Citation: | Fan Xiao, Qiuming Cheng, Weisheng Hou, Frederik P. Agterberg. Three-Dimensional Prospectivity Modeling of Jinshan Ag-Au Deposit, Southern China by Weights-of-Evidence. Journal of Earth Science, 2025, 36(5): 2038-2057. doi: 10.1007/s12583-023-1822-6 |
To comprehensively utilize the valuable geological map, exploration profile, borehole, and geochemical logging data and the knowledge on the formation of the Jinshan Ag-Au deposit for forecasting the exploration targets of concealed ore bodies, three-dimensional Mineral Prospectivity Modeling (MPM) of the deposit has been conducted using the weights-of-evidence (WofE) method. Conditional independence between evidence layers was tested, and the outline results using the prediction-volume (
Abedi, M., Norouzi, G. H., 2012. Integration of Various Geophysical Data with Geological and Geochemical Data to Determine Additional Drilling for Copper Exploration. Journal of Applied Geophysics, 83: 35–45. https://doi.org/10.1016/j.jappgeo.2012.05.003 |
Afzal, P., Ahari, H. D., Omran, N. R., et al., 2013. Delineation of Gold Mineralized Zones Using Concentration-Volume Fractal Model in Qolqoleh Gold Deposit, NW Iran. Ore Geology Reviews, 55: 125–133. https://doi.org/10.1016/j.oregeorev.2013.05.005 |
Afzal, P., Alghalandis, Y. F., Khakzad, A., et al., 2011. Delineation of Mineralization Zones in Porphyry Cu Deposits by Fractal Concentration-Volume Modeling. Journal of Geochemical Exploration, 108(3): 220–232 |
Agterberg, F. P., 1974. Automatic Contouring of Geological Maps to Detect Target Areas for Mineral Exploration. Journal of the International Association for Mathematical Geology, 6(4): 373–395. https://doi.org/10.1007/bf02082358 |
Agterberg, F. P., 1989. Computer Programs for Mineral Exploration. Science (New York, NY), 245(4913): 76–81. https://doi.org/10.1126/science.245.4913.76 |
Agterberg, F. P., Bonham-Carter, G. F., 2005. Measuring the Performance of Mineral-Potential Maps. Natural Resources Research, 14(1): 1–17. https://doi.org/10.1007/s11053-005-4674-0 |
Agterberg, F. P., Bonham-Carter, G. F., Cheng, Q. M., et al., 1993. Weights of Evidence Modeling and Weighted Logistic Regression for Mineral Potential Mapping, In: Davis, J. C., Herzfeld, U. C., eds., Computers in Geology, 25 Years of Progress. Oxford University Press, Oxford |
Agterberg, F. P., Bonham-Carter, G. F., Wright, D. F., 1990. Statistical Pattern Integration for Mineral Exploration, In: Gaál, G., Merriam, D. F., eds., Computer Applications in Resource Estimation. Pergamon Press, Oxford. |
Agterberg, F. P., Cheng, Q. M., 2002. Conditional Independence Test for Weights-of-Evidence Modeling. Natural Resources Research, 11(4): 249–255. https://doi.org/10.1023/a:1021193827501 |
Agterberg, F., 2011. A Modified Weights-of-Evidence Method for Regional Mineral Resource Estimation. Natural Resources Research, 20(2): 95–101. https://doi.org/10.1007/s11053-011-9138-0 |
Apel, M., 2006. From 3D Geomodelling Systems towards 3D Geoscience Information Systems: Data Model, Query Functionality, and Data Management. Computers & Geosciences, 32(2): 222–229. https://doi.org/10.1016/j.cageo.2005.06.016 |
Bonham-Carter, G. F., 1994. Geographic Information Systems for Geoscientists: Modeling with GIS, Computer Methods in the Geosciences. Pergamon, New York |
Cai, M. H., Zhan, M. G., Peng, S. B., et al., 2002. Study of Mesozoic Metallogenic Geological Setting and Dynamic Mechanism in Yunkai Area. Mineral Deposits, 21(3): 264–269 (in Chinese with English Abstract) |
Carranza, E. J. M., 2004. Weights of Evidence Modeling of Mineral Potential: A Case Study Using Small Number of Prospects, Abra, Philippines. Natural Resources Research, 13(3): 173–187. https://doi.org/10.1023/b:narr.0000046919.87758.f5 |
Carranza, E. J. M., 2011. Editorial: Geocomputation of Mineral Exploration Targets. Computers & Geosciences, 37(12): 1907–1916. https://doi.org/10.1016/j.cageo.2011.11.009 |
Carranza, E. J. M., Laborte, A. G., 2015. Random Forest Predictive Modeling of Mineral Prospectivity with Small Number of Prospects and Data with Missing Values in Abra (Philippines). Computers & Geosciences, 74: 60–70. https://doi.org/10.1016/j.cageo.2014.10.004 |
Chen, Y. L., Wu, W., 2016. A Prospecting Cost-Benefit Strategy for Mineral Potential Mapping Based on ROC Curve Analysis. Ore Geology Reviews, 74: 26–38. https://doi.org/10.1016/j.oregeorev.2015.11.011 |
Cheng, Q. M., 2015. BoostWofE: A New Sequential Weights of Evidence Model Reducing the Effect of Conditional Dependency. Mathematical Geosciences, 47(5): 591–621. https://doi.org/10.1007/s11004-014-9578-2 |
Cheng, Q. M., Agterberg, F. P., 1999. Fuzzy Weights of Evidence Method and Its Application in Mineral Potential Mapping. Natural Resources Research, 8(1): 27–35. https://doi.org/10.1023/a:1021677510649 |
Cheng, Q. M., Agterberg, F. P., Ballantyne, S. B., 1994. The Separation of Geochemical Anomalies from Background by Fractal Methods. Journal of Geochemical Exploration, 51(2): 109–130. https://doi.org/10.1016/0375-6742(94)90013-2 |
Chung, C. F., 1977. An Application of Discriminant Analysis for the Evaluation of Mineral Potential, In: Ramani, R. V., ed., Application of Computer Methods in the MineralIndustry, Proceedings of the 14th APCOM Symposium, Society of Mining Engineers of American Institute of Mining, Metallurgical, and Petroleum Engineers, New York |
de Kemp, E. A., 2000. 3-D Visualization of Structural Field Data: Examples from the Archean Caopatina Formation, Abitibi Greenstone Belt, Québec, Canada. Computers & Geosciences, 26(5): 509–530. https://doi.org/10.1016/s0098-3004(99)00142-9 |
de Kemp, E. A., Monecke, T., Sheshpari, M., et al., 2011. 3D GIS as a Support for Mineral Discovery. Geochemistry-Exploration Environment Analysis, 11(2): 117–128 |
de Kemp, E. A., Sprague, K. B., 2003. Interpretive Tools for 3-D Structural Geological Modeling Part Ⅰ: Bézier-Based Curves, Ribbons and Grip Frames. Geoinformatica, 7(1): 55–71. https://doi.org/10.1023/a:1022822227691 |
Deng, H., Zheng, Y., Chen, J., et al., 2020. Deep Learning-Based 3D Prediction Model for the Dayingezhuang Gold Deposit, Shandong Province. Acta Geoscientica Sinica, 41(2): 157–165 (in Chinese with English Abstract) |
Deng, M. F., 2009. A Conditional Dependence Adjusted Weights of Evidence Model. Natural Resources Research, 18(4): 249–258. https://doi.org/10.1007/s11053-009-9101-5 |
DeWolfe, Y. M., Gibson, H. L., Richardson, D., 2018. 3D Reconstruction of Volcanic and Ore-Forming Environments of a Giant VMS System: A Case Study from the Kidd Creek Mine, Canada. Ore Geology Reviews, 101: 532–555. https://doi.org/10.1016/j.oregeorev.2018.07.008 |
Ding, R. X., Yu, P. P., Hu, G. M., et al., 2018. Thermochornology of Pangxidong Fault Zone in Southern Section of Qin-Hang Metallogenic Belt. Earth Science, 43(6): 1830–1838 (in Chinese with English Abstract) |
Ding, R. X., Zou, H. P., Lao, M. J., et al., 2015. Indosinian Activity Records of Ductile Shear Zones in Southern Segment of Qin-Hang Combined Belt: A Case Study of Fangcheng-Lingshan Fault Zone. Earth Science Frontiers, 22(2): 79–85 (in Chinese with English Abstract) |
Ford, A., Miller, J. M., Mol, A. G., 2016. A Comparative Analysis of Weights of Evidence, Evidential Belief Functions, and Fuzzy Logic for Mineral Potential Mapping Using Incomplete Data at the Scale of Investigation. Natural Resources Research, 25(1): 19–33. https://doi.org/10.1007/s11053-015-9263-2 |
Fu, G. M., Lü, Q. T., Yan, J. Y., et al., 2021. 3D Mineral Prospectivity Modeling Based on Machine Learning: A Case Study of the Zhuxi Tungsten Deposit in Northeastern Jiangxi Province, South China. Ore Geology Reviews, 131: 104010. https://doi.org/10.1016/j.oregeorev.2021.104010 |
Geng, W. H., Li, B. P., 1993. Metallogenic Regularity and Exploring Indicator for Altered Rock Type Au-Ag Deposits in Southeastern Guangxi, China. Mineral Resources and Geology, 7(3): 183–187 (in Chinese with English Abstract) |
Gholampour, O., Hezarkhani, A., Maghsoudi, A., et al., 2019. Application of Sequential Gaussian Simulation and Concentration-Volume Fractal Model to Delineate Alterations in Hypogene Zone of Miduk Porphyry Copper Deposit, SE Iran. Journal of African Earth Sciences, 150: 389–400. https://doi.org/10.1016/j.jafrearsci.2018.07.002 |
Harris, D., Zurcher, L., Stanley, M., et al., 2003. A Comparative Analysis of Favorability Mappings by Weights of Evidence, Probabilistic Neural Networks, Discriminant Analysis, and Logistic Regression. Natural Resources Research, 12(4): 241–255. https://doi.org/10.1023/b:narr.0000007804.27450.e8 |
Huang, X., Zheng, Y., Yu, P. P., et al., 2021. Mass Transfer during Alteration and Ore-Forming Geological Process of the Pangxidong-Jinshan Ag-Au Ore-Field in the Yunkai Area. Geochimica, 50(4): 365–380 (in Chinese with English Abstract) |
Jiao, Q. Q., Wang, L. X., Deng, T., et al., 2017. Origin of the Ore-Forming Fluids and Metals of the Hetai Goldfield in Guangdong Province of South China: Constraints from C-H-O-S-Pb-He-Ar Isotopes. Ore Geology Reviews, 88: 674–689. https://doi.org/10.1016/j.oregeorev.2017.04.005 |
Karaman, M., Kumral, M., Yildirim, D. K., et al., 2021. Delineation of the Porphyry-Skarn Mineralized Zones (NW Turkey) Using Concentration-Volume Fractal Model. Geochemistry, 81(4): 125802. https://doi.org/10.1016/j.chemer.2021.125802 |
Kianoush, P., Mohammadi, G., Hosseini, S. A., et al., 2022. Compressional and Shear Interval Velocity Modeling to Determine Formation Pressures in an Oilfield of SW Iran. Journal of Mining and Environment, 13(3): 851–871. https://doi.org/10.2139/ssrn.4316010 |
Kreuzer, O. P., Yousefi, M., Nykänen, V., 2020. Introduction to the Special Issue on Spatial Modelling and Analysis of Ore-Forming Processes in Mineral Exploration Targeting. Ore Geology Reviews, 119: 103391. https://doi.org/10.1016/j.oregeorev.2020.103391 |
Lawley, C. J. M., Tschirhart, V., Smith, J. W., et al., 2021. Prospectivity Modelling of Canadian Magmatic Ni (±Cu±Co±PGE) Sulphide Mineral Systems. Ore Geology Reviews, 132: 103985. https://doi.org/10.1016/j.oregeorev.2021.103985 |
Lee, C., Oh, H. J., Cho, S. J., et al., 2019. Three-Dimensional Prospectivity Mapping of Skarn-Type Mineralization in the Southern Taebaek Area, Korea. Geosciences Journal, 23(2): 327–339. https://doi.org/10.1007/s12303-018-0035-y |
Li, H., Li, X. H., Yuan, F., et al., 2022. Knowledge-Driven Based Three-Dimensional Prospectivity Modeling of Fe-Cu Skarn Deposits: A Case Study of the Fanchang Volcanic Basin, Anhui Province, Eastern China. Ore Geology Reviews, 149: 105065. https://doi.org/10.1016/j.oregeorev.2022.105065 |
Li, N., Song, X. L., Li, C. B., et al., 2019. 3D Geological Modeling for Mineral System Approach to GIS-Based Prospectivity Analysis: Case Study of an MVT Pb-Zn Deposit. Natural Resources Research, 28(3): 995–1019. https://doi.org/10.1007/s11053-018-9429-9 |
Li, R. X., Wang, G. W., Carranza, E. J. M., 2016. GeoCube: A 3D Mineral Resources Quantitative Prediction and Assessment System. Computers & Geosciences, 89: 161–173. https://doi.org/10.1016/j.cageo.2016.01.012 |
Li, S., Chen, J. P., Xiang, J., 2020. Applications of Deep Convolutional Neural Networks in Prospecting Prediction Based on Two-Dimensional Geological Big Data. Neural Computing and Applications, 32(7): 2037–2053. https://doi.org/10.1007/s00521-019-04341-3 |
Li, X. H., Yuan, F., Zhang, M. M., et al., 2015. Three-Dimensional Mineral Prospectivity Modeling for Targeting of Concealed Mineralization within the Zhonggu Iron Orefield, Ningwu Basin, China. Ore Geology Reviews, 71: 633–654. https://doi.org/10.1016/j.oregeorev.2015.06.001 |
Li, X. H., Yuan, F., Zhang, M. M., et al., 2019. 3D Computational Simulation-Based Mineral Prospectivity Modeling for Exploration for Concealed Fe-Cu Skarn-Type Mineralization within the Yueshan Orefield, Anqing District, Anhui Province, China. Ore Geology Reviews, 105: 1–17. https://doi.org/10.1016/j.oregeorev.2018.12.003 |
