Lithological and lineament mapping using remote sensing is a fundamental step in various geological studies, as it forms the basis for the interpretation and validation of the results obtained. There were two objectives for this study, applied in the Imini-Ounilla-Asfalou district, South High Atlas of Marrakech region: first, lithological mapping by satellite image processing techniques such as ASTER L1B (hight spectral and spatial resolution), namely Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), as well as the application of three types of supervised classification, namely Spectral Angle Mapper (SAM), Maximum Likelihood (ML) and Minimum Distance (MD), on the visible/near-infrared (VNIR) and short-wave infrared (SWIR) spectral bands of our ASTER image; second, an analysis of the distribution of lineaments by automatic extraction using a Global Digital Elevation Model (GDEM) and the PC1 image derived from the PCA transformation applied to the satellite image. The best results are highlighted by the delineation of new facies in relation to the existing map; after confirmation in the field, all of these facies, which include Eocene, Triassic and Jurassic formations, are represented on the new map. The results of lineaments showed that each of them systematically shows a similarity in terms of concentration and orientation, with four preferential oriented systems: NE-SW, E-W, NNE-SSW and NW-SE. The lineaments mainly follow those of the major fault zones, with high concentrations in the northeast and southwest parts of the study area.
Certainly, remote sensing data more specifically Landsat 8 Operational Land Imager and SRTM images can be used as a powerful tool for lineament mapping. Lineament extraction method and statistical studies are attractive an alternative analysis techniques which resolve lineament mapping problems in the region and allow exceeding the usual classical method. The present study deals with the estimation of the potential of both Landsat 8 Operational Land Imager sensor images and SRTM Digital Elevation Model data for automatic lineament extraction in the south side of Marrakech High Atlas (Telouet-Tighza area). After image corrections, enhancement methods such as principal component analysis (PCA), Band Composite and Directional Filter were adopted in order to create new images with high visibility of linear structures. A Principal Component Analysis (PCA) has been realized on the Landsat 8- OLI bands in order to reduce the redundancy information in highly correlated bands. Validating the use of the new Landsat band composite image relied on calculating statistical optimum index factor (OIF), Correlation Index and matching interpreted linear structures to previously published geologic maps. Therefore, the SRTM Digital Elevation Model is used in this study to generate shaded relief images as well as three-dimensional representation of the terrain and slope. Shaded relief images allowed to highlight linear features related to geomorphological data which are not identified in optical images. Multi-source data, such as Band Ratio image, geological map and fieldworks were used to verify and eliminate meaningless and non- geological lineaments extracted by applying line model tool of Geomatica software.The results indicate that automatic method was applied successfully for lineament mapping in the Telouet-Tighza area and showing improvement over previous techniques in detailing the main tectonic faults. Slope and lithological factor were recognized to understand their relation with spatial distribution of lineaments over the study area. Structural lineaments generated from PC1, selected Band composite images and shaded relief DEM data proved the coincidence of their direction, length, and density with the tectonic system of the study area. The resultant fracture network is oriented ENE-WSW and E-W with a predominance of the E-W direction. It showsgood correlation between the distribution and the orientation of the lineaments on updated lineament map in comparison with the localization and orientation of fault system pattern in the existing geological map. In addition, the new synthetic structural map shows more information and details compared with based geological map which reveals the performance of Landsat 8-oli bands and SRTM data in this kind of study.
This study provides the first evaluation of the potential of both Landsat-8 Operational Land Imager (OLI) sensor images and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data, for automated lineament extraction in the south side of Marrakech High Atlas (MHA), (Telouet-Tighza area). After image corrections, enhancement methods such as Principal Component Analysis (PCA), Band Composite (BC) and Directional Filter (DF) were adopted in order to create new images that provide high visibility of linear structures. The new Landsat BC image used in this study was selected based on the calculation of the optimum index factor (OIF) and Correlation Index. In addition to the Landsat image, the SRTM DEM is used to detect structural lineaments in the area, by generating shaded relief images. Multi-source data, such as Band Ratio (BR) image, geological maps and fieldwork, were used to eliminate the non-geological lineaments extracted. The results indicate that automated method was applied successfully for lineament mapping in this area, by detailing the main tectonic faults. Moreover, new lineaments are identified and are validated by field works. Structural lineaments extracted show compatibility in their direction, length, distribution and density with the tectonic evolution of the study area. A total of 2945 lineaments are extracted with major ENE-WSW, and predominant E-W directions. The new structural map shows more structural information compared with the geological map of this area, and exemplifies the performance of Landsat-8 OLI bands and SRTM data in this kind of study.
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