Unmixing of hyperspectral data for mineral detection using a hybrid method, Sar Chah-e Shur, Iran

Moghadam, Hadi Jamshid; Oskouei, Majid Mohammady; Nouri, Tohid

doi:10.1007/s12517-020-06070-7

Cited by 9 publications

(2 citation statements)

References 66 publications

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“…For this reason, implementing column mean adjustments in the Minimum Noise Fraction (MNF) space technique has been proposed as a solution to mitigate this issue. The MNF adjustment method is especially noteworthy for its effective noise reduction capabilities, making it a suitable approach for correcting the smile effect, as employed in this study [35].…”

Section: Pre-processingmentioning

confidence: 99%

“…Despite appearing minor, these shifts, ranging from 2.6 to 3.6 nm in the visible and near-infrared (VNIR) range and approximately 1 nm in the short-wave infrared (SWIR) range, can significantly impact the diagnostic absorption and reflection. Hence, addressing the spectral smile effect is crucial when interpreting hyperspectral imagery data, particularly in applications involving mineral identification and other detailed spectral analyses [35,36]. For this reason, implementing column mean adjustments in the Minimum Noise Fraction (MNF) space technique has been proposed as a solution to mitigate this issue.…”

Section: Pre-processingmentioning

confidence: 99%

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PRISMA Hyperspectral Remote Sensing Data for Mapping Alteration Minerals in Sar-e-Châh-e-Shur Region, Birjand, Iran

Habashi,

Jamshid Moghadam,

Mohammady Oskouei

et al. 2024

Remote Sensing

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Remote sensing satellite imagery consistently provides valuable and frequent information, enabling the exploration of mineral resources across immense, remote and harsh domains. Recent developments in spaceborne hyperspectral remote sensing have opened avenues to support diverse remote sensing applications, particularly in the realm of mineral exploration. This study evaluates the capabilities of the PRecursore IperSpettrale della Missione Applicativa (PRISMA) hyperspectral satellite data for mapping alteration minerals using the Matched Filtering Unmixing (MFU) approach in the Sar-e-châh-e-shur, Birjand, Iran. Minerals such as richterite, augite, psilomelane, ilmenite, kaolinite, smectite, mirabilite, muscovite, and chlorite were identified using the vertex component analysis (VCA) technique. Subsequently, alteration mineral maps of the study area were generated using a matched filtering technique. Additionally, through the integration of X-ray diffraction (XRD) analysis, thin section examination, geochemical study of stream sediments, and interpretation of geological maps, potential alteration mineralization zones were delineated in the study area. Ultimately, the validation process, which included comparing the maps with the findings derived from the PRISMA remote sensing study, was conducted using the normal score equation. Thus, our results yielded a normalized score of 3.42 out of 4, signifying an 85.71% agreement with the regional geological characteristics of the study area. The results of this investigation highlight the substantial potential of the PRISMA dataset for systematic alteration mineral mapping and consequent exploration of ore minerals, specifically in challenging and inaccessible terrains.

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Section: Pre-processingmentioning

confidence: 99%

Section: Pre-processingmentioning

confidence: 99%