Evaluation of normalization methods applied to Short-Wavelength Infrared (SWIR) spectroscopy mineral databases from multiple instruments and for vectoring analysis exploration
Over the past decade, short-wave infrared (SWIR) spectroscopy has made significant advances in detecting geochemical variations in minerals like white mica, alunite, and chlorite for exploring hydrothermal ore deposits. These variations provide valuable clues, indicating changes in temperature, pH,...
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| Format: | Article |
| Language: | Spanish |
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Universidad Nacional de Colombia
2024-12-01
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| Series: | Boletín de Ciencias de la Tierra |
| Subjects: | |
| Online Access: | https://revistas.unal.edu.co/index.php/rbct/article/view/113445 |
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| _version_ | 1841525257928704000 |
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| author | Juan Camilo Paredes Yan Carlos Trigos Camilo Uribe-Mogollon |
| author_facet | Juan Camilo Paredes Yan Carlos Trigos Camilo Uribe-Mogollon |
| author_sort | Juan Camilo Paredes |
| collection | DOAJ |
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Over the past decade, short-wave infrared (SWIR) spectroscopy has made significant advances in detecting geochemical variations in minerals like white mica, alunite, and chlorite for exploring hydrothermal ore deposits. These variations provide valuable clues, indicating changes in temperature, pH, and fluid oxidation state towards the mineralized center. However, small calibration differences among devices challenge data integration. This study evaluates the 2200 nm Al-OH absorption feature in four white mica SWIR spectroscopy databases collected by TerraSpec™ and OreXpress™ from samples at the Grasshopper porphyry prospect. It evaluates three normalization methodologies: rescaling, mean normalization, and Z-score, yielding p-values for successful data merging of up to 0.75. Findings suggest effective normalization methods across devices, reducing biases from uncalibrated spectrometers. This research offers a methodology to correct SWIR database biases, facilitating accurate data integration across instruments for vectoring analysis.
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| format | Article |
| id | doaj-art-dc94615e5b8d4e5d8523b7abc76c190e |
| institution | Kabale University |
| issn | 0120-3630 2357-3740 |
| language | Spanish |
| publishDate | 2024-12-01 |
| publisher | Universidad Nacional de Colombia |
| record_format | Article |
| series | Boletín de Ciencias de la Tierra |
| spelling | doaj-art-dc94615e5b8d4e5d8523b7abc76c190e2025-01-17T18:35:12ZspaUniversidad Nacional de ColombiaBoletín de Ciencias de la Tierra0120-36302357-37402024-12-015610.15446/rbct.n56.113445Evaluation of normalization methods applied to Short-Wavelength Infrared (SWIR) spectroscopy mineral databases from multiple instruments and for vectoring analysis explorationJuan Camilo Paredes0https://orcid.org/0009-0000-8121-4446Yan Carlos Trigos 1https://orcid.org/0009-0004-1846-8231Camilo Uribe-Mogollon2https://orcid.org/0009-0004-6036-2529Eafit University, Medellín, ColombiaEafit University, Medellín, ColombiaEafit University, Medellín, Colombia Over the past decade, short-wave infrared (SWIR) spectroscopy has made significant advances in detecting geochemical variations in minerals like white mica, alunite, and chlorite for exploring hydrothermal ore deposits. These variations provide valuable clues, indicating changes in temperature, pH, and fluid oxidation state towards the mineralized center. However, small calibration differences among devices challenge data integration. This study evaluates the 2200 nm Al-OH absorption feature in four white mica SWIR spectroscopy databases collected by TerraSpec™ and OreXpress™ from samples at the Grasshopper porphyry prospect. It evaluates three normalization methodologies: rescaling, mean normalization, and Z-score, yielding p-values for successful data merging of up to 0.75. Findings suggest effective normalization methods across devices, reducing biases from uncalibrated spectrometers. This research offers a methodology to correct SWIR database biases, facilitating accurate data integration across instruments for vectoring analysis. https://revistas.unal.edu.co/index.php/rbct/article/view/113445Reflectance spectroscopySWIRWhite micadatabase normalization |
| spellingShingle | Juan Camilo Paredes Yan Carlos Trigos Camilo Uribe-Mogollon Evaluation of normalization methods applied to Short-Wavelength Infrared (SWIR) spectroscopy mineral databases from multiple instruments and for vectoring analysis exploration Boletín de Ciencias de la Tierra Reflectance spectroscopy SWIR White mica database normalization |
| title | Evaluation of normalization methods applied to Short-Wavelength Infrared (SWIR) spectroscopy mineral databases from multiple instruments and for vectoring analysis exploration |
| title_full | Evaluation of normalization methods applied to Short-Wavelength Infrared (SWIR) spectroscopy mineral databases from multiple instruments and for vectoring analysis exploration |
| title_fullStr | Evaluation of normalization methods applied to Short-Wavelength Infrared (SWIR) spectroscopy mineral databases from multiple instruments and for vectoring analysis exploration |
| title_full_unstemmed | Evaluation of normalization methods applied to Short-Wavelength Infrared (SWIR) spectroscopy mineral databases from multiple instruments and for vectoring analysis exploration |
| title_short | Evaluation of normalization methods applied to Short-Wavelength Infrared (SