution in central and eastern Iran,” Tectonics, vol. 23, no. 5, p. n/a-n/a, Oct. 2004, doi: 10.1029/2003TC001529.

[33]   S. Samimi, E. Gholami, M. M. Khatib, S. Madanipour, and F. Lisker, “Transpression and Exhumation of Granitoid Plutons along the Northern Part of the Nehbandan Fault System in the Sistan Suture Zone, Eastern Iran,” Geotectonics, vol. 54, no. 1, pp. 130–144, Jan. 2020, doi: 10.1134/S0016852120010124.

[34]   M. Delaloye and J. Desmons, “Ophiolites and melange terranes in Iran: A geochronological study and its paleotectonic implications,” Tectonophysics, vol. 68, no. 1–2, pp. 83–111, Sep. 1980, doi: 10.1016/0040-1951(80)90009-8.

[35]   Z. Khajehmiri, M. R. Shayestehfar, and H. Moeinzadeh, “Using Spectral Angle Method to Detect Alterations in Sheets of Mokhtaran and Sarchahshur,” vol. 1, no. 1, pp. 11–22, 2018.

[36]   J. Golonka, “Plate tectonic evolution of the southern margin of Eurasia in the Mesozoic and Cenozoic,” Tectonophysics, vol. 381, no. 1–4, pp. 235–273, Mar. 2004, doi: 10.1016/j.tecto.2002.06.004.

[37]   D. Jung, J. Keller, R. Khorasani, Chr. Marcks, A. Baumann, and P. Horn, “Petrology of the Tertiary Magmatic Activity in the Northern Lut Area, East Iran,” Neues Jahrb Geol Palaontol Abh, vol. 168, no. 2–3, pp. 417–467, Jun. 1984, doi: 10.1127/njgpa/168/1984/417.

[38]   A. Malekzadeh Shafaroudi, M. H. Karimpour, and C. R. Stern, “The Khopik porphyry copper prospect, Lut Block, Eastern Iran: Geology, alteration and mineralization, fluid inclusion, and oxygen isotope studies,” Ore Geol Rev, vol. 65, pp. 522–544, 2015, doi: https://doi.org/10.1016/j.oregeorev.2014.04.015.

[39]   B. A. Tarkian M, Lotfi M, “Tectonic, magmatism and the formation of mineral deposits in the central Lut, east Iran, Ministry of mines and metals, GSI, Geodynamic project (geotraverse) in Iran, Geological Survey of Iran,” Report 51, Iran, 1983.

[40]   A. Behrouzi, N. K. Nazer, F. Ezattian, M. Davari, and I. Eftekharnezhad, Geological Map Of Iran - 1:100,000 Series, Sheet 7754 - Basiran. Tehran: Geological Survey of Iran, 1992.

[41]   H. Movahhed, M. H. Emami, J. EftekharNezhad, and J. Stocklin, Geological Map Of Iran - 1:100,000 Series, Sheet 7854 - Mokhtaran. Tehran: Geological Survey of Iran, 1978.

[42]   R. Arjmandzadeh, S. Alirezaei, and A. Almasi, “Tectonomagmatic reconstruction of the Upper Mesozoic–Cenozoic Neotethyan arcs in the Lut block, East Iran: a review and synthesis,” Turkish Journal of Earth Sciences, vol. 31, no. 6, pp. 520–544, 2022, doi: 10.55730/1300-0985.1818.

[43]   S. Samiee, M. H. Karimpour, M. Ghaderi, M. R. Haidarian Shahri, U. Klöetzli, and J. F. Santos, “Petrogenesis of subvolcanic rocks from the Khunik prospecting area, south of Birjand, Iran: Geochemical, Sr–Nd isotopic and U–Pb zircon constraints,” J Asian Earth Sci, vol. 115, pp. 170–182, 2016, doi: https://doi.org/10.1016/j.jseaes.2015.09.023.

