Detection of hydrothermal mineralized zones associated with listwaenites in Central Oman using ASTER data

Rajendran, Sankaran; Nasir, Sobhi; Kusky, Timothy M.; Ghulam, Abduwasit; Gabr, Safwat S.; El‐Ghali, Mohamed A.K.

doi:10.1016/j.oregeorev.2013.02.008

Cited by 82 publications

(41 citation statements)

References 44 publications

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“…However, the spectral reflectance of water class is higher than standard spectral reflectance clear water, especially in SWIR, because the rivers in the study area are shallow and the bedrock influences the reflectance ( Figure 4A). All classes have strong absorption in band 8 because of C-O, hydroxyl and Fe +2 effects [45,113,114]. The trend of valley fill sediments and diorite spectra in bands 7 and 8, which is different than the rest of the spectra indicate hydroxyl bearing minerals.…”

Section: Discussionmentioning

confidence: 92%

“…A wide spectrum absorptions region (900-1300 nm) centered in 1050, a broad shallow feature (1900-2072 nm) centered in 1967, and a sharp spectrum absorptions in 1388 nm, 2300 nm and 1831 nm are due to olivine content [13,15,16,21,113,[115][116][117][118]. Metabasalt, basalt and gabbro reflectance samples spectra have absorptions located at 1000-1050 nm and 1800-1900 nm because of ferrous iron (Fe 2+ ) content [45,119]. All classes have strong absorption in band 8 because of C-O, hydroxyl and Fe +2 effects [45,113,114] (Figure 8A).…”

Section: Discussionmentioning

confidence: 99%

“…Metabasalt, basalt and gabbro reflectance samples spectra have absorptions located at 1000-1050 nm and 1800-1900 nm because of ferrous iron (Fe 2+ ) content [45,119]. All classes have strong absorption in band 8 because of C-O, hydroxyl and Fe +2 effects [45,113,114] (Figure 8A). SAM method does not consider the spectral illumination and only consider the spectral similarity between the reference and image spectra [120], therefore it introduces potential commission errors in the results.…”

Section: Discussionmentioning

confidence: 99%

“…Each scene of ASTER covers 60 × 60 km 2 on land [43]. ASTER provides more spectral bands in the SWIR than say Landsat, which therefor increases its ability to spectrally discriminate minerals and rocks on the Earth's surface [2,13,[44][45][46]. We processed a cloud-free ASTER level 1A scene acquired on 24 August 2003 and provided by the Iraq Geological Survey (GEOSURV-Iraq).…”

Section: Data Characteristics and Softwarementioning

confidence: 99%

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Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

2014

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Abstract:The mineral ore potential of many mountainous regions of the world, like the Kurdistan region of Iraq, remains unexplored. For logistical and sometimes political reasons, these areas are difficult to map using traditional methods. We highlight the improvement in remote sensing geological mapping that arises from the integration of geomorphic features in classifications. The Mawat Ophiolite Complex (MOC) is located in the NE of Iraq and is known for its mineral deposits. The aims of this study are: (I) to refine the existing lithological map of the MOC; (II) to identify the best discriminatory datasets for lithological classification, including geomorphic features and textures; and (III) to identify potential locations with high concentrations of chromite. 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. The updated map allowed the identification of a new mafic body and a substantial improvement of the geometry of the known lithological units. The use of geomorphic features allowed for the increase of the overall accuracy from 73% to 79.3%. In addition, we detected chromite occurrences within the ophiolite by applying Spectral Angle Mapping (SAM) technique. We identified two new locations having high concentrations of chromite and verified one of these promising areas and has coarsely crystalline chromite within dunite host rock. The chromium (Cr 2 O 3 ) concentration is ~8.46%. The SAM and SVM methods applied on ASTER satellite data show that these can be used as a powerful tool to explore ore deposits and to further improve lithological mapping in mountainous semi-arid regions.

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Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Data Characteristics and Softwarementioning

confidence: 99%

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Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

2014

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“…Multispectral satellite images acquired by remote sensing play a vital role in mapping of lithological formations and have the capability of providing information on the occurrence and distribution of minerals and rocks [1][2][3][4][5][6][7][8]. Satellite data and image processing techniques are used to map ophiolite sequences, chromite potential zones, hydrothermal mineralized zones, carbonates and carbonatite rocks in the arid region of the Sultanate of Oman [1,[9][10][11][12]. Studies using hyperspectral remote sensing data have also been carried out on the Oman ophiolite sequences [13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Recognition of Minerals Using Multispectral Remote Sensing Data: A Case Study in the Sultanate of Oman

Rajendran

Nasir

2015

SQU Journal for Science

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ABSTRACT:The present study demonstrates the capability of a multispectral sensor for the detection of the minerals in the rocks surrounding the Rusayl and Al Jafnayn regions, Sultanate of Oman. The study of spectral absorptions of rocks and minerals in the visible and near infrared (VNIR) and short wavelength infrared (SWIR) spectral bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) using the Spectral Angle Mapper (SAM) supervised image classification technique has provided information on the occurrence of minerals in the rock types of the regions. The study shows the occurrence of carbonate minerals in the limestone formations and of poorly altered silicate minerals in the basic dyke rocks of the study regions. The analysis of minerals over the ancient terraces and recent alluvial deposits show that the deposit materials are derived from the dykes and foliated gabbro source rocks. The image interpretation is compared to the geological map, verified in the field and confirmed through laboratory analyses. The satellite data and the image processing techniques used have potential in the recognition of minerals in the rocks of the study region and could be used in similar arid regions elsewhere in the world.

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Distribution of rocks in Pınarbaşı Ophiolite from central Anatolia (Turkey) based on analysis of ASTER and Landsat‐8 data

et al. 2020

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The Late Cretaceous Pınarbaşı Ophiolite (PO), located at central Turkey is represented by distinct rock types (e.g., harzburgite, dunite, pyroxenite, gabbro) that can be observed in many ophiolites around the world. In this study, the classification of rock types of PO in the Eastern Tauride Belt (Turkey) was made using the advanced spaceborne thermal emission and reflection radiometer and Landsat-8 satellite images. The developed colour-band ratio composite images together with principal component analysis and minimum noise fraction transformations implemented to the remote sensing data efficiently delineate the spatial distribution of pyroxenites, metamorphic sole rocks, and gabbros in the study area. In addition, a body of serpentinized dunites, pyroxenites, metamorphic sole rocks, and listwaenites that has not been recognized before was identified within PO using remote sensing techniques. The promising results of the image processing were verified by detailed field observations and petrographic analysis. The satellite-based remote sensing approaches of this work can be applicable for mapping ophiolitic rock types in PO in particular as well as other ophiolites from similar geographical regions around the world.

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Detection of hydrothermal mineralized zones associated with listwaenites in Central Oman using ASTER data

Cited by 82 publications

References 44 publications

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

Recognition of Minerals Using Multispectral Remote Sensing Data: A Case Study in the Sultanate of Oman

Distribution of rocks in Pınarbaşı Ophiolite from central Anatolia (Turkey) based on analysis of ASTER and Landsat‐8 data

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