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Modeling And Targeting Of Iron Resources With ETM+Data Interpretation, Alteration Mineral Mapping And Synthetic Analysis, Tonkolili Iron Field, Northern Sierra Leone

Posted on:2015-05-07Degree:MasterType:Thesis
Country:ChinaCandidate:Lamin Rahman MansarayFull Text:PDF
GTID:2180330422485760Subject:Cartography and geographic information system
Abstract/Summary:PDF Full Text Request
Iron resources have become very important in the global economy as they provide theinputs for the steel industry. The rapid industrial development of countries such as China,India, Brazil and other emerging economies in Asia and Africa have led to an increasingdemand for steel products. This has resulted to an increase in global iron ore exploration.Located in the world’s biggest underdeveloped iron ore province (West Africa), SierraLeone is correspondingly home to Africa’s largest iron ore (magnetite) deposit at present.The Tonkolili iron field in northern Sierra Leone forms the focus of this study. Theprimary iron mineralization here is magnetite. At the laterite and saprolite horizons havedeveloped a supergene iron-oxide enrichment blanket which covers almost the entirearea. Iron-oxides show diagnostic spectral features in the visible near infra-red (VNIR)portions of the electromagnetic spectrum which allows their remote identification.In this study, Landsat7Enhanced Thematic Mapper plus (ETM+) data are applied inmodeling and targeting iron resources in Tonkolili. The key objectives are the mapping ofbanded iron formation (BIFs), discrimination of alteration zones and targeting new areasfor BIFs and haematite prospects in the Tonkolili iron field. The methods employed inETM+image enhancement are the RGB, Crosta, band ratios and false color composites.The results show that for the mapping of magnetite-BIF, the ETM321and754in RGBcolor composites produced the most spectrally unique colors. The principal component-based Crosta technique enhanced areas with iron-oxides and hydroxyl-bearing minerals.The band ratio technique was only effective in enhancing areas with iron-oxide mineralsusing band ratios3/1and5/4. The modeled alteration anomalies were overlain with thesimplified geological map of Tonkolili and iron-oxide anomalies were found to followthe NE-SW trending of magnetic anomalies. This trend points to the fact that oxidative-weathering of the surface magnetite-BIFs have resulted to these iron-oxide anomalies inthe Tonkolili laterite duricrust and saprolite layers. In the final iron prospecting map, BIFboundaries were modified and five haematite prospects were inferred for field inspection.This study therefore concludes that, the application of remote sensing data such as ETM+could provide a fast and complementary tool in recognizing prospective areas of iron oremineralization found in Archaean Greenstone terranes such as Tonkolili in Sierra Leone.
Keywords/Search Tags:Tonkolili, iron resources, magnetite-BIF, alteration mapping, ETM+data
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