[44]   N. Vafaei, R. A. Ribeiro, and L. M. Camarinha-Matos, “Normalization Techniques for Multi-Criteria Decision Making: Analytical Hierarchy Process Case Study,” 2016, pp. 261–269. doi: 10.1007/978-3-319-31165-4_26.

[45]   M. Yousefi and E. J. M. Carranza, “Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping,” Comput Geosci, vol. 74, pp. 97–109, 2015, doi: 10.1016/j.cageo.2014.10.014.

[46]   A. Jahan and K. L. Edwards, “A state-of-the-art survey on the influence of normalization techniques in ranking: Improving the materials selection process in engineering design,” Materials & Design (1980-2015), vol. 65, pp. 335–342, 2015, doi: https://doi.org/10.1016/j.matdes.2014.09.022.

[47]   E. D. Forson et al., “Data-driven multi-index overlay gold prospectivity mapping using geophysical and remote sensing datasets,” Journal of African Earth Sciences, vol. 190, p. 104504, Jun. 2022, doi: 10.1016/j.jafrearsci.2022.104504.

[48]   M. Yousefi, S. Yousefi, and A. Kamkar-Rouhani, “Recognition coefficient of spatial geological features, an approach to facilitate criteria weighting for mineral exploration targeting,” IJMGE, vol. 57, no. 3, pp. 251–258, 2023, doi: 10.22059/IJMGE.2023.355380.595037.

[49]   P. Afzal, R. A. Asl, A. Adib, and A. B. Yasrebi, “Application of Fractal Modelling for Cu Mineralisation Reconnaissance by ASTER Multispectral and Stream Sediment Data in Khoshname Area, NW Iran,” Journal of the Indian Society of Remote Sensing, vol. 43, no. 1, pp. 121–132, 2015, doi: 10.1007/s12524-014-0384-6.

[50]   M. Yousefi and E. J. M. Carranza, “Prediction-area (P-A) plot and C-A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling,” Comput Geosci, vol. 79, pp. 69–81, 2015, doi: 10.1016/j.cageo.2015.03.007.

[51]   R. Ghezelbash, A. Maghsoudi, A. Bigdeli, and E. J. M. Carranza, “Regional-Scale Mineral Prospectivity Mapping: Support Vector Machines and an Improved Data-Driven Multi-criteria Decision-Making Technique,” Natural Resources Research, vol. 30, no. 3, pp. 1977–2005, 2021, doi: 10.1007/s11053-021-09842-4.

[52]   M. Yousefi and J. M. A. Hronsky, “Translation of the function of hydrothermal mineralization-related focused fluid flux into a mappable exploration criterion for mineral exploration targeting,” Applied Geochemistry, vol. 149, no. October 2022, p. 105561, 2023, doi: 10.1016/j.apgeochem.2023.105561.

[53]   M. Parsa, A. Maghsoudi, M. Yousefi, and M. Sadeghi, “Recognition of significant multi-element geochemical signatures of porphyry Cu deposits in Noghdouz area, NW Iran,” J Geochem Explor, vol. 165, pp. 111–124, 2016, doi: 10.1016/j.gexplo.2016.03.009.

[54]   K. Yoon, “A Reconciliation Among Discrete Compromise Solutions,” Journal of the Operational Research Society, vol. 38, no. 3, pp. 277–286, Mar. 1987, doi: 10.1057/jors.1987.44.

[55]   M. Abedi and G.-H. Norouzi, “A general framework of TOPSIS method for integration of airborne geophysics, satellite imagery, geochemical and geological data,” International Journal of Applied Earth Observation and Geoinformation, vol. 46, pp. 31–44, 2016, doi: https://doi.org/10.1016/j.jag.2015.11.016.

[56]   F. Feizi, A. Karbalaei-Ramezanali, and H. Tusi, “Mineral Potential Mapping Via TOPSIS with Hybrid AHP–Shannon Entropy Weighting of Evidence: A Case Study for Porphyry-Cu, Farmahin Area, Markazi Province, Iran,” Natural Resources Research, vol. 26, no. 4, pp. 553–570, Oct. 2017, doi: 10.1007/s11053-017-9338-3.

