Geobotanical and geomorphological approach to map the surface lithology using remote sensor data

The objective of this research was to evaluate the potential of ASTER imagery for lithologic mapping in the heavily vegetated area using digital image processing. This study used geobotanical and geomorphological approach to identify the underlying surface lithology of the study area. Two lithologic maps were produced: the first lithologic map based on the combination of vegetation and drainage pattern was done using knowledge base classification and the second lithologic map based on GIS analysis of drainage pattern. Results of both of these two lithologic maps show that shale is dominant in the axial part of anticlines, sandstone in the outer flank of anticlines and alternation of sandstone and shale in the middle flank of anticlines. Accuracy of classification derived from knowledge-based classification was checked against field data and this shows an agreement of about 36% for sandstone, 92% for sandstone-shale alteration and 55% for shale units. Similar accuracy analysis yielded about 34% agreement for sandstone, 98% for sandstone-shale alteration and 77% for shale for the litho map derived on the basis of drainage pattern. Methodologies and findings of this study showed that remotely sensed ASTER imagery is a good tool for mapping lithology of a heavily vegetated area like this study area.