Abstract
Abstract. This study exploited the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) data in order to map lithological units and structural map in the south High Atlas of Marrakech. The method of analysis was used by principal component analysis (PCA), band ratios (BR), Minimum noise fraction (MNF) transformation. We performed a Support Vector Machine (SVM) classification method to allow the joint use of geomorphic features, textures and multispectral data of the Advanced Space-borne Thermal Emission and Reflection radiometer (ASTER) satellite. SVM based on ground truth in addition to the results of PCA and BR show an excellent correlation with the existing geological map of the study area. Consequently, the methodology proposed demonstrates a high potential of ASTER and Landsat 8 OLI data in lithological units discrimination. The application of the SVM methods on ASTER and Landsat satellite data show that these can be used as a powerful tool to explore and improve lithological mapping in mountainous semi-arid, the overall classification accuracy of Landsat8 OLI data is 97.28% and the Kappa Coefficient is 0.97. The overall classification accuracy of ASTER using nine bands (VNIR-SWIR) is 74.88% and the Kappa Coefficient is 0.71.
Highlights
On May, 2013 Landsat 8 Operational Land Imager (OLI) became available as well as Thermal Infrared Sensor (TIRS) imagery
The results showed that the mafic and ultra-mafic rock units are detected as light brownish hue like rhyolite; schist as green color and vegetated region appears as pink color in the study area (Figure 7)
1.6 Concluding Remarks: This study investigated the utility of the Landsat 8 OLI and ASTER data for lithologic mapping in the southern mountains of the high atlas of Marrakech
Summary
On May, 2013 Landsat 8 Operational Land Imager (OLI) became available as well as Thermal Infrared Sensor (TIRS) imagery. This study aims to provide an overview of the use of remote sensing data ASTER and Landsat OLI images, in the field of geological mapping in the Imini-Ounilla district (South High Atlas of Marrakech, Morocco). This will be achieved mainly using digital processing, Band ratio, principal component analysis (PCA) and minimum noise fraction (MNF) in order to enhance the capability of lithological discrimination between different rock units in the study area
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