EFFECTIVE ALGORITHMS FOR REMOTE SENSING DATA INTEGRATION AS APPLIED TO GEOLOGICAL STUDIES: EXAMPLES FROM THE AFAR DEPRESSION, ETHIOPIA

Remote sensing data integration is the process whereby data with different spatial and/or spectral characteristics and digital elevation models (DEM) covering the same region are combined and displayed in a single image. In this presentation, optical (Advanced Space-borne Thermal Emission Radiometer (ASTER) and radar images (Shuttle Imaging Radar (SIR) C/X-band Synthetic Aperture radar (SAR) and RADARSAT), and DEMs (Digital Terrane Elevation Data (DTED)) covering parts of the Afar Depression in NE Ethiopia are fused using: (1) Red-Green-Blue (RGB) – Intensity-Hue-Saturation (IHS) – RGB transformation; and (2) Color Normalization Transformation (CNT). The objective is to enhance the effectiveness of remote sensing data in mapping morphologically-defined structures and discriminate between volcanic flows of different ages. We used the Dobe Graben and the Erte’ Ale volcano, respectively as examples. The advantage of integrating optical and radar images is that multi-spectral optical remote sensing data, which measure material composition, is combined with radar data, which emphasize surface roughness and morphology. In addition, DEMs help in understanding the three-dimensional geometry of geological features. Remote sensing data integration has significantly improved the extractable geological information. Using visible and near infrared (VNIR) ASTER - C-band Radarsat - DTED images and field studies in the Dobe Graben, we are able to identify high-angle normal faults and low-angle-layer parallel slip planes associated with extensional imbrication fans. Integration of thermal infrared (TIR) ASTER band-ratio images with SIR-C/X-SAR images and DTED data allowed us to identify volcanic flows of different ages and/or compositions in the Erte’ Ale volcano.