Li, Z. X., Li, X. H., Zhou, H. W., et al., 2002. Grenvillian Continental Collision in South China: New SHRIMP U-Pb Zircon Results and Implications for the Configuration of Rodinia. Geology, 30(2): 163–166 (in Chinese with English Abstract) |
Lin, Z. W., Zhou, Y. Z., Qin, Y., et al., 2017. Ore-Controlling Structure Analysis of Pangxidong-Jinshan Silver-Gold Orefield, Southern Qin-Hang Belt: Implications for Further Exploration. Mineral Deposits, 36(4): 866–878 (in Chinese with English Abstract) |
Lindsay, M. D., Jessell, M. W., Ailleres, L., et al., 2013. Geodiversity: Exploration of 3D Geological Model Space. Tectonophysics, 594: 27–37. https://doi.org/10.1016/j.tecto.2013.03.013 |
Liu, T. F., 1990. Geological Characteristics and Concentration Regularity of Jinshan Au-Ag Deposit, Guangxi Autonomous Region, Guangxi. Gold, 11(8): 1–7 (in Chinese with English Abstract) |
Liu, Y., Zhou, K. F., Zhang, N. N., et al., 2018. Maximum Entropy Modeling for Orogenic Gold Prospectivity Mapping in the Tangbale-Hatu Belt, Western Junggar, China. Ore Geology Reviews, 100: 133–147. https://doi.org/10.1016/j.oregeorev.2017.04.029 |
Lü, W. C., Liu, X. Y., Chen, Q., et al., 2014. Geochemical Characteristics of REE of Pangxidong Electrum Deposit of Guangdong Province. Metal Mine, 3: 108–110 (in Chinese with English Abstract) |
Mahdizadeh, M., Afzal, P., Eftekhari, M., et al., 2022. Geomechanical Zonation Using Multivariate Fractal Modeling in Chadormalu Iron Mine, Central Iran. Bulletin of Engineering Geology and the Environment, 81(1): 59. https://doi.org/10.1007/s10064-021-02558-y |
Mallet, J. L., 1992. Discrete Smooth Interpolation in Geometric Modelling. Computer-Aided Design, 24(4): 178–191. https://doi.org/10.1016/0010-4485(92)90054-e |
Mao, J. W., Cheng, Y. B., Chen, M. H., et al., 2013. Major Types and Time-Space Distribution of Mesozoic Ore Deposits in South China and Their Geodynamic Settings. Mineralium Deposita, 48(3): 267–294. https://doi.org/10.1007/s00126-012-0446-z |
Mao, X. C., Ren, J., Liu, Z. K., et al., 2019. Three-Dimensional Prospectivity Modeling of the Jiaojia-Type Gold Deposit, Jiaodong Peninsula, Eastern China: A Case Study of the Dayingezhuang Deposit. Journal of Geochemical Exploration, 203: 27–44. https://doi.org/10.1016/j.gexplo.2019.04.002 |
McMillan, M., Haber, E., Peters, B., et al., 2021. Mineral Prospectivity Mapping Using a VNet Convolutional Neural Network. The Leading Edge, 40(2): 99–105 |
Mirzaie, M., Afzal, P., Adib, A., et al., 2020. Detection of Zones Based on Ore and Gangue Using Fractal and Multivariate Analysis in Chah Gaz Iron Ore Deposit, Central Iran. Journal of Mining and Environment, 11(2): 453–466 |
Mohammadpour, M., Bahroudi, A., Abedi, M., 2021. Three Dimensional Mineral Prospectivity Modeling by Evidential Belief Functions, a Case Study from Kahang Porphyry Cu Deposit. Journal of African Earth Sciences, 174: 104098. https://doi.org/10.1016/j.jafrearsci.2020.104098 |
Nielsen, S., Partington, G., Franey, D., et al., 2019. 3D Mineral Potential Modelling of Gold Distribution at the Tampia Gold Deposit. Ore Geology Reviews, 109: 276–289 |
Nykänen, V., Karinen, T., Niiranen, T., et al., 2011. Modelling the Gold Potential of Central Lapland, Northern Finland. Geological Survey of Finland, Special Paper, 49: 71–82 |
Nykänen, V., Lahti, I., Niiranen, T., et al., 2015. 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 Geology Reviews, 71: 853–860. https://doi.org/10.1016/j.oregeorev.2014.09.007 |
Olierook, H. K., Scalzo, R., Kohn, D., et al., 2021. Bayesian Geological and Geophysical Data Fusion for the Construction and Uncertainty Quantification of 3D Geological Models. Geoscience Frontiers, 12: 479–493 |
Paganelli, F., Richards, J. P., Grunsky, E. C., 2002. Integration of Structural, Gravity, and Magnetic Data Using the Weights of Evidence Method as a Tool for Kimberlite Exploration in the Buffalo Head Hills, Northern Central Alberta, Canada. Natural Resources Research, 11(3): 219–236. https://doi.org/10.1023/a:1019936006314 |
