CHAPTER 2: LITERATURE REVIEW
3.3 Groundwater Potential Mapping
3.3.1 Lineament Mapping from Remotely-Sensed Imagery (Landsat 8 OLI).
According to Meijerink et al. (2007), lineaments are simple mappable linear features on an image whose parts align in a rectilinear or slightly curvilinear relationship, and may differ from the patterns of adjacent features. In geology, these features are indicative of discontinuities and other zones of weakness in the ground. ERDAS Imagine software was used to manually trace lineaments from satellite images.
The mapping of structural lineaments in the entire study area was carried out from three scenes of LANDSAT 8 OLI (Operational Land Imager) images downloaded from the United States Geological Survey website. Landsat 8 OLI represents the new generation of the series of Landsat satellites, and it was launched in 2013. The satellite carries two push-broom sensors namely OLI (Operational Land Imager) and Thermal Infrared Sensor (TIRS).
The OLI is characterized by 9 spectral bands, 4 in the visible spectrum (0.43 – 0.67 mm), 1 band of the near infrared (0.85 – 0.88), 2 bands of the Shortwave Infrared (1.57 – 2.29 mm), and 1 band of cirrus (1.36 -1.38), all in 30 m spatial resolution. In addition, it has a high spatial resolution (i.e. 15 m) panchromatic band operating between 0.50 – 0.68 mm.
On the other hand, the TIRS consists of 2 bands with 100 m spatial resolution, operating between 10.60 -11.19 mm and 11.50 -12.51 mm respectively.
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The scenes of Landsat 8 used in the current study are for path 169 and 170, and rows 75 and 76 respectively. Each satellite image covers a wide area of about 170 KM (North to South) by 183 KM (East to West), with a spatial resolution of 30 meters for bands 1-7 and 9, and a resolution of 15 meters for band 8 (panchromatic). All the scenes are supplied as 11 separate GeoTiff files that are referenced to some location on earth. In the present study only bands 2, 3, 4, 5, and 8 were used, since band 1 and 9 are intended for aerosol studies and mapping of cirrus clouds (USGS, 2018).
A wide array of software packages was used for satellite image processing and subsequent map production operations. The software packages used include ERDAS Imagine 2014, Rockworks and ArcMap 10.2.1. A number of operations were carried out in successive steps using ERDAS Imagine to prepare the images for further processing operations. The following operations were carried out to prepare the imagery for lineament extraction:
3.3.2 Layer stacking and Principal Component Pansharpening
Landsat images are often available for download in a form of separate GeoTiff format files. GeoTiff is a standard format for georeferenced raster imagery, and each file represents a separate band of the electromagnetic spectrum. It is a common practice when using remotely-sensed imagery to select certain band combinations to meet the objectives of the study (USGS, 2017).
In this study, the main objective was to map geological lineaments from the Landsat imagery; therefore, bands 2,3,4,5 and 8 were chosen to achieve this objective. Previous studies have shown that these chosen band combinations are of potential significance to the extraction of geological lineaments, and lithological boundaries (Tessema et al., 2014;
Mwaniki et al., 2015).
As explained in section 3.3.1, bands 2, 3, 4 and 5 are characterized by a coarse spatial resolution of 30 m. It was therefore deemed necessary to resample the spatial resolution of the aforementioned bands to 15 m using the panchromatic band 8 to enhance the overall spatial resolution.
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Pan-sharpening tool of ERDAS Imagine 2014 was used to resample the four bands to a 15m spatial resolution in order to enhance the overall spatial resolution of the resultant composite image. The technique uses algorithms to inject the spatial detail of the panchromatic image to a multispectral image data (Jelenek et al., 2016). The resultant image has a spatial resolution of 15 m, with an enhanced visual quality of various features.
3.3.3 Mosaicking scenes of LANDSAT 8 OLI
The area of interest is approximately 16000 KM2 in size, a single Landsat scene is not large enough to portray the entire study area. Thus, the three partially processed images were merged together into a large cohesive image using ERDAS Imagine MosaicPro feature (figure A-3.1 in appendix A). Initially, the input images were color-balanced and their histograms adjusted in order to account for the color and contrast variations in the individual images. Equally important, the application of the aforementioned enhancements led to the production of a smoother image devoid of shadowy areas and bright patches. This operation led to the production of a large image portraying the entire study area along with parts of adjacent regions.
3.3.4 Creating a Subset image
Since a mosaicked image often represents a very large area, it was imperative to crop out the area of interest from it. Therefore, a subset image was created by cutting out an area of interest from the larger image area. An inquire tool in ERDAS Imagine was used to define the four geographic (i.e. x, y) coordinates making up the study area and cropping the defined area out of the large mosaicked composite image. Further enhancement operations were conducted on the subset image to improve the visibility of features of interest.
3.3.5 Image enhancement
In order to fulfill the objectives of the present study, only certain enhancement operations were applied to delineate the linear features. The image was initially contrast-stretched in order to linearly distribute the range of pixel values across the entire image. Contrast stretching improved the contrast of various features in the image, thus enabling easy feature extraction.
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A 3 × 3 edge-sharpening filter developed by ERDAS Imagine was applied to sharpen linear features in the image. This was followed by a non-directional edge enhancement filter to enhance the edges of all linear features regardless of their orientation. The resulting contrast-stretched image produced prominent linear features that were readily discernable.
3.3.6 Extraction of Lineaments from Landsat 8 OLI Imagery.
Lineaments were readily identified using the elements of photo interpretation such as color, tone, brightness, shape and contrast. The identified linear structures were finally digitized so that the image could be used in ArcGIS. In order to facilitate the digitization process, Easy-Trace tool option in ERDAS Imagine was used to manually trace the lineaments. The digitized lineaments were saved as a vector layer suitable for further processing using ArcMap 10.2.1 software. The lineaments were presented in a form of lineament map depicting their positions and azimuths of the geological lineaments.