Airborne imaging spectrometer dataset for spectral characterization and predictive mineral mapping using sub-pixel based classifier in parts of Udaipur, Rajasthan, India

Jain, Ronak; Bhu, Harsh; Purohit, Ritesh

doi:10.1016/j.asr.2022.08.032

Cited by 7 publications

(2 citation statements)

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“…The information enhancement processing methods for remote sensing images are used to acquire lithology and tectonic information; these methods include optimal waveband combination, principal component analysis (PCA) and direction filtering, (Honarmand et al, 2013;Shahriari et al, 2013;Xu et al, 2019;Ibrahim et al, 2021;Benaissi et al, 2022). In terms of mineral lithology mapping and alteration information extraction, the construction and improvement of a mineral spectrum library provides the potential for the extraction of the lithology and the alteration information from remote sensing data (Swayze et al, 1993;Wang et al, 2012;Abubakar et al, 2017;Wang et al, 2018;Jain et al, 2024). The main methods used are matched filtering, the spectral area method, the mineral index method, PCA, the band ratio, and machine learning; among these methods, PCA and the band ratio are more widely used in the extraction of etching information (Crosta and Moore, 1989;Rowan et al, 2004;Leverington and Moon, 2012;Pour et al, 2013;Ninomiya and Fu, 2017;Abdolmaleki et al, 2020;Ahmadi and Uygucgil, 2021;Osinowo et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Extracting geological and alteration information and predicting antimony ore based on multisource remote sensing data in Huangyangling, Xinjiang

Wang,

Chen,

Dai

2024

Front. Earth Sci.

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Introduction: China has the world’s largest amount of antimony resources and plays a vital role in the global antimony industry. The Huangyangling area in Xinjiang belongs to the Lazhulong-Huangyangling antimony mineralization belt; this area is rich in antimony ore resources, with potential for discovery of additional ore. This high-elevation mountainous area is located in the northwestern region of the northern Tibetan Plateau, with a harsh natural environment and poor transportation access; thus, the use of traditional geological exploration methods is limited, and remote sensing technology provides unique advantages.Methods: Using Landsat 8 OLI and Gaofen-6 (GF-6) data, we extracted stratigraphic, lithologic and fault information from the study area through information enhancement processing of the images. Based on Landsat 8 OLI, Sentinel-2 and ASTER images and the use of remote sensing image preprocessing and interference information masking, the spectral characteristics of limonite, as well as hydroxyl, carbonate, and silicified alteration minerals were utilized; the characteristics included reflection or absorption in specific spectral bands. The spectral characteristics were then combined with principal component analysis (PCA) and the band ratio method to extract the alteration information for the study area.Results: The stratigraphy and boundaries between stratigraphic and lithologic units extracted in this study were defined, and numerous small faults were identified based on a comparison with 1:250,000 geologic maps. And the overall distribution trends of the indicators of alteration extracted in this study were located along fault zones; additionally, the hydroxyl and carbonate alteration anomalies matched well with known deposits (occurrences). Thus, the alteration information is a good indication of antimony ore bodies. Based on the geological interpretation, alteration information extraction and geochemical exploration data, four prospecting areas were identified.Discussion: The method of extracting geological and hydrothermal alteration information by remote sensing has practical significance because it provides the possibility for geological work and mineral exploration in difficult high-elevation environments.

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Section: Introductionmentioning

confidence: 99%

Extracting geological and alteration information and predicting antimony ore based on multisource remote sensing data in Huangyangling, Xinjiang

Wang,

Chen,

Dai

2024

Front. Earth Sci.

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“…ASTER has a single band centered at 2.33 µm, with a 35 nm bandwidth, therefore preventing the observation of the diagnostic doublet of talc. Hyperspectral remote sensing, also known as imaging spectroscopy, acquires reflectance of materials caused by electronic transitions and vibrational processes in narrow spectral channels of Visible to Near InfraRed (VNIR, 0.3-1.0 µm) and Short Wave InfraRed (SWIR, 1.0-2.5 µm) region spectral range 0.35-2.5 µm, and it facilitates subtle mineralogical identification and mapping [17][18][19][20][21][22]. The wavelength region, 0.3-2.5 µm, is the general spectral range of imaging spectroscopy in earth observation as iron oxides such as hematite, goethite, limonite have absorption in the VNIR region, and carbonates, mica and sulphates have their diagnostic absorption features in the SWIR region [17,19,20,23,24].…”

Section: Introductionmentioning

confidence: 99%

Can Imaging Spectroscopy Divulge the Process Mechanism of Mineralization? Inferences from the Talc Mineralization, Jahazpur, India

et al. 2023

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Talc deposits of Jahazpur, Rajasthan, hosted by dolomite, are one of the largest high-quality talc deposits in India. In the present study, we use AVIRIS-NG datasets to study the link between the spatial pattern of talc mineralization, associated alteration minerals, and iron-oxide enrichment. It is noted that the majority of talc-bearing areas are characterized by the presence of clay minerals, such as an intimate mixture of kaolinite and muscovite, illite, dickite (indicative of phyllic and argillic alteration), and also enhanced iron enrichment. The talc-bearing zones are located adjacent to quartz-rich lithologies, and they are aligned along the Jahazpur thrust. Based on mineralogical and geological evidence, hydrothermal alteration of dolomites by silica and iron-rich fluid is proposed as major factorcontrolling talc mineralization. This study has implications for the identification of prospective zones of talc mineralization using imaging spectroscopy.

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VNIR–SWIR reflectance spectroscopy as a nondestructive technique for compositional determination of archaeological talc samples with a machine learning approach

Ferrer-Julià,

Quirós,

Herrero-Alonso

et al. 2024

Archaeol Anthropol Sci

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The material from which an archaeological piece is made provides a great deal of information regarding the society in which it was made; thus, any misidentification can lead to erroneous conclusions. The uniqueness of many of these pieces hinders their mineralogical analysis because the pieces cannot be damaged for sampling; therefore, errors in the classification of these materials are common. In the present study, we evaluate the suitability of the spectroradiometry technique in the analysis of two archaeological talc pieces. Both came from the Iron Age archaeological site of Peña del Castro (La Ercina, León) in the northwestern Iberian Peninsula. We compared the spectral curves of these 2 pieces with the spectral curves from 50 talc geological samples from different geographical sources, combining bulk and powdered samples. Our results show that spectral curves enabled the identification of the talc material in the powdered and bulk samples. Moreover, the absence of the talc characteristic features in other soft materials also used in antiquity enabled the detection of incorrect identification of the classified pieces. Even though our results cannot be used to define any absorption feature characteristic to establish the provenance of the material, in the present study, spectral analysis has been shown to be suitable as a nondestructive technique to mineralogically identify archaeological pieces.

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Airborne imaging spectrometer dataset for spectral characterization and predictive mineral mapping using sub-pixel based classifier in parts of Udaipur, Rajasthan, India

Cited by 7 publications

References 77 publications

Extracting geological and alteration information and predicting antimony ore based on multisource remote sensing data in Huangyangling, Xinjiang

Extracting geological and alteration information and predicting antimony ore based on multisource remote sensing data in Huangyangling, Xinjiang

Can Imaging Spectroscopy Divulge the Process Mechanism of Mineralization? Inferences from the Talc Mineralization, Jahazpur, India

VNIR–SWIR reflectance spectroscopy as a nondestructive technique for compositional determination of archaeological talc samples with a machine learning approach

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