Application of Remote Sensing and GIS for Geological Investigation and Groundwater Potential Zone Identification, Southeastern Ethiopian Plateau, Bale Mountains and the Surrounding Areas
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Date
2005-07
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Addis Ababa University
Abstract
The application of remote sensing and GIS has found to be a quick and inexpensive technique in
order to obtain the desired output efficiently. For the present study an attempt was made to map
dykes, lithology and other thematic maps such as of drainage density, slope, elevation, lineament,
rainfall, landcover and burrowing of rodents and then to integrate them in a GIS environment to
get information about the occurrence of groundwater and used to select promising areas for
further groundwater exploration.
The present study was conducted on southeastern part of Ethiopia plateau, the Bale Mountains
and the surrounding areas. Satellite image of Landsat ETM+ of all bands except the thermal
bands were utilized for lithologic and geologic structures mapping. Topographic map at the scale
of 1 :50,000 were used to generate elevation contour at the interval of 20m. Slope map were
derived from TIN (Triangulated Irregular Network), which is derived from elevation contour
map. Spatial distribution of drainage density was derived by using three softwares AutoCAD map
2000 engineering software, Arcview3 .2 and MapInfo professional 6.0. The burrowing of Rodents
were mapped from field Knowledge and using 742(RGB) that shows areas of rodent burrowing
activities. Secondary data of landcover, soi l were also utilized. Groundwater potentiality in the
area has been assessed through the integration of the different thematic layers that contributes for
the natural recharging of aquifer. The predicted groundwater potential zones were divided into 5
classes from very good up to poor.
Color composite, ratio and PCA (Principal Component analysis) were made to interpret the
lithology of the area. Due to vegetation cover and similarities of reflectance of different rock
units it was difficult to separate them. The field knowledge and some petrographic analysis
support the identification of the lithology.
Key words: dykes, lithology, groundwater potential zone prediction, Remote Sensing and GIS
Description
Keywords
dykes, lithology, groundwater potential zone prediction, Remote Sensing, GIS