Comparison of altered mineral information extracted from ETM+, ASTER and Hyperion data in Águas Claras iron ore, Brazil

Huang, Shuang; Chen, Shengbo; Zhang, Yuanzhi

doi:10.1049/iet-ipr.2018.5026

Cited by 7 publications

(5 citation statements)

References 34 publications

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“…Several papers have appeared describing application of ASTER data in the search for iron ore deposits. Using ASTER data alone, or in combination with data from other satellites (Landsat and Hyperion) or airborne geophysics, methods were developed over targets in India, Iran, Brazil, and Australia by Rajendran et al [148], Huang et al [149], Duuring et al [150], Mansouri et al [151], and Mazhari et al [152]. One report by Moghtaderi et al [153] used ASTER and Landsat data to determine iron mineral contamination in an iron mine area in Iran.…”

Section: Aster Data Applied To Exploration For Other Mineralsmentioning

confidence: 99%

Twenty Years of ASTER Contributions to Lithologic Mapping and Mineral Exploration

Abrams

Yamaguchi

2019

Remote Sensing

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The Advanced Spaceborne Thermal Emission and Reflection Radiometer is one of five instruments operating on the National Aeronautics and Space Administration (NASA) Terra platform. Launched in 1999, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) has been acquiring optical data for 20 years. ASTER is a joint project between Japan’s Ministry of Economy, Trade and Industry; and U.S. National Aeronautics and Space Administration. Numerous reports of geologic mapping and mineral exploration applications of ASTER data attest to the unique capabilities of the instrument. Until 2000, Landsat was the instrument of choice to provide surface composition information. Its scanners had two broadband short wave infrared (SWIR) bands and a single thermal infrared band. A single SWIR band amalgamated all diagnostic absorption features in the 2–2.5 micron wavelength region into a single band, providing no information on mineral composition. Clays, carbonates, and sulfates could only be detected as a single group. The single thermal infrared (TIR) band provided no information on silicate composition (felsic vs. mafic igneous rocks; quartz content of sedimentary rocks). Since 2000, all of these mineralogical distinctions, and more, could be accomplished due to ASTER’s unique, high spatial resolution multispectral bands: six in the SWIR and five in the TIR. The data have sufficient information to provide good results using the simplest techniques, like band ratios, or more sophisticated analyses, like machine learning. A robust archive of images facilitated use of the data for global exploration and mapping.

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Section: Aster Data Applied To Exploration For Other Mineralsmentioning

confidence: 99%

Twenty Years of ASTER Contributions to Lithologic Mapping and Mineral Exploration

Abrams

Yamaguchi

2019

Remote Sensing

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“…The fusion of TIR with other high-resolution SWIR datasets can provide insight into understanding different features [4,11,13]. Integrating results from multiple sources, e.g., the Landsat-8, the Sentinel-2, and the ASTER, by a suitable criterion would generally improve the outcome compared to single-source data [14].…”

Section: Introductionmentioning

confidence: 99%

A Fusion of Feature-Oriented Principal Components of Multispectral Data to Map Granite Exposures of Pakistan

et al. 2021

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Despite low spatial resolutions, thermal infrared bands (TIRs) are generally more suitable for mineral mapping due to fundamental tones and high penetration in vegetated areas compared to shortwave infrared (SWIR) bands. However, the weak overtone combinations of SWIR bands for minerals can be compensated by fusing SWIR-bearing data (Sentinel-2 and Landsat-8) with other multispectral data containing fundamental tones from TIR bands. In this paper, marble in a granitic complex in Mardan District (Khyber Pakhtunkhwa) in Pakistan is discriminated by fusing feature-oriented principal component selection (FPCS) obtained from the ASTER, Landsat-8 Operational Land Imager (OLI), Thermal Infrared Sensor (TIRS) and Sentinel-2 MSI data. Cloud computing from Google Earth Engine (GEE) was used to apply FPCS before and after the decorrelation stretching of Landsat-8, ASTER, and Sentinel-2 MSI data containing five (5) bands in the Landsat-8 OLI and TIRS and six (6) bands each in the ASTER and Sentinel-2 MSI datasets, resulting in 34 components (i.e., 2 × 17 components). A weighted linear combination of selected three components was used to map granite and marble. The samples collected during field visits and petrographic analysis confirmed the remote sensing results by revealing the region’s precise contact and extent of marble and granite rock types. The experimental results reflected the theoretical advantages of the proposed approach compared with the conventional stacking of band data for PCA-based fusion. The proposed methodology was also applied to delineate granite deposits in Karoonjhar Mountains, Nagarparker (Sindh province) and the Kotah Dome, Malakand (Khyber Pakhtunkhwa Province) in Pakistan. The paper presents a cost-effective methodology by the fusion of FPCS components for granite/marble mapping during mineral resource estimation. The importance of SWIR-bearing components in fusion represents minor minerals present in granite that could be used to model the engineering properties of the rock mass.

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“…Several authοrs have used data frοm Landsat TM, ETM+ (Sabin, 1999;Abrams et al, 1988) and ASTER (Gad and Kusky, 2007;Safari et al, 2018;Pοur et al, 2019;Küçük Matçı and Avdan, 2019) fοr the explοratiοn οf mineral resοurces and mapping οf geοlοgical fοrmatiοns in the arid and semi-arid zοnes. Many studies have proved the pοtential οf remοte sensing in the mapping οf irοn οre using Landsat (Abrams et al, 1983;Sabins, 1997, Ducart et al, 2016 and ASTER (Rajendran, 2011;Huang et al, 2018;Sengupta et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Discriminatiοn of Irοn Deposits Using Feature Οriented Principal Cοmpοnent Selectiοn and Band Ratiο Methοds: Eastern Taurus /Turkey

Traoré

Çan

Tekin

2020

International Journal of Environment and Geoinformatics

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Comparison of altered mineral information extracted from ETM+, ASTER and Hyperion data in Águas Claras iron ore, Brazil

Cited by 7 publications

References 34 publications

Twenty Years of ASTER Contributions to Lithologic Mapping and Mineral Exploration

Twenty Years of ASTER Contributions to Lithologic Mapping and Mineral Exploration

A Fusion of Feature-Oriented Principal Components of Multispectral Data to Map Granite Exposures of Pakistan

Discriminatiοn of Irοn Deposits Using Feature Οriented Principal Cοmpοnent Selectiοn and Band Ratiο Methοds: Eastern Taurus /Turkey

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