Mapping Geological Structures in Western Mutomo, Kitui County: A Remote Sensing Approach
Abstract
Lineament mapping constitute a very important process in the field of Geology and Earth
Sciences. Much of the exploration work, mapping and the exploitation of natural resources
including oil and gas, ground water and other hydrocarbons rely on a thorough understanding of
the geological structures within an area and the ability to interpret the result from analysis before
the exploitation process begins. This increases success rates while reducing cost and time
associated with geophysical surveys.
Structural analysis and mapping in this study was done using remote sensing and GIS
technologies to map linear geological features or structures using optical Landsat data. The
analysis was conducted on the multispectral Landsat ETM+ image captured in the year 2001
representing the Southern areas of the Kitui County on the eastern parts of Kenya. This was done
in combination with other datasets like DEM, topography dataset, geology and elevation data in
order to enhance the understanding and interpretation of structures.
Several filters were used to extract lineaments and structures applied on individual subsets of
panchromatic bands 4 and 7, the ratio of bands 3 and 4 and the composite image consisting of all
the 7 bands in the Landsat ETM+ image. Erdas Imagine® 2013 was the preferred software for
this study for conducting image analysis because of its robust filtering algorithms suitable for
lineament mapping. The filters applied to the several bands therefore, helped in extracting
structures and identifying their trends using several image enhancement techniques like the
Linear, Gamma, Gaussian and histogram equalizer and the statistical approach of principle
component analysis which uses the covariance of spectral bands to analyze spectral patterns
associated with structures in the study area. The DEM was processed for topography and
establishing the intersection between tilted plates which helped in recognizing different
structures. The interpretation process involved correlating drainage, vegetation patterns and
topography of the area with structures using visual interpretation elements of texture, color, tonal
differences and orientation. The color and pattern of the geology and geomorphology of the area
were also used to infer the different types of lineaments. The output was a structural map
representing the different lineations present in the area. The results were validated against sample
data collected together with field observations.
Citation
Master of Science in Geographic Information SystemsPublisher
University of Nairobi