An integrated lineament extraction from satellite imagery and gravity anomaly maps for groundwater exploration in the Gongola Basin

Epuh, E. E.; Okolie, Chukwuma J.; Daramola, Olagoke E.; Ogunlade, Funmilola S.; Oyatayo, Funmilayo J.; Akinnusi, Samuel A.; Emmanuel, Eno-Obong I.

doi:10.1016/j.rsase.2020.100346

Cited by 14 publications

(9 citation statements)

References 11 publications

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“…In general, there is a close relationship between geological lineaments and topographic relief; several faults form clear topographic features that appear in the lineament map. It is common that the abrupt changes in topography might be the consequence or the outcome of structural phenomena such as, faults, joint sets, folds or fractures (Epuh et al 2020). Accordingly, detailed extraction of topographic features will help in identifying lineaments and interpreting the tectonic history of this region.…”

Section: Geological Settingmentioning

confidence: 99%

“…A number of studies have demonstrated the applicability of the automatic extraction by using Line Module algorithm for lineament mapping (Epuh et al 2020;Shandini et al 2020; Azman, Ab Talib, and Sokiman 2020). In Some works, lineament extraction was tried to be executed from only Landsat 8 OLI data.…”

Section: Introductionmentioning

confidence: 99%

“…Directional FilterDirectional ltering is de ned as a spatial domain ltering( Javhar et al 2019),Thataccentuates the rst derivative between each two adjacent pixels and selectively bring out any feature in the input image having speci c direction gradients(Epuh et al 2020;Jellouli et al 2021). It consists of changing the values of pixels by replacing each center pixel by the median value within the neighborhood pixels(Farahbakhsh et al 2020).…”

mentioning

confidence: 99%

“…It consists of changing the values of pixels by replacing each center pixel by the median value within the neighborhood pixels(Farahbakhsh et al 2020). The resulted image comprises pixels with uniform values while the others present variable values that indicate bright edges(Epuh et al 2020). Furthermore, the directional nature of structural lineaments give up to the obligation of using directional ltering in order to enhance the perception of the structural features when processing multispectrales images(Javhar et al 2019;Hermi et al 2017) displayed in his study that the directional contrast gradient is produced by ltering algorithm on the input image independently of lineaments orientation.…”

mentioning

confidence: 99%

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Mapping and analysis of structural lineaments using SRTM radar data and Landsat 8-OLI images in Telouet-Tighza area, Marrakech High Atlas - Morocco.

Errami

Algouti

et al. 2022

Preprint

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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.

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Section: Geological Settingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Mapping and analysis of structural lineaments using SRTM radar data and Landsat 8-OLI images in Telouet-Tighza area, Marrakech High Atlas - Morocco.

Errami

Algouti

et al. 2022

Preprint

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“…Gravity data interpretation has been widely used to appraise the different types of subsurface structures and their locations [1][2][3][4][5][6][7][8]. Gravity methods have been widely applied to ore and mineral exploration [9-13], hydrocarbon exploration [14 -16], cave detection [17,18], hydrogeology [19,20], geothermal and volcanic activity [21][22][23], locating of unexploded military ordnance [24], environmental and engineering application [25,26] and archaeological investigations [27,28].…”

Section: Introductionmentioning

confidence: 99%

Gravity Anomaly Interpretation Using the R-Parameter Imaging Technique over a Salt Dome

Essa¹,

Diab²

2022

Gravitational Field - Concepts and Applications

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Rapid imaging technique, so-called “R-parameter”, utilized for interpreting a gravity anomaly profile. The R-parameter based on calculating the correlation factor between the analytic signal of the real anomaly and the analytic signal of the forward anomaly of assumed buried source denoted by simple geometric shapes. The model parameters (amplitude, origin, depth, and shape factor) picked at the maximum value of the R-parameter. The technique has been proved on noise free and noisy numerical example, numerical example showing the impact of interfering sources. Furthermore, the introduced technique has been successfully applied to visualize a salt dome gravity anomaly profile, USA. The obtained results are in good agreement with those reported in the published studies and that with that obtained from drilling.

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Fractal characteristics of lineaments extracted from OLI images at different time phases

Zhang

Luo

et al. 2022

Earth Sci Inform

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An integrated lineament extraction from satellite imagery and gravity anomaly maps for groundwater exploration in the Gongola Basin

Cited by 14 publications

References 11 publications

Mapping and analysis of structural lineaments using SRTM radar data and Landsat 8-OLI images in Telouet-Tighza area, Marrakech High Atlas - Morocco.

Mapping and analysis of structural lineaments using SRTM radar data and Landsat 8-OLI images in Telouet-Tighza area, Marrakech High Atlas - Morocco.

Gravity Anomaly Interpretation Using the R-Parameter Imaging Technique over a Salt Dome

Fractal characteristics of lineaments extracted from OLI images at different time phases

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