| Abstract |
Geothermal energy is a clean and renewable energy source which if harnessed can contribute to the Socio-economic growth of Kenya to achieve the power demand envisioned in ‘Vision 2030’.The initial investment in geothermal exploration is expensive, time consuming and tiresome venture which requires alot of time, resources and manpower to achieve the targeted results. To reduce time spent during exploration, proper base maps or base data is required to lessen the workload. Various basemaps like topographical maps, aerial photographs and satellite images are used for baseline data to guide during exploration. Most of the basemaps give topographical information which is not detailed and upto date enough to assist in providing detailed data interpretation during resource exploration. Classified satellite images come in handy during geothermal exploration surveys since the geoscientists will be equiped with preliminary data which acts as a guide and also gives them a clue of the results to expect during the exploration.With proper image classification, the field exercise can act as a validation process hence reduce the time spent for field work. Satellite image classification is specifically usefull to Geologists since rock types can be determined based on the reflectance characteristics of the rocks. Environmentalists can also benefit from satellite image classification to determine the landuse and landcover of a given area based on the spectral properties of the features. Landsat multispectral image use in geothermal exploration, and to classify the landcover and landuse in Silali geothermal prospect and two image classification methods will be discussed in this paper. |