Abstract
Lithological identification and mapping are crucial in understanding geological processes, mineral exploration, natural resource management, land-use planning, and other applications. Conventional field-focused mapping of geology is often requiring a lot of time and expensive, particularly in remote and rugged terrains, like in our area. Recent advances in satellite remote sensing provide efficient tools for lithological discrimination. This study explores the application of Sentinel-2 multispectral imagery to develop a lithological map in a case of Meda kebele. The Sentinel-2 satellite image was classified by using support vector machine (SVM) classification system to prepare a excellent geological map, which was validated by previous geological maps and field surveys For this purpose, several band combinations, spectral indices, and image processing methods, including OIF, ICA and PCA, were used in order to enhance the contrast among different rocks. Following that, a supervised classification supported by field survey and previous lithological maps of the area was carried out to create a lithological map. The results show that Sentinel-2 imagery can distinguish between the common geological units found in the area, which include metavolcanics, basalt, dolomite, limestone, marble, slate and sandstone, due to it has good spatial resolution of 10- 60 m and vast spectral extent from VNIR-SWIR. This paper highlights the significance of Sentinel-2 data for regional geological mapping, giving baseline information for mineral prospecting and resource management in Meda kebele.