Dickson E. Ngowi, Elisante E. Mshiu, Michael Msabi
{"title":"描绘金矿潜在区域的矿产远景建模:坦桑尼亚西南部卢帕金矿的案例研究","authors":"Dickson E. Ngowi, Elisante E. Mshiu, Michael Msabi","doi":"10.1080/25726838.2023.2259737","DOIUrl":null,"url":null,"abstract":"ABSTRACTThis study used the weight of evidence model to delineate prospective areas for gold deposits in the Lupa Goldfield. The method establishes a spatial relationship between known mineral deposits and evidential maps to create a mineral prospectivity map. Four evidential maps derived from geochemical, geological, geophysical, and topographical Digital Elevation Model (DEM) datasets were analysed and integrated to create a mineral prospectivity map. Results have revealed five classes ranked from the highest, high, medium, low, and lowest favourability patterns with probability values of 0.051, 0.0426, 0.0225, 0.0172, and 0.0091, respectively. The highest favourable areas have the best gold potentials based on the presence of predictor patterns from all four evidential maps. The posterior probability map revealed good prediction, existing gold deposits, such as Saza Mine and Shanta Gold Mine, were mapped. Results have shown that the weight of evidence model was successful and can be applied in mineral exploration targeting.KEYWORDS: Mineral prospectivity mapping; weight of evidence model; geographical information system (GIS); Lupa Goldfieldmineral exploration AcknowledgementThe authors would like to thank the Geological Survey of Tanzania for providing geological, geochemical, and geophysical data which were used in this study.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by Ministry of Minerals, Tanzania.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mineral prospectivity modelling to delineate potential areas for gold deposits: a case study of Lupa Goldfield, South West Tanzania\",\"authors\":\"Dickson E. Ngowi, Elisante E. Mshiu, Michael Msabi\",\"doi\":\"10.1080/25726838.2023.2259737\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACTThis study used the weight of evidence model to delineate prospective areas for gold deposits in the Lupa Goldfield. The method establishes a spatial relationship between known mineral deposits and evidential maps to create a mineral prospectivity map. Four evidential maps derived from geochemical, geological, geophysical, and topographical Digital Elevation Model (DEM) datasets were analysed and integrated to create a mineral prospectivity map. Results have revealed five classes ranked from the highest, high, medium, low, and lowest favourability patterns with probability values of 0.051, 0.0426, 0.0225, 0.0172, and 0.0091, respectively. The highest favourable areas have the best gold potentials based on the presence of predictor patterns from all four evidential maps. The posterior probability map revealed good prediction, existing gold deposits, such as Saza Mine and Shanta Gold Mine, were mapped. Results have shown that the weight of evidence model was successful and can be applied in mineral exploration targeting.KEYWORDS: Mineral prospectivity mapping; weight of evidence model; geographical information system (GIS); Lupa Goldfieldmineral exploration AcknowledgementThe authors would like to thank the Geological Survey of Tanzania for providing geological, geochemical, and geophysical data which were used in this study.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by Ministry of Minerals, Tanzania.\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2023-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/25726838.2023.2259737\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/25726838.2023.2259737","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mineral prospectivity modelling to delineate potential areas for gold deposits: a case study of Lupa Goldfield, South West Tanzania
ABSTRACTThis study used the weight of evidence model to delineate prospective areas for gold deposits in the Lupa Goldfield. The method establishes a spatial relationship between known mineral deposits and evidential maps to create a mineral prospectivity map. Four evidential maps derived from geochemical, geological, geophysical, and topographical Digital Elevation Model (DEM) datasets were analysed and integrated to create a mineral prospectivity map. Results have revealed five classes ranked from the highest, high, medium, low, and lowest favourability patterns with probability values of 0.051, 0.0426, 0.0225, 0.0172, and 0.0091, respectively. The highest favourable areas have the best gold potentials based on the presence of predictor patterns from all four evidential maps. The posterior probability map revealed good prediction, existing gold deposits, such as Saza Mine and Shanta Gold Mine, were mapped. Results have shown that the weight of evidence model was successful and can be applied in mineral exploration targeting.KEYWORDS: Mineral prospectivity mapping; weight of evidence model; geographical information system (GIS); Lupa Goldfieldmineral exploration AcknowledgementThe authors would like to thank the Geological Survey of Tanzania for providing geological, geochemical, and geophysical data which were used in this study.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by Ministry of Minerals, Tanzania.