Pan, G. C., Harris, D. P., 1992. Estimating a Favorability Equation for the Integration of Geodata and Selection of Mineral Exploration Targets. Mathematical Geology, 24(2): 177–202. https://doi.org/10.1007/bf00897031 |
Pan, J. Y., Zhang, Q., Zhang, B. G., et al., 1996. Metallogenic Regularity of Gold and Silver Deposits in Western Guangdong. Mineral Deposits, 15(3): 66–75 (in Chinese with English Abstract) |
Parsa, M., Carranza, E. J. M., Ahmadi, B., 2022. Deep GMDH Neural Networks for Predictive Mapping of Mineral Prospectivity in Terrains Hosting Few but Large Mineral Deposits. Natural Resources Research, 31(1): 37–50. https://doi.org/10.1007/s11053-021-09984-5 |
Payne, C. E., Cunningham, F., Peters, K. J., et al., 2015. From 2D to 3D: Prospectivity Modelling in the Taupo Volcanic Zone, New Zealand. Ore Geology Reviews, 71: 558–577. https://doi.org/10.1016/j.oregeorev.2014.11.013 |
Perrouty, S., Lindsay, M. D., Jessell, M. W., et al., 2014. 3D Modeling of the Ashanti Belt, Southwest Ghana: Evidence for a Litho-Stratigraphic Control on Gold Occurrences within the Birimian Sefwi Group. Ore Geology Reviews, 63: 252–264. https://doi.org/10.1016/j.oregeorev.2014.05.011 |
Pirajno, F., Bagas, L., 2002. Gold and Silver Metallogeny of the South China Fold Belt: A Consequence of Multiple Mineralizing Events? Ore Geology Reviews, 20(3/4): 109–126. https://doi.org/10.1016/s0169-1368(02)00067-7 |
Porwal, A. K., Kreuzer, O. P., 2010. Introduction to the Special Issue: Mineral Prospectivity Analysis and Quantitative Resource Estimation. Ore Geology Reviews, 38(3): 121–127. https://doi.org/10.1016/j.oregeorev.2010.06.002 |
Porwal, A., Carranza, E. J. M., Hale, M., 2003. Knowledge-Driven and Data-Driven Fuzzy Models for Predictive Mineral Potential Mapping. Natural Resources Research, 12(1): 1–25. https://doi.org/10.1023/a:1022693220894 |
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. https://doi.org/10.1007/s11053-006-9012-7 |
Qian, J. P., Xie, B. W., Chen, H. Y., et al., 2011. Analysis of Ore-Controlling Structure and Prospecting of Tectono-Geochemistry in Jinshan Au-Ag Mining Area, Guangxi. Geoscience, 25(3): 531–544 (in Chinese with English Abstract) |
Raines, G. L., 1999. Evaluation of Weights of Evidence to Predict Epithermal-Gold Deposits in the Great Basin of the Western United States. Natural Resources Research, 8(4): 257–276. https://doi.org/10.1023/a:1021602316101 |
Schaeben, H., 2014. A Mathematical View of Weights-of-Evidence, Conditional Independence, and Logistic Regression in Terms of Markov Random Fields. Mathematical Geosciences, 46(6): 691–709. https://doi.org/10.1007/s11004-013-9513-y |
Singer, D. A., Kouda, R., 1996. Application of a Feedforward Neural Network in the Search for Kuroko Deposits in the Hokuroku District, Japan. Mathematical Geology, 28(8): 1017–1023. https://doi.org/10.1007/bf02068587 |
Souza Filho, C. R., Sawatzky, D. L., Raines, G. L., et al., 2017. Spatial Data Modeler 5 (ArcSDM 5): ArcGIS Geoprocessing Tools for Spatial Data Modelling Using Weights of Evidence, Logistic Regression, Fuzzy Logic and Neural Networks, |
Sprague, K., de Kemp, E., Wong, W., et al., 2006. Spatial Targeting Using Queries in a 3-D GIS Environment with Application to Mineral Exploration. Computers & Geosciences, 32(3): 396–418. https://doi.org/10.1016/j.cageo.2005.07.008 |
Sun, H. S., Cao, X. Z., Zhang, K., 2005. Characteristics of Ore-Controlling Faults and Rules of Ore-Controlling Faults in Pangxidong Ag(Au) Deposit, Northwestern Guangdong. Conributions to Geology and Mineral Resources Research, 20(3): 161–165 (in Chinese with English Abstract) |
Sun, T., Wu, K. X., Chen, L. K., et al., 2017. Joint Application of Fractal Analysis and Weights-of-Evidence Method for Revealing the Geological Controls on Regional-Scale Tungsten Mineralization in Southern Jiangxi Province, China. Minerals, 7: 243. https://doi.org/10.3390/min7120243 |