[57]   E. K. Zavadskas, A. Mardani, Z. Turskis, A. Jusoh, and K. M. Nor, Development of TOPSIS Method to Solve Complicated Decision-Making Problems - An Overview on Developments from 2000 to 2015, vol. 15, no. 3. 2016. doi: 10.1142/S0219622016300019.

[58]   H. Deng, C.-H. Yeh, and R. J. Willis, “Inter-company comparison using modified TOPSIS with objective weights,” Comput Oper Res, vol. 27, no. 10, pp. 963–973, Sep. 2000, doi: 10.1016/S0305-0548(99)00069-6.

[59]   H. Bahrami, S. Homayouni, A. Safari, S. Mirzaei, M. Mahdianpari, and O. Reisi-Gahrouei, “Deep learning-based estimation of crop biophysical parameters using multi-source and multi-temporal remote sensing observations,” Agronomy, vol. 11, no. 7, 2021, doi: 10.3390/agronomy11071363.

[60]   V. Lisitsin, “Spatial data analysis of mineral deposit point patterns: Applications to exploration targeting,” Ore Geol Rev, vol. 71, pp. 861–881, 2015, doi: 10.1016/j.oregeorev.2015.05.019.

[61]   S. Ghasemzadeh, A. Maghsoudi, M. Yousefi, and M. J. Mihalasky, “Stream sediment geochemical data analysis for district-scale mineral exploration targeting: Measuring the performance of the spatial U-statistic and C-A fractal modeling,” Ore Geol Rev, vol. 113, p. 103115, Oct. 2019, doi: 10.1016/j.oregeorev.2019.103115.

[62]   M. E. Doherty, K. Arndt, Z. Chang, K. Kelley, and O. Lavin, “Stream sediment geochemistry in mineral exploration: a review of fine-fraction, clay-fraction, bulk leach gold, heavy mineral concentrate and indicator mineral chemistry,” Geochemistry: Exploration, Environment, Analysis, Jun. 2023, doi: 10.1144/geochem2022-039.

[63]   A. Saydi, M. Abedi, A. Bahroudi, and H. Ferdowsi, “Geochemical prospectivity of Cu-mineralization through concentration-number fractal modeling and prediction-area plot: a case study in East Iran,” International Journal of Mining and Geo-Engineering, vol. 57, no. 2, pp. 159–169, Jun. 2023, doi: 10.22059/IJMGE.2022.347447.594993.

[64]   A. B. Pour and M. Hashim, “Hydrothermal alteration mapping from Landsat-8 data, Sar Cheshmeh copper mining district, south-eastern Islamic Republic of Iran,” Journal of Taibah University for Science, vol. 9, no. 2, pp. 155–166, 2015, doi: 10.1016/j.jtusci.2014.11.008.

[65]   E. Jude Steven, A. Suleiman, A. Asema Ibrahim, and U. 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, p. 148, 2020, doi: 10.11648/j.earth.20200905.12.

[66]   F. Mami, S. Barak, M. Abedi, and S. Yousefi, “Gold prospectivity mapping through generation and integration of geophysical, geochemical, remote sensing, and geological evidence layers in Saqez area, NW Iran”, doi: 10.22059/IJMGE.2023.358626.595062.

[67]   M. Airo, “Geophysical signatures of deposits,” Geological Survey of Finland, vol. 58, no. 58. pp. 9–70, 2015.

[68]   A. M. SILVA, A. C. B. PIRES, A. MCCAFFERTY, R. A. V. DE MORAES, and H. XIA, “Application of airborne geophysical data to mineral exploration in the uneven exposed terrains of the Rio das Velhas greenstone belt,” Revista Brasileira de Geociências, vol. 33, no. 2, pp. 17–28, Jun. 2003, doi: 10.25249/0375-7536.200333S21728.

