A directed matched filtering algorithm (DMF) for discriminating hydrothermal alteration zones using the ASTER remote sensing data

Fereydooni, Hosein; Mojeddifar, Saeed

doi:10.1016/j.jag.2017.04.010

Cited by 19 publications

(6 citation statements)

References 19 publications

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“…XRD is an appropriate method that has been used for cross-validation of spectralbased mineral interpretation in many studies [e.g., [6][7][8][9][10][11]. The cross-validated samples de- Comparing the spatial accuracy and threshold value effect on the accuracy of the ASTER mineral map demonstrated that threshold values had a higher impact on reducing the accuracy of the ASTER mineral map.…”

Section: Discussionmentioning

confidence: 99%

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An Approach to Accuracy Assessment of ASTER Derived Mineral Maps

Moud¹,

Ruitenbeek²,

Hewson³

et al. 2021

Remote Sensing

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An accuracy assessment of a classified thematic map is critical for the success of a remote sensing project. The identification and quantification of accuracy sources for classified mineral maps derived from satellite images enable confident decisions to be made for further exploration operations. Nineteen rock samples were collected from the different lithological units of the hydrothermally altered Kuh Panj Cu porphyry occurrence within the south-eastern part of Iran. SPECIM hyperspectral imaging was applied to the rock samples, followed by X-ray diffraction (XRD) analysis to compare the SPECIM mineral maps. The SPECIM results were then interpreted for mineralogy and compositional mapping extracted from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. The spectral angle mapper (SAM) and real value−area (RV−A) fractal methods were applied on SPECIM and ASTER images to interpret the mineralogy and derived classified map products. Two methods, including confusion matrix and one minus standard deviation over mean, were used to assess the accuracy of the classified SPECIM and ASTER derived mineral maps. Performing sensitivity studies were investigated, including the effect of spatially displacing ASTER mineral mapping and changing the SAM-derived threshold values on the accuracy of the ASTER mineral map. The sensitivity analyses demonstrated that selecting an optimum SAM-derived threshold value is more important than spatial displacement. Finally, accuracy sources were summarized in an accuracy budget table. The results demonstrated 89 and 88% accuracy for SPECIM and 88 and 92% accuracy for ASTER mineral maps via the confusion matrix and one minus standard deviation over mean methods, respectively. The accuracy budget helped to evaluate and compare all sources of accuracy with their accuracy values.

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Section: Discussionmentioning

confidence: 99%

“…Many different methods, such as the error matrix, confusion matrix, and Kappa coefficient, are used to assess the accuracy of classified thematic maps. In most mineral exploration studies, the accuracy of mineral maps is derived from or based on, the remote sensing data [6][7][8][9][10][11]. However, they normally…”

Section: Introductionmentioning

confidence: 99%

An Approach to Accuracy Assessment of ASTER Derived Mineral Maps

Moud¹,

Ruitenbeek²,

Hewson³

et al. 2021

Remote Sensing

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“…ASTER has been the workhorse of the geological community for mapping alteration zones [2,3]. It could detect the geological units and broad mineral groups based on their spectral characteristics [4][5][6][7][8][9][10] and has played an important role in mineral exploration [11][12][13][14][15][16]. However, it is difficult to detect talc using the multispectral dataset of ASTER because of the presence of a characteristic absorption feature at 2.31 µm, which overlaps with spectrally similar calcite and dolomite [6].…”

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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“…Crosta et al [36] were the first to utilize PCA and ASTER data to extract alteration data in Patagonia, Argentina. Other researchers later used ASTER data to achieve important achievements in a variety of fields [37][38][39][40][41][42][43][44][45].…”

Section: Introductionmentioning

confidence: 99%

Mapping Hydrothermal Alteration Zones Associated with Copper Mineralization using ASTER Data: A Case Study from the Mirjaveh Area, Southeast Iran

Nasab

Agah

2023

IJE

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In this research, ASTER satellite images and the combined algorithm of band ratios with the method of logical operators with the determination of the threshold limit based on ground, laboratory and experimental studies have been used in order to highlight hydrothermal alterations. Image transformation techniques such as specialized band ratio and principal component analysis are used to map lithologic units and alteration minerals. Supervised classification technique, i.e. Spectral Angle Mapper (SAM) is applied to detect subtle differences between index alteration minerals associated with actual copper localities in the region. The results show that the integration of image transformation techniques and supervised classification of ASTER data with field studies and geochemical exploration is highly effective in targeting new copper mineralization prospects. Copper mineralization is found in siliceous veins that strike from north-south to northeast-southwest across the region. Remote sensing evidence supports the presence of propylitic and argillic alteration, which can be useful for searching for coppergold type deposits. Kaolinite and pyrophyllite play a role in identifying arzilic alteration zones, and muscoite, epidote and chlorite minerals are very important in identifying pyropilitic and phyllic areas and in mineral exploration. Based on remote sensing processing, according to the detection of various alterations (phyllic, pyrophyllite and argillic) in this area, possible copper mineralization was detected in the central part of the studied area. The approach used in this research provides a quick and costeffective means of initiating comprehensive geological and geochemical exploration programs in the study area and elsewhere in similar areas.

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A directed matched filtering algorithm (DMF) for discriminating hydrothermal alteration zones using the ASTER remote sensing data

Cited by 19 publications

References 19 publications

An Approach to Accuracy Assessment of ASTER Derived Mineral Maps

An Approach to Accuracy Assessment of ASTER Derived Mineral Maps

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

Mapping Hydrothermal Alteration Zones Associated with Copper Mineralization using ASTER Data: A Case Study from the Mirjaveh Area, Southeast Iran

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