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Highlighting Volcanic Outcrops by Mapping Geological Lineaments Using Satellite Data in the Saka Region, North-East Morocco

Elaaraj Abdallah, Lhachmi Ali, Tabyaoui Hassan, Alitane Abdennabi, El Yousfi Yassine

Ecological Engineering & Environmental Technology

2024

Vol. 25, iss. 2

54--69

The Saka region and its environs are situated in the northeastern part of Morocco. This study aimed to optimize automated lineament extraction based on the comparing of Landsat-8 optical satellite data with Sentinel-2B for enhanced analysis. The research delved into the structural lineaments within the Saka region, with the objective of advancing the understanding of lineament extraction techniques. Remote sensing techniques were employed to extract and map these lineaments Furthermore, the study sought to elucidate the distribution and genesis of volcanism in the Saka region and its surroundings in the context of geodynamics. The availability of optical and multispectral remote sensing datasets, including those from Landsat-8 OLI and Sentinel-2B, characterized by medium and high spatial resolutions, enhances the efficiency and simplicity of lineament mapping – an essential component of any structural geological investigation. However, due to the differences in spatial resolution and sensitivity to land cover, the outcomes from these diverse data sources were derived with varying resolutions display variability. The spatial resolution of the images significantly influences the precision and clarity of the retrieved lineaments. The findings underscore a strong correlation between lineament directions (primarily NE-SW, E-W, NW-SE) and faults, i.e., correspond to the distribution of volcanic outcrops in the Saka area and its vicinity. For validation purposes, the lineaments extracted through directional filtering were compared to the manually obtained lineaments, alongside lineaments digitized from the pre-existing neotectonic map (faults) as well as satellite images depicting lineaments in the study area. Density analysis was employed to investigate the correlation between the concentration of lineaments and the distribution of pre-existing faults. Additionally, the geological map was utilized to refine the correlation between density distribution and the spatial orientations of volcanic rock formations in the study area.

Utilization of ASTER data in lithological and lineament mapping of the southern flank of the Central High Atlas in Morocco

Errami Maryam, Algouti Ahmed, Algouti Abdellah, Farah Abdelouhed, Agli Saloua

Geologos

2023

Vol. 29, No. 1

1--20

Geological mapping undoubtedly plays an important role in several studies and remote sensing data are of great significance in geological mapping, particularly in poorly mapped areas situated in inaccessible regions. In the present study, Principal Component Analysis (PCA), Band Rationing (BR) and Minimum Noise Fraction (MNF) algorithms are applied to map lithological units and extract lineaments in the Amezri-Amassine area, by using multispectral ASTER image and global digital elevation model (GDEM) data for the first time. Following preprocessing of ASTER images, advanced image algorithms such as PCA, BR and MNF analyses are applied to the 9ASTER bands. Validation of the resultant maps has relied on matching lithological boundaries and faults in the study area and on the basis of pre-existing geological maps. In addition to the PCA image, a new band-ratio image, 4/6–5/8–4/5, as adopted in the present work, provides high accuracy in discriminating lithological units. The MNF transformation reveals improvement over previous enhancement techniques, in detailing most rock units in the area. Hence, results derived from the enhancement techniques show a good correlation with the existing litho-structural map of the study area. In addition, the present results have allowed to update this map by identifying new lithological units and structural lineaments. Consequently, the methodology followed here has provided satisfactory results and has demonstrated the high potential of multispectral ASTER data for improving lithological discrimination and lineament extraction.