[69]   A. A. El-Raouf, F. Doğru, K. Abdelrahman, M. S. Fnais, A. El Manharawy, and O. Amer, “Using Airborne Geophysical and Geochemical Methods to Map Structures and Their Related Gold Mineralization,” Minerals, vol. 13, no. 2, p. 237, Feb. 2023, doi: 10.3390/min13020237.

[70]   A. M. Silva*, C. G. de Oliveira, G. C. Marques, and A. C. B. Pires, “Relationship between airborne geophysical signatures and hydrothermal rocks with Cu-Au mineralization in the Mara Rosa Magmatic Arc, Central Brazil,” in 10th International Congress of the Brazilian Geophysical Society & EXPOGEF 2007, Rio de Janeiro, Brazil, 19-23 November 2007, Brazilian Geophysical Society, Nov. 2007, pp. 999–1003. doi: 10.1190/sbgf2007-192.

[71]   J. Torppa, V. Nykänen, and F. Molnár, “Unsupervised clustering and empirical fuzzy memberships for mineral prospectivity modelling,” Ore Geol Rev, vol. 107, no. January, pp. 58–71, 2019, doi: 10.1016/j.oregeorev.2019.02.007.

[72]   T. Sun, F. Chen, L. Zhong, W. Liu, and Y. Wang, “GIS-based mineral prospectivity mapping using machine learning methods: A case study from Tongling ore district, eastern China,” Ore Geol Rev, vol. 109, no. April, pp. 26–49, Jun. 2019, doi: 10.1016/j.oregeorev.2019.04.003.

[73]   G. Partington, “Developing models using GIS to assess geological and economic risk: An example from VMS copper gold mineral exploration in Oman,” Ore Geol Rev, vol. 38, no. 3, pp. 197–207, Nov. 2010, doi: 10.1016/j.oregeorev.2010.02.002.

[74]   M. Mohammadpour, A. Bahroudi, and M. Abedi, “Automatic Lineament Extraction Method in Mineral Exploration Using CANNY Algorithm and Hough Transform,” Geotectonics, vol. 54, no. 3, pp. 366–382, 2020, doi: 10.1134/S0016852120030085.

[75]   S. G. Hagemann, V. A. Lisitsin, and D. L. Huston, “Mineral system analysis: Quo vadis,” Ore Geol Rev, vol. 76, pp. 504–522, Jul. 2016.

[76]   J. P. Richards, T. Spell, E. Rameh, A. Razique, and T. Fletcher, “High Sr/Y magmas reflect arc maturity, high magmatic water content, and porphyry Cu ± Mo ± Au potential: Examples from the tethyan arcs of central and eastern iran and Western Pakistan,” Economic Geology, vol. 107, no. 2, pp. 295–332, 2012, doi: 10.2113/econgeo.107.2.295.

[77]   M. Billa et al., “Predicting gold-rich epithermal and porphyry systems in the central Andes with a continental-scale metallogenic GIS,” Ore Geol Rev, vol. 25, no. 1–2, pp. 39–67, 2004, doi: 10.1016/j.oregeorev.2004.01.002.

[78]   R. H. Sillitoe, “Porphyry copper systems,” Economic Geology, vol. 105, no. 1, pp. 3–41, 2010, doi: 10.2113/gsecongeo.105.1.3.

[79]   N. T. T. Hang, D. D. Thanh, and L. H. Minh, “Application of directional derivative method to determine boundary of magnetic sources by total magnetic anomalies,” VIETNAM JOURNAL OF EARTH SCIENCES, vol. 39, no. 4, Sep. 2017, doi: 10.15625/0866-7187/39/4/10731.

[80]   L. Pham Thanh et al., “Determination of subsurface lineaments in the Hoang Sa islands using enhanced methods of gravity total horizontal gradient,” Vietnam Journal of Earth Sciences, Mar. 2022, doi: 10.15625/2615-9783/17013.

