Spectral characterization and ASTER-based lithological mapping of an ophiolite complex: A case study from Neyriz ophiolite, SW Iran

Tangestani, Majid H.; Jaffari, Laleh; Vincent, Robert K.; Sridhar, B. B. Maruthi

doi:10.1016/j.rse.2011.04.023

Cited by 69 publications

(35 citation statements)

References 26 publications

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“…The clastic and carbonite rock curves show similarity with the curves provided by Rowan and Mars [110] and Tangestani et al [22], but in our curves the band 12 has more emissivity than both curves. The mafic and ultramafic rocks curves have less emissivity in band number 10 and 11 compared to the curves provided by Tangestani et al [22], and Yajima and Yamaguchi [19]. Water curves show less emissivity in band number 10 compared to the curves provided by Lammoglia et al [111] ( Figure 5).…”

Section: Discussionsupporting

confidence: 86%

“…The temperature curve's behavior of valley fill sediments is similar to the emissivity curve of dark sand provided by Schmugge [109]. The clastic and carbonite rock curves show similarity with the curves provided by Rowan and Mars [110] and Tangestani et al [22], but in our curves the band 12 has more emissivity than both curves. The mafic and ultramafic rocks curves have less emissivity in band number 10 and 11 compared to the curves provided by Tangestani et al [22], and Yajima and Yamaguchi [19].…”

Section: Discussionsupporting

confidence: 85%

“…We used ATCOR-3 model, which is available in PCI Geomatica 10.1, to remove or reduce the effects of rugged terrain areas illuminated under low local solar elevation angles. ATCOR requires a description of the components in the atmospheric profile [22]. ATCOR3 was used to perform the initial atmospheric correction using 40 km initial visibility, ''Rural'' atmospheric definition, for "Mid-Latitude summer".…”

Section: Atmospheric Correctionsmentioning

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: Discussionsupporting

confidence: 86%

Section: Discussionsupporting

confidence: 85%

Section: Atmospheric Correctionsmentioning

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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“…The algorithm considers only the major pixel components; therefore, sub-pixel abundances, i.e., mixtures, cannot be detected (hard classification). As it takes specific absorption features, not the shape of the overall spectra, and the reference spectrum is scaled so as to match to that of the image pixel, SFF is sensitive to subtle absorption features of the end-members given the accurate reference spectrum [62,63]. Thus, SFF benefits from application of continuum removal over narrower wavelength ranges that cover diagnostic absorption features.…”

Section: Hyperspectral Image Classificationmentioning

confidence: 99%

Ground-Based Hyperspectral Image Analysis of the Lower Mississippian (Osagean) Reeds Spring Formation Rocks in Southwestern Missouri

et al. 2016

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Abstract:Ground-based hyperspectral imaging is fairly new for studying near-vertical rock exposures where airborne or satellite-based imaging fail to provide useful information. In this study, ground-based hyperspectral image analysis was performed on a roadcut, where diagenetic tripolite facies is observed in southwestern Missouri. Laboratory-based reflectance spectroscopy and hyperspectral image analyses were also performed on collected samples. Image classification was performed using Spectral Feature Fitting (SFF) and Mixture-tuned Match Filtering (MTMF) with laboratory-and image-derived end-member spectra. SFF provided thorough yet detailed classification, whereas MTMF provided information on the relative abundances of the lithologies. Ground-based hyperspectral imaging demonstrated its potential to aid geological studies providing valuable information on mineralogical and lithological variations rapidly and with two-dimensional continuity in inaccessible rock faces of near-vertical outcrops. The results showed decreasing tripolite abundance going downward in the investigated vertical succession. Also, a leaching pattern has been observed such that persistent and continuous limestone layers become lenses and patches towards the upper portion of the outcrop. These observations show that the effect of tripolitization decreases when going deeper in the succession, suggesting that the fluid responsible for the weathering of siliceous precursors may have been flowing from top to bottom and thus have had a meteoric origin.

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“…The technique is widely used in regions which have extremely rugged topography where it is difficult to do dense sampling and detailed conventional geological mapping. 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].…”

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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Spectral characterization and ASTER-based lithological mapping of an ophiolite complex: A case study from Neyriz ophiolite, SW Iran

Cited by 69 publications

References 26 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)

Ground-Based Hyperspectral Image Analysis of the Lower Mississippian (Osagean) Reeds Spring Formation Rocks in Southwestern Missouri

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

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