Taylor, B. E., de Kemp, E., Grunsky, E., et al., 2014. Three-Dimensional Visualization of the Archean Horne and Quemont Au-Bearing Volcanogenic Massive Sulfide Hydrothermal Systems, Blake River Group, Quebec. Economic Geology, 109(1): 183–203. https://doi.org/10.2113/econgeo.109.1.183 |
The Sixth Geological Team of Guangxi (TSGTG), 1984. Topographic and Geological Map of Jinshan Ag-Au Mining Area in Bobai County, Guangxi. Guangxi Zhuang Autonomous Region, Guigang |
Thiart, C., Bonham-Carter, G. F., Agterberg, F. P., 2003. Conditional Independence in Weights-of-Rvidence: Application of an Improved Test. Proceedings of the 2003 Annual IAMG conference, Portsmouth, England, CD-ROM |
Thiart, C., Bonham-Carter, G. F., Agterberg, F. P., et al., 2005. An Application of the New Omnibus Test for Conditional Independence in Weights of Evidence Modelling, In: Harris, J. R., ed., GIS Applications in the Earth Sciences. Geological Association of Canada Special Publication, Toronto |
Wang, G. W., Carranza, E. J. M., Zuo, R. G., et al., 2012. Mapping of District-Scale Potential Targets Using Fractal Models. Journal of Geochemical Exploration, 122: 34–46. https://doi.org/10.1016/j.gexplo.2012.06.013 |
Wang, G. W., Li, R. X., Carranza, E. J. M., et al., 2015. 3D Geological Modeling for Prediction of Subsurface Mo Targets in the Luanchuan District, China. Ore Geology Reviews, 71: 592–610. https://doi.org/10.1016/j.oregeorev.2015.03.002 |
Wang, H. N., Yang, J. W., Chen, H. Q., 1992. Geochemical Studies of the Pangxidong Silver Deposit in Guangdong Province. Mineral Deposits, 11(2): 179–187 (in Chinese with English Abstract) |
Wang, W. L., Zhao, J., Cheng, Q. M., et al., 2012. Tectonic-Geochemical Exploration Modeling for Characterizing Geo-Anomalies in Southeastern Yunnan District, China. Journal of Geochemical Exploration, 122: 71–80. https://doi.org/10.1016/j.gexplo.2012.06.017 |
Wang, Y., Chen, J. P., Jia, D. H., 2020. Three-Dimensional Mineral Potential Mapping for Reducing Multiplicity and Uncertainty: Kaerqueka Polymetallic Deposit, QingHai Province, China. Natural Resources Research, 29(1): 365–393. https://doi.org/10.1007/s11053-019-09539-9 |
Wang, Z. W., Zhou, Y. Z., 2002a. Geochemistry Character of Pangxidong-Jinshan Silver-Gold Deposit and Its Mineral Resource Evaluation Yunkai Area, South China, Beijing (in Chinese with English Abstract) |
Wang, Z. W., Zhou, Y. Z., 2002b. Geological Characteristics and Genesis of the Pangxidong-Jinshan Ag-Au Deopsit in Yunkai Terrain, South China. Geotectonic et Metallogenia, 26(2): 193–198 (in Chinese with English Abstract) |
Wang, Z. Y., Wang, J. C., Yin, Y. Q., et al., 1995. Metallogenic Law and Model of Au-Ag Deposits in Southeastern Guangxi. Mineral Resources and Geolgy, 9(4): 257–262 (in Chinese with English Abstract) |
Xia, J. L., Huang, G. C., Ding, L. X., et al., 2018. Zircon U-Pb Dating, Petrogenesis and Tectonic Background of the Early Paleozoic Nintan Gneisis Granitic Pluton, in the Yunkai Terran. Earth Science, 43(7): 2276–2293 (in Chinese with English Abstract) |
Xiang, J., Xiao, K. Y., Carranza, E. J. M., et al., 2020. 3D Mineral Prospectivity Mapping with Random Forests: A Case Study of Tongling, Anhui, China. Natural Resources Research, 29(1): 395–414. https://doi.org/10.1007/s11053-019-09578-2 |
Xiao, F., Chen, J. G., Agterberg, F., et al., 2014. Element Behavior Analysis and Its Implications for Geochemical Anomaly Identification: A Case Study for Porphyry Cu-Mo Deposits in Eastern Tianshan, China. Journal of Geochemical Exploration, 145: 1–11. https://doi.org/10.1016/j.gexplo.2014.04.008 |
Xiao, F., Chen, J. G., Hou, W. S., et al., 2017. Identification and Extraction of Ag-Au Mineralization Associated Geochemical Anomaly in Pangxitong District, Southern Part of the Qinzhou-Hangzhou Metallogenic Belt, China. Acta Petrologica Sinica, 33(3): 779–790 (in Chinese with English Abstract) |
