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Geology Project Topics

Structural Interpretation and Mineral Potential Using Remote Sensing Data and GIS Tool

Structural Interpretation and Mineral Potential Using Remote Sensing Data and GIS Tool

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Structural Interpretation and Mineral Potential Using Remote Sensing Data and GIS Tool

Chapter One

Objectives and Aims of the study

The main thrust of his paper is to investigate the Structural interpretation and mineral potential using remote sensing data and GIS tools.

CHAPTER TWO

LITERATURE REVIEW

Concept of Geographical Information System (GIS)

Geographical Information System (GIS) is used to arrange the computer hardware, software, and geographic data. It helps the people interact, analyze, identify relationship and find the solutions to the problems. The system is designed to capture, store, update, manipulate, analyze, and display studied data and used to perform analyses (ESRI, 2005). Since 1970s, GIS has been used to analyze various environments. But the extensive application of GIS to hydrologic and hydraulic modeling and flood mapping and management begin from early 1990s. (Maidment, 2000).

GIS has the ability to represent elevation in terms of topographic surfaces is central to geomorphological analyses and thus to the importance of representing topography using Digital Elevation Model (DEM). It is through the distribution of soil that the land surface changes over the long term and so the ability to link sediment transfer with DEM changes. (Schmidt, 2000)

ArcView GIS desktop software provided the tools of map features that will affect a propertyโ€™s value such as crime rates, environmental hazards, and the condition of surrounding neighborhoods and properties. ESRIโ€™s ArcGIS is a GIS which is working with maps and geographic information. ArcGIS software can be used for following functions: creating and using maps, compiling geographic data, analyzing mapped information, sharing and discovering geographic information, using maps and geographic information in a range of applications, and managing geographic information in database. (Wikipedia, ArcGIS, 2012). The ArcGIS provides tools for constructing maps and geographic information.

RELEVANCE OF GIS TOOL IN GROUNDWATER EXPLORATION.

Remote Sensing (RS) and Geographic Information Systems (GIS) as proved to be useful tools in groundwater exploration mapping in the following ways:

ย Increased accuracy and speed in exploration data analysis:

For simple groundwater exploration, aerial photographs and GIS/RS are used to map features likely to be high-yielding zones, and to identify favorable structures or deposits for groundwater accumulation.

Reduction in the cost of investigations and groundwater development

A groundwater investigation is costly and time consuming as it involves:

  1. drilling trial boreholes,
  2. monitoring groundwater heads, flows and chemical characteristics for a number of years,
  3. carrying out a thorough analysis of all the data and
  4. developing a simulation model.

Nevertheless, with the advent of GIS/RS has brought about reduction in the cost of investigations, time used for investigations through the use of high resolution satellite imagery of the earthโ€™s surfaces, computer based computations and analysis of such images, through Visual interpretation with image processing capabilities of GIS.

Integration of RS, GIS and modeling techniques

Modern RS/GIS software enables digital RS data to be merged with other data. Digitized maps, e.g. road networks, or geological maps, can be combined with the images, making the interpretation easier. An existing thematic map can be visualized together with the information from a satellite image. In most studies the conceptual models essential as the backbone of the investigations, need to be quantified. It is not sufficient to know where water is stored; amounts, quality and fluxes also need to be known. Here again the techniques combining RS, GIS and simple models can be used to estimate fluxes. Mapping units can be based on geomorphology, geology, soils and vegetation. Some of the components of the hydrological cycle, such as actual evapotranspiration and groundwater recharge potential, may be estimated for different mapping units using GIS. Irrigated area and the associated consumption of surface water and groundwater can be estimated using RS/GIS techniques (Hoffmann and Sanders 2007).

 

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CHAPTER THREE

Description of the studyย area

Sokoto state is located in the northwestern part of Nigeria as shown in Figure 1. In Northwestern Nigeria, the sediments of the Iullemmeden Basin were deposited during three main phases: continental Mesozoic and Tertiary phases with an intervening marine Maastrichtian to Paleocene phase. Overlying the Precambrian basement conformably, the Illo and Gundumi Formations, made up of grits and clay from parts of the Continental Intercalier ofย Westย Africa.ย Theyย areย overlainย uncornformablyย byย theย Maastrichtianย Rimaย Group,ย consisting of musdstone and friable sandstones separated by a fossiliferous shaly formation (Odeyemi, 1981).

The geological structure of the Sokoto basin is without much complexity (Figure 2). The bedsย areย freeย fromย faulting,ย withย dipsย betweenย 2.5ย toย 3.8ย metersย perย kilometreย inย aย directionย 60ยฐ west of north. Around Sokoto the direction of dip is about 18ยฐNW. The sedimentary deposits lie on the crystalline Precambrian basement, consisting of gneisses, granite, phyllites and quartzites. The basement rocks outcrop in the eastern and southern sector of Sokoto state (Kogbe, 1999).