[81]   P. J. Gunn, B. R. S. Minty, and P. R. Milligan, “The-Airborne-Gamma-Ray-Spectrometric-Response-Over-Arid-Australian-Terranes,” Fourth Decennial International Conference on Mineral Exploration, pp. 733–740, 1997.

[82]   B. L. Dickson and K. M. Scott, “Interpretation of aerial gamma-ray survey - adding geochemical factors,” AGSO J Aust Geol Geophys, vol. 17, no. 2, pp. 187–200, 1997.

[83]   S. H. Abd El Nabi, “Role of γ-ray spectrometry in detecting potassic alteration associated with Um Ba’anib granitic gneiss and metasediments, G. Meatiq area, Central Eastern Desert, Egypt,” Arabian Journal of Geosciences, vol. 6, no. 4, pp. 1249–1261, Apr. 2013, doi: 10.1007/s12517-011-0378-4.

[84]   I. C. Okeyode, O. T. Olurin, S. A. Ganiyu, and J. A. Olowofela, “High resolution airborne radiometric and magnetic studies of ilesha and its environs, southwestern Nigeria,” Materials and Geoenvironment, vol. 66, no. 1, pp. 51–73, Mar. 2019, doi: 10.2478/rmzmag-2018-0020.

[85]   D. B. Hoover and H. A. Pierce, “Annotated bibliography of gamma-ray methods applied to gold exploration,” 1990.

[86]   F. Feizi, A. Karbalaei-Ramezanali, and H. Tusi, “Mineral Potential Mapping Via TOPSIS with Hybrid AHP–Shannon Entropy Weighting of Evidence: A Case Study for Porphyry-Cu, Farmahin Area, Markazi Province, Iran,” Natural Resources Research, vol. 26, no. 4, pp. 553–570, Oct. 2017, doi: 10.1007/s11053-017-9338-3.

[87]   Y. Ma, J. Zhao, Y. Sui, S. Liao, and Z. Zhang, “Application of knowledge-driven methods for mineral prospectivity mapping of polymetallic sulfide deposits in the southwest indian ridge between 46◦ and 52◦e,” Minerals, vol. 10, no. 11, pp. 1–18, 2020, doi: 10.3390/min10110970.

[88]   H. Rahimi, M. Abedi, M. Yousefi, A. Bahroudi, and G. R. Elyasi, “Supervised mineral exploration targeting and the challenges with the selection of deposit and non-deposit sites thereof,” Applied Geochemistry, vol. 128, May 2021, doi: 10.1016/j.apgeochem.2021.104940.

[89]   F. Provost and T. Fawcett, “Robust Classification for Imprecise Environments,” Mach Learn, vol. 42, pp. 203–231, 2001, doi: https://doi.org/10.1023/A:1007601015854.

[90]   T. Fawcett, “An introduction to ROC analysis,” Pattern Recognit Lett, vol. 27, no. 8, pp. 861–874, Jun. 2006, doi: 10.1016/j.patrec.2005.10.010.

[91]   V. Nykänen, I. Lahti, T. Niiranen, and K. Korhonen, “Receiver operating characteristics (ROC) as validation tool for prospectivity models - A magmatic Ni-Cu case study from the Central Lapland Greenstone Belt, Northern Finland,” Ore Geol Rev, vol. 71, pp. 853–860, 2015, doi: 10.1016/j.oregeorev.2014.09.007.

[92]   V. Nykänen, I. Lahti, T. Niiranen, and K. Korhonen, “Receiver operating characteristics (ROC) as validation tool for prospectivity models - A magmatic Ni-Cu case study from the Central Lapland Greenstone Belt, Northern Finland,” Ore Geol Rev, vol. 71, pp. 853–860, 2015, doi: 10.1016/j.oregeorev.2014.09.007.E. J. M. Carranza and A. G. Laborte, “Data-driven predictive mapping of gold prospectivity, Baguio district, Philippines: Application of Random Forests algorithm,” Ore Geol. Rev., vol. 71, pp. 777–787, 2015.