Xiao, F., Chen, J. G., Hou, W. S., et al., 2018. A Spatially Weighted Singularity Mapping Method Applied to Identify Epithermal Ag and Pb-Zn Polymetallic Mineralization Associated Geochemical Anomaly in Northwest Zhejiang, China. Journal of Geochemical Exploration, 189: 122–137. https://doi.org/10.1016/j.gexplo.2017.03.017 |
Xiao, F., Chen, J. G., Zhang, Z. Y., et al., 2012. Singularity Mapping and Spatially Weighted Principal Component Analysis to Identify Geochemical Anomalies Associated with Ag and Pb-Zn Polymetallic Mineralization in Northwest Zhejiang, China. Journal of Geochemical Exploration, 122: 90–100. https://doi.org/10.1016/j.gexplo.2012.04.010 |
Xiao, F., Chen, W. L., Wang, J., et al., 2022. A Hybrid Logistic Regression: Gene Expression Programming Model and Its Application to Mineral Prospectivity Mapping. Natural Resources Research, 31(4): 2041–2064. https://doi.org/10.1007/s11053-021-09918-1 |
Xiao, F., Wang, K. Q., Hou, W. S., et al., 2020a. Identifying Geochemical Anomaly through Spatially Anisotropic Singularity Mapping: A Case Study from Silver-Gold Deposit in Pangxidong District, SE China. Journal of Geochemical Exploration, 210: 106453. https://doi.org/10.1016/j.gexplo.2019.106453 |
Xiao, F., Wang, K. Q., Hou, W. S., et al., 2020b. Prospectivity Mapping for Porphyry Cu-Mo Mineralization in the Eastern Tianshan, Xinjiang, Northwestern China. Natural Resources Research, 29(1): 89–113. https://doi.org/10.1007/s11053-019-09486-5 |
Xiao, F., Wang, Y., Zhou, Y. Z., 2020c. Determining Thresholds of Arsenic and Mercury in Stream Sediment for Mapping Natural Toxic Element Anomaly Using Data-Driven Models: A Comparative Study on Probability Plots and Fractal Methods. Arabian Journal of Geosciences, 13(18): 915. https://doi.org/10.1007/s12517-020-05917-3 |
Xiao, K. Y., Li, N., Porwal, A., et al., 2015. GIS-Based 3D Prospectivity Mapping: A Case Study of Jiama Copper-Polymetallic Deposit in Tibet, China. Ore Geology Reviews, 71: 611–632. https://doi.org/10.1016/j.oregeorev.2015.03.001 |
Xu, D. M., Lin, Z. Y., Long, W. G., et al., 2012. Research History and Current Situation of Qinzhou-Hangzhou Metallogenic Belt, South China. Geology and Mineral Resources of South China, 28(4): 277–289 (in Chinese with English Abstract) |
Yang, M. G., Mei, Y. W., 1997. Charateristics of Geology and Metallization in the Qinzhou-Hangzhou Paleoplate Juncture. Geology and Mineral Resources of South China, 3: 52–59 (in Chinese with English Abstract) |
Yin, B. J., Zuo, R. G., Sun, S. Q., 2023. Mineral Prospectivity Mapping Using Deep Self-Attention Model. Natural Resources Research, 32(1): 37–56. https://doi.org/10.1007/s11053-022-10 142-8 doi: 10.1007/s11053-022-10142-8 |
Yousefi, M., Carranza, E. J. M., 2015a. Fuzzification of Continuous-Value Spatial Evidence for Mineral Prospectivity Mapping. Computers & Geosciences, 74: 97–109. https://doi.org/10.1016/j.cageo.2014.10.014 |
Yousefi, M., Carranza, E. J. M., 2015b. Prediction-Area (P-A) Plot and C-A Fractal Analysis to Classify and Evaluate Evidential Maps for Mineral Prospectivity Modeling. Computers & Geosciences, 79: 69–81. https://doi.org/10.1016/j.cageo.2015.03.007 |
Yu, X. T., Xiao, F., Zhou, Y. Z., et al., 2019. Application of Hierarchical Clustering, Singularity Mapping, and Kohonen Neural Network to Identify Ag-Au-Pb-Zn Polymetallic Mineralization Associated Geochemical Anomaly in Pangxidong District. Journal of Geochemical Exploration, 203: 87–95 |
Yu, Z. B., Liu, B. L., Xie, M. A., et al., 2022.3D Mineral Prospectivity Mapping of Zaozigou Gold Deposit, West Qinling, China: Deep Learning-Based Mineral Prediction. Minerals, 12(11): 1382. https://doi.org/10.3390/min12111382 |
Yuan, F., Li, X. H., Zhang, M. M., et al., 2014. Three-Dimensional Weights of Evidence-Based Prospectivity Modeling: A Case Study of the Baixiangshan Mining Area, Ningwu Basin, Middle and Lower Yangtze Metallogenic Belt, China. Journal of Geochemical Exploration, 145: 82–97. https://doi.org/10.1016/j.gexplo.2014.05.012 |
