Litho-structural analysis of eastern part of Ilesha schist belt, Southwestern Nigeria

Fagbohun, Babatunde Joseph; Adeoti, Blessing; Aladejana, Olabanji Odunayo

doi:10.1016/j.jafrearsci.2017.05.017

Cited by 19 publications

(7 citation statements)

References 41 publications

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“…The lineaments extracted from the S1A VH and VV polarization images (Figure 11c,d respectively) are mainly located in the slope and shading and even in the areas with no value classified as a shading area having slops and structural features, thus, indicating the high sensitivity of S1A radar data to geomorphology compared to optical L8 and S2A data. In lineament analysis and mapping studies, a density classification map is a parameter widely used for a correlation analysis with other geological information [4,20,73,96]. This classification map provides information about the concentration of lineaments per unit area [97].…”

Section: Resultsmentioning

confidence: 99%

“…From previous studies, one can conclude that lineaments usually occur as edges with tonal differences in satellite images and that most of the detection approaches are based on edge enhancement and filtering techniques [3][4][5]. These studies proposed two principal techniques for lineament identification and extraction from remotely sensed data.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Multi-Resolution Optical Landsat-8, Sentinel-2 and Radar Sentinel-1 Data for Automatic Lineament Extraction: A Case Study of Alichur Area, SE Pamir

et al. 2019

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Lineament mapping, which is an important part of any structural geological investigation, is made more efficient and easier by the availability of optical as well as radar remote sensing data, such as Landsat and Sentinel with medium and high spatial resolutions. However, the results from these multi-resolution data vary due to their difference in spatial resolution and sensitivity to soil occupation. The accuracy and quality of extracted lineaments depend strongly on the spatial resolution of the imagery. Therefore, the aim of this study was to compare the optical Landsat-8, Sentinel-2A, and radar Sentinel-1A satellite data for automatic lineament extraction. The framework of automatic approach includes defining the optimal parameters for automatic lineament extraction with a combination of edge detection and line-linking algorithms and determining suitable bands from optical data suited for lineament mapping in the study area. For the result validation, the extracted lineaments are compared against the manually obtained lineaments through the application of directional filtering and edge enhancement as well as to the lineaments digitized from the existing geological maps of the study area. In addition, a digital elevation model (DEM) has been utilized for an accuracy assessment followed by the field verification. The obtained results show that the best correlation between automatically extracted lineaments, manual interpretation, and the preexisting lineament map is achieved from the radar Sentinel-1A images. The tests indicate that the radar data used in this study, with 5872 and 5865 lineaments extracted from VH and VV polarizations respectively, is more efficient for structural lineament mapping than the Landsat-8 and Sentinel-2A optical imagery, from which 2338 and 4745 lineaments were extracted respectively.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of Multi-Resolution Optical Landsat-8, Sentinel-2 and Radar Sentinel-1 Data for Automatic Lineament Extraction: A Case Study of Alichur Area, SE Pamir

et al. 2019

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“…The Shear Zone was formed due to shearing activities of late Precambrian times ( Odeyemi, 1993 ). Interpretation of remotely sensed imageries, shows a general recumbent folding in the area ( Fagbohun et al., 2017 ). This Shear Zone hosts the 250 km, NNE-SSW trending Ifewara fault.…”

Section: Discussionmentioning

confidence: 99%

Pan African Nappe system: evidence of thrust structures from Okemesi, southwestern Nigeria

Bamisaiye

Ajala

2021

Heliyon

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The Okemesi area, southwestern Nigeria, is part of the Ilesha schist belt and play host to the Okemesi fold belt and the Ifewara Shear Zone. Nappe structures had been proposed for some parts of Southwestern Nigeria without very clear meso or micro structural evidence. This study provides a lot of new structural evidences to substantiate the inferred Nappe structures within the Okemesi fold belt. Mapping of the Okemesi fold has been hampered by thick vegetation in the past. However, a major deformation zone was exposed by the recent landslide activities in the area, structures and lithologies exposed by the landslide were studied and structural features that are typical of transtensional and transpressional settings were observed. This paper presents the result of the systematic filed mapping which revealed the complete, fold transposition, elements of internal strain such as cleavages and mineral lineation, intrafolial folds, flexure slip, sheath, recumbent and conjugate kink folds, winged porphyroblast, faults (low angle reverse faults, dextral faults, normal faults), ramp and flat structures, etc. The characteristics and the geometry of the observed thrust structures make it an important piece of evidence, not only to infer the tectonic events in the area, but also to constrain the timing and nature of movement associated with thrusting in the area.

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“…He has also demonstrated a good correspondence between those bands. In the present paper; based on the geological studies carried in the region of Tafilalet (Baidder et al, 2016(Baidder et al, , 2008Lubeseder et al, 2010;Michard et al, 2008;Soulaimani and Burkhard, 2008) and based on the remote sensing methods used in such geological mapping studies (Bishop et al, 2018b;Fagbohun et al, 2017;Rajendran and Nasir, 2017;Asadzadeh and de Souza Filho, 2016;van der Meer et al, 2012;Bannari et al, 2015Bannari et al, , 2016; we try to deduce the best improvement procedure (OIF, DS or MNF) that can be used to discriminate rock lithology encountered in the region. We also aim to classify lithofacies by processing sentinel 2A multispectral data.…”

Section: Introductionmentioning

confidence: 99%

The Contribution of Sentinel-2 Satellite Images for Geological Mapping in the South of Tafilalet Basin (Eastern Anti-Atlas, Morocco)

Fal

Maanan

Baïdder

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Geological mapping in desert, mountainous or densely vegetated areas are sometimes faced with many constraints. Recently several remote sensing methods are used on ASTER or LANDSAT imagery for making that task easier. The aim of this paper is to evaluate the applicability of some of these methods on Sentinel-2A images. The study, therefore, focuses on a lithological classification using these multispectral images in the south of the Tafilalet basin. To achieve this goal, two L1C level images were used. Decorelation stretch combined with the optimal index factor (OIF) and Minimum Noise Fraction (MNF) were the main improvements used for RGB combination images. The classifiers Spectral Angle Mapper (SAM) and the Maximum Likelihood classifier (MLC) have been evaluated for a most accurate classification to be used for our lithofacies mapping. The latest drawn geological maps and RGB images of false colour combinations were used to select regions of interest (ROI) as the endmembers to use for these classifiers. Obtained results showed a clear discrimination of the different lithological units of the study area. Classifications evaluation showed that the Maximum likelihood classifier is more accurate with an overall accuracy of 76% and a Kappa coefficient is 0.74. Finally, this study has shown the importance of the use of sentinel-2 multispectral images in geological mapping and has shown that the high spectral resolution of the VNIR and SWIR bands creates a synergy with the high spatial resolution for optimal lithological mapping.</p>

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Litho-structural analysis of eastern part of Ilesha schist belt, Southwestern Nigeria

Cited by 19 publications

References 41 publications

Comparison of Multi-Resolution Optical Landsat-8, Sentinel-2 and Radar Sentinel-1 Data for Automatic Lineament Extraction: A Case Study of Alichur Area, SE Pamir

Comparison of Multi-Resolution Optical Landsat-8, Sentinel-2 and Radar Sentinel-1 Data for Automatic Lineament Extraction: A Case Study of Alichur Area, SE Pamir

Pan African Nappe system: evidence of thrust structures from Okemesi, southwestern Nigeria

The Contribution of Sentinel-2 Satellite Images for Geological Mapping in the South of Tafilalet Basin (Eastern Anti-Atlas, Morocco)

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