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 property’s value such as crime rates, environmental hazards, and the condition of surrounding neighborhoods and properties. ESRI’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:
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:
- drilling trial boreholes,
- monitoring groundwater heads, flows and chemical characteristics for a number of years,
- carrying out a thorough analysis of all the data and
- 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 earth’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).
CHAPTER THREE
Description of the study 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 of West Africa. They are overlain uncornformably by the Maastrichtian Rima Group, 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 beds are free from faulting, with dips between 2.5 to 3.8 meters per kilometre in a direction 60° west of north. Around Sokoto the direction of dip is about 18°NW. 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 and Methods
Image Acquisition and Preprocessing
Four Landsat-8 OLI/TIR scenes (path 190, row 051), (path 190, row 052), (path 191, 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 – 0.453µm), Band 2 (blue, 0.450 – 0.515µm), Band 3 (green, 0.525 – 0.600µm), Band 4 (red, 0.630 – 0.680µm), Band 5 (NIR, 0.845 – 0.885µm), Band 6 (SWIR, 1.560 – 1.660µm), Band 7 (SWIR, 2.100 –
CHAPTER FOUR
Result and Discussion
Multispectral images of Landsat-8 data were processed to interpret for geological studies 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 high reflectance within 0.63 – 0.69µm (band 4) and high absorption within 0.45 – 0.52µm (band 2). Clay and carbonate minerals have absorption features from 2.1 – 2.4µm (band 7) and reflectance from 1.55 – 1.75µm (band 6) in Landsat-8 data (Han et al., 2015). Minerals such as alunite, and clay minerals such as illite, kaolinite and montmorillonite have distinctive absorption features at 2.20µm and low absorption at 1.6µm, hence, band ratio of 6 and 7, and 7 and 5 were calculated to map clay deposits as dark blue in figure 4 and figure 5. Band 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 ratio 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.
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