Characterized by lithological diversity and rich mineral resources, Benshangul-Gumuz National Regional State located in Asosa Zones, Western Ethiopia has been investigated for geological mapping and morpho-structural lineaments extraction using PALSAR (Phased Array type L-band Synthetic Aperture Radar) Fine Beam Single (FBS) L-HH polarization and Landsat-5 TM (Thematic Mapper) datasets. These data were preprocessed to retrieve ground surface reflectance and backscatter coefficients. To overcome the geometry acquisition between the two sensors, they were geometrically and topographically rectified using ASTER-V2 DEM. Intensity-Hue-Saturation, directional filters and automatic lineaments extraction were applied on the datasets for lithological units' discrimination and structural delimitation for potential mineral exploration. The obtained results showed good relationship among the topographic morphology, rock-substrate, structural variations properties, and drainage network. The spectral variations were easily associated with lithological units. Likewise, the morpho-structural information highlighted in the PALSAR image was visible without altering the radiometric integrity of the details in TM bands through the fusion process. Moreover, predominant lineaments directions trending NE-SW, NS, and NW-SE were identified. Results of this study highlighted the importance of the PALSAR FBS L-HH mode and TM data fusion to enhance geological features and lithological units for mineral exploration particularly in tropical zones.

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This paper presents a fusion approach of PALSAR-FBS L-HH polarization and Landsat-5 TM datasets for geological mapping and morpho-structural lineaments extraction. The study site is situated in Western Ethiopia, BenshangulGumuz National Regional State, Asosa Zones; which is characterized by lithological diversity and rich mineral resources. The TM data were calibrated radiometrically and corrected atmospherically to retrieve ground surface reflectance. As well, the radar data were calibrated to retrieve backscatter coefficients and then filtered using the gamma filter to reduce speckle. Moreover, the two images were geometrically corrected and topographically rectified using the ASTER GDEM, UTM projection and WGS84 geodetic reference. Then, the images were transformed to Intensity-HueSaturation (I-H-S) using three different methods, such as hexagonal, double hexagonal and cylindrical transformations. Based on several tests integrating all the considered datasets, the SWIR and NIR bands were selected for "I", "H" and "S" codification using cylindrical transformation. Three color composites (named spatio-maps) were selected due to their best results: 1) "I", "H" and "L-HH"; 2) "I", "H" and the blue band resulting from the fusion of TM (7, 5, 4) and LHH; and 3) the R-G-B resulting from the fusion of "I", "H", "S" and "L-HH". These derived spatio-maps show good relationship between the topographic morphology, rock-substrate, structural variations properties, and drainage network. In addition, the spectral variations are easily associated with lithological units. Likewise, the morpho-structural information's highlighted in the PALSAR image are visible without altering the radiometric integrity of the details in TM spectral bands through the fusion process. Otherwise, the synergy between visual and automatic methods for lineaments extraction provides the best lineaments maps. The obtained product shows that the predominant lineaments directions are the NE-SW and the NS, and then the second dominant direction is the NW-SE. The results integration in GIS environment provides good discrimination of fractures and details of structural attributes. This research results highlight the importance of the PALSAR fine mode L-HH and TM data fusion to enhance geological features.