Materials andย Methods

ย Image Acquisition andย Preprocessing

Fourย Landsat-8ย OLI/TIRย scenesย (pathย 190,ย rowย 051),ย (pathย 190,ย rowย 052),ย (pathย 191,ย row

051) and (path 191, row 052) with 0% cloud cover were acquired for the year 2017 from the US Geological Survey. All four Level 1T standard terrain corrected images were processed using the Environment for Visualizing Images (ENVI) version 5.1 software and Environment Systems Research Institute (ESRI) ArcGIS version 10.1 software. The Landsat images were spectrally subset to contain OLI bands of Band 1 (coastal/aerosol, 0.433 โ€“ 0.453ยตm), Band 2 (blue, 0.450 โ€“ 0.515ยตm), Band 3 (green, 0.525 โ€“ 0.600ยตm), Band 4 (red, 0.630 โ€“ 0.680ยตm), Bandย 5ย (NIR,ย 0.845ย โ€“ย 0.885ยตm),ย Bandย 6ย (SWIR,ย 1.560ย โ€“ย 1.660ยตm),ย Bandย 7ย (SWIR,ย 2.100ย โ€“

CHAPTER FOUR

Result andย Discussion

Multispectral images of Landsat-8 data were processed to interpret for geological studiesย of the survey area. The image from colour composite technique showed a good result in terms of lithological mapping. Mapping iron oxides was carried out using bands 2 and 4 because iron oxide/hydroxide minerals such as hematite, jarosite and limonite, and sulphuric minerals have highย reflectanceย withinย 0.63ย โ€“ย 0.69ยตmย (bandย 4)ย andย highย absorptionย withinย 0.45ย โ€“ย 0.52ยตmย (band 2). Clay and carbonate minerals have absorption features from 2.1 โ€“ 2.4ยตm (band 7) and reflectanceย fromย 1.55ย โ€“ย 1.75ยตmย (bandย 6)ย inย Landsat-8ย dataย (Hanย etย al.,ย 2015).ย Mineralsย suchย as alunite, and clay minerals such as illite, kaolinite and montmorillonite have distinctive absorptionย featuresย atย 2.20ยตmย andย lowย absorptionย atย 1.6ยตm,ย hence,ย bandย ratioย ofย 6ย andย 7,ย andย 7 andย 5ย wereย calculatedย toย mapย clayย depositsย asย darkย blueย inย figureย 4ย andย figureย 5.ย Bandย ratios

CHAPTER FIVE

Conclusion

Remote sensing method employing techniques such as band combination, band ratio and supervised image classification can be an appropriate tool in mapping the geology and structure of a vast region of area especially when combined with field investigations. Based on the classification method used (maximum likelihood classification), the band ratioย  produced an accurate classification of the geology of Sokoto state. The number of observable spectral signatures on the band ratio image determined the number of training site classes used in the image classification in this study.

References

  • Ahmed, S. & Amin, B. 2014. Lithological mapping and hydrothermal alteration using Landsat 8 data: a case study in Ariab mining district, red sea hills, Sudan. Intl. J. Basic and Appld. Sci., 3(3), 199- 208
  • Crosta, A. & De Souza Filho, C. 2009. Mineral exploration with Landsat Thematic Mapper (TM) / Enhanced Thematic Mapper plus (ETM+): A review of fundamentals, characteristics, data processing, and case studies. Rev.in Econ. Geol., 16, 59-82
  • El Khidir, S. 2006. Remote Sensing and GIS Applications in Geological Mapping, prospecting for minerals deposits and groundwater Berber Sheet Area, Northern Sudan (Ph. D. Thesis). Al Neelain University, Khartoum, Sudan
  • Furon, R. 1963. Geology of Africa, Oliver and Boyd, England
  • Green,ย A.,ย Berman,ย M.,ย Switzer,ย P.,ย Craig,ย M.ย 1988.ย Aย transformationย forย orderingย multispectralย dataย in terms of image quality with implications for noise removal: IEEE Transactions on Geoscience and Remote Sensing, 26(1),ย 65-74
  • Gupta, R.P. 2003. Remote sensing geology, Springer, 2nd edition, Germany. 31-33
  • Han,ย T.ย &ย Nelson,ย J.ย 2015.ย Mappingย hydrothermallyย alteredย rocksย withย Landsat-8ย imagery:ย Aย caseย study in the KSM and Snow field zones, northwestern British Columbia. In: Geological Fieldwork 2014, British Columbia Ministry of Energy and Mines, British Columbia Geological Survey Paper Vol. 1, 103-112.
  • Khalid, A. & Abdel, H. 2014. The use of Landsat 8 OLI Image for the delineation of Gossanic Ridges in the Red Sea Hills of NE Sudan. American J. of Earth Sci., (1)3, 62-67
  • Kogbe, C. 1979. Geology of the south eastern sector of the Iullemmeden Basin. Bulletin of Geology Department. ABU Zaria, (2)1, 44-63.

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