Remote sensing based improvement of the geological map of the Neoproterozoic Ras Gharib segment in the Eastern Desert (NE–Egypt) using texture features

Jakob, Sandra; Bühler, Benjamin; Gloaguen, Richard; Breitkreuz, Christoph; Eliwa, Hassan A.; Gameel, Khaled El

doi:10.1016/j.jafrearsci.2015.07.024

Cited by 23 publications

(15 citation statements)

References 21 publications

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“…Pournamdari et al (2014) Amer et al (2010) showed that ASTER data have important potential for mapping granitic and ophiolitic rocks by applying band ratios (2 + 4) / 3, (5 + 7) / 6, (7 + 9) / 8. Also, a color composite of the ACP bands (5,4,2) showed satisfied results to identify ophiolitic rocks The Moroccan Anti-Atlas is a mountain belt in southwestern Morocco, oriented ENE-WSW about 800 km long and 200 km wide ( Fig. 1).…”

Section: Introductionmentioning

confidence: 89%

“…The availability of image data, with high or medium spatial and spectral resolution, opens the door to an easy and efficient identification of different geological structures such as lineaments. furthermore, the different techniques and methods of spatial imaging processing allow to extract interpretable geological information with better precision [5].…”

Section: Introductionmentioning

confidence: 99%

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Application of Remote Sensing Data in Lithological Discrimination of Kerdous Inlier in the Anti Atlas Belt of Morocco

Jellouli

Harti

Adiri

et al. 2019

JOIV : Int. J. Inform. Visualization

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Remote sensing data reveals a great importance for lithological mapping due to their spatial, spectral and radiometric characteristics. Lithological mapping using spatial data is a preliminary and important step to mineral mapping. In this work, several spectral and radiometric transformations methods were applied on Landsat 8 OLI data to enhance lithological units in the study area situated in the Anti Atlas belt. The methods of Optimum Index Factor (OIF), Decorrelation Stretching (DS), Principal Components Analysis (PCA) and Band Ratioing (BR) showed good results for lithological mapping in comparison with the existing geological and field investigation. An RGB color composite of OLI bands 651 was developed for mapping lithological units of the study area by fusing optimum index factor (OIF) and decorrelation stretching methods. furthermore, Band ratios derived from image spectra were applied in two RGB color composites (7+4/2, PC1, PC2) and (PC1, 7/6, 3/7) providing good discrimination of the lithological units. The Landsat-8 OLI data significantly provided satisfied results for lithological mapping.

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Section: Introductionmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Application of Remote Sensing Data in Lithological Discrimination of Kerdous Inlier in the Anti Atlas Belt of Morocco

Jellouli

Harti

Adiri

et al. 2019

JOIV : Int. J. Inform. Visualization

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“…This study can evaluate recently launched Landsat-8 satellite for targeting hydrothermal alterations and compare its results with ASTER which is widely accepted for such cases (Mezned et al 2010;Jakob et al 2015). To this purpose robust mapping and digital image processing methods in SWIR and VNIR for both the ASTER and OLI data for Shahr-e-Babak area were carried out.…”

Section: Introductionmentioning

confidence: 99%

Targeting Hydrothermal Alterations Utilizing Landsat-8 Andaster Data in Shahr-E-Babak, Iran

Safari

Pour

Maghsoudi

et al. 2017

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

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ABSTRACT:Shahr-e-Babak tract of the Kerman metalogenic belt is one of the most potential segments of Urumieh-Dokhtar (Sahand-Bazman) magmatic arc. This area encompasses several porphyry copper deposits in exploration, development and exploitation hierarchy. The aim of this study is to map hydrothermal alterations caused by early Cenozoic magmatic intrusions in Shahr-e-Babak area. To this purpose, mineral mapping methods including band combinations, ratios and multiplications as well as PCA and MNF data space transforms in SWIR and VNIR for both ASTER and OLI sensors. Alteration zones according to spectral signatures of each type of alteration mineral assemblages such as argillic, phyllic and propylitic are successfully mapped. For enhancing the target areas false color composites and HSI-RGB color space transform are performed on developed band combinations. Previous studies have proven the robust application of ASTER in geology and mineral exploration; nonetheless, the results of this investigation prove applicability of OLI sensor from landsat-8 for alteration mapping. According to the results, evidently OLI sensor data can accurately map alteration zones. Additionally, the 12-bit quantization of OLI data is its privilege over 8-bit data of ASTER in VNIR and SWIR, thus OLI high quality results, which makes it easy to distinguish targets with enhanced color contrast between the altered and unaltered rocks.

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“…Different surface objects have different surface morphology, which yields different textural features. Textural features have been widely applied in several studies, such as sea ice mapping, crop species composition classification, vegetation structure analysis, lithological discrimination, and land-cover mapping [20,[30][31][32][33][34][35][36]. However, these studies focused more on the improvement or design of texture-derived methods, and texture features were calculated from a single remote sensing image.…”

Section: Introductionmentioning

confidence: 99%

Integrating Textural and Spectral Features to Classify Silicate-Bearing Rocks Using Landsat 8 Data

2016

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Abstract:Texture as a measure of spatial features has been useful as supplementary information to improve image classification in many areas of research fields. This study focuses on assessing the ability of different textural vectors and their combinations to aid spectral features in the classification of silicate rocks. Texture images were calculated from Landsat 8 imagery using a fractal dimension method. Different combinations of texture images, fused with all seven spectral bands, were examined using the Jeffries-Matusita (J-M) distance to select the optimal input feature vectors for image classification. Then, a support vector machine (SVM) fusing textural and spectral features was applied for image classification. The results showed that the fused SVM classifier achieved an overall classification accuracy of 83.73%. Compared to the conventional classification method, which is based only on spectral features, the accuracy achieved by the fused SVM classifier is noticeably improved, especially for granite and quartzose rock, which shows an increase of 38.84% and 7.03%, respectively. We conclude that the integration of textural and spectral features is promising for lithological classification when an appropriate method is selected to derive texture images and an effective technique is applied to select the optimal feature vectors for image classification.

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Remote sensing based improvement of the geological map of the Neoproterozoic Ras Gharib segment in the Eastern Desert (NE–Egypt) using texture features

Cited by 23 publications

References 21 publications

Application of Remote Sensing Data in Lithological Discrimination of Kerdous Inlier in the Anti Atlas Belt of Morocco

Application of Remote Sensing Data in Lithological Discrimination of Kerdous Inlier in the Anti Atlas Belt of Morocco

Targeting Hydrothermal Alterations Utilizing Landsat-8 Andaster Data in Shahr-E-Babak, Iran

Integrating Textural and Spectral Features to Classify Silicate-Bearing Rocks Using Landsat 8 Data

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