Zeng, C. Y., Ding, R. X., Li, H. Z., et al., 2015. Analysis of X-Ray Fluorescence Spectroscopy and Plasma Mass Spectrometry of Pangxidong Composite Granitoid Pluton and Its Implications for Magmatic Differentiation. Spectroscopy and Spectral Analysis, 35(11): 3187–3191 (in Chinese with English Abstract) |
Zhang, D. J., Agterberg, F., Cheng, Q. M., et al., 2014. A Comparison of Modified Fuzzy Weights of Evidence, Fuzzy Weights of Evidence, and Logistic Regression for Mapping Mineral Prospectivity. Mathematical Geosciences, 46(7): 869–885. https://doi.org/10.1007/s11004-013-9496-8 |
Zhang, K. J., Cai, J. X., 2009. NE-SW-Trending Hepu-Hetai Dextral Shear Zone in Southern China: Penetration of the Yunkai Promontory of South China into Indochina. Journal of Structural Geology, 31(7): 737–748. https://doi.org/10.1016/j.jsg.2009.04.012 |
Zhang, Q. P., Chen, J. P., Xu, H., et al., 2022. Three-Dimensional Mineral Prospectivity Mapping by XGBoost Modeling: A Case Study of the Lannigou Gold Deposit, China. Natural Resources Research, 31(3): 1135–1156. https://doi.org/10.1007/s11053-022-10054-7 |
Zhang, S., Carranza, E. J. M., Wei, H. T., et al., 2021. Data-Driven Mineral Prospectivity Mapping by Joint Application of Unsupervised Convolutional Auto-Encoder Network and Supervised Convolutional Neural Network. Natural Resources Research, 30(2): 1011–1031. https://doi.org/10.1007/s11053-020-09789-y |
Zhang, Z. J., Zuo, R. G., Xiong, Y. H., 2016. A Comparative Study of Fuzzy Weights of Evidence and Random Forests for Mapping Mineral Prospectivity for Skarn-Type Fe Deposits in the Southwestern Fujian Metallogenic Belt, China. Science China Earth Sciences, 59(3): 556–572. https://doi.org/10.1007/s11430-015-5178-3 |
Zheng, W., Mao, J. W., Pirajno, F., et al., 2015. Geochronology and Geochemistry of the Shilu Cu-Mo Deposit in the Yunkai Area, Guangdong Province, South China and Its Implication. Ore Geology Reviews, 67: 382–398. https://doi.org/10.1016/j.oregeorev.2014.12.009 |
Zheng, Y., Zhou, Y. Z., Wang, Y. J., et al., 2016. A Fluid Inclusion Study of the Hetai Goldfield in the Qinzhou Bay-Hangzhou Bay Metallogenic Belt, South China. Ore Geology Reviews, 73: 346–353. https://doi.org/10.1016/j.oregeorev.2014.09.008 |
Zhou, M. F., Yan, D. P., Kennedy, A. K., et al., 2002. SHRIMP U-Pb Zircon Geochronological and Geochemical Evidence for Neoproterozoic Arc-Magmatism along the Western Margin of the Yangtze Block, South China. Earth and Planetary Science Letters, 196(1/2): 51–67. https://doi.org/10.1016/s0012-821x(01)00595-7 |
Zhou, Y. Z., Li, X. Y., Zheng, Y., et al., 2017. Geological Settings and Metallogenesis of Qinzhou Bay-Hangzhou Bay Orogenic Juncture Belt, South China. Acta Petrologica Sinica, 33(3): 667–681 (in Chinese with English Abstract) |
Zhou, Y. Z., Zheng, Y., Zeng, C. Y., et al., 2015. On the Understanding of Qinzhou Bay-Hangzhou Bay Metallogenic Belt, South China. Earth Science Frontiers, 22(2): 1–6 (in Chinese with English Abstract) |
Zuo, R. G., Carranza, E. J. M., 2011. Support Vector Machine: A Tool for Mapping Mineral Prospectivity. Computers & Geosciences, 37(12): 1967–1975. https://doi.org/10.1016/j.cageo.2010.09.014 |
Zuo, R. G., Cheng, Q. M., Agterberg, F. P., et al., 2009. Application of Singularity Mapping Technique to Identify Local Anomalies Using Stream Sediment Geochemical Data, a Case Study from Gangdese, Tibet, Western China. Journal of Geochemical Exploration, 101(3): 225–235. https://doi.org/10.1016/j.gexplo.2008.08.003 |
Zuo, R. G., Luo, Z. J., Xiong, Y. H., et al., 2022. A Geologically Constrained Variational Autoencoder for Mineral Prospectivity Mapping. Natural Resources Research, 31(3): 1121–1133. https://doi.org/10.1007/s11053-022-10050-x |
Zuo, R. G., Xu, Y., 2023. Graph Deep Learning Model for Mapping Mineral Prospectivity. Mathematical Geosciences, 55(1): 1–21. https://doi.org/10.1007/s11004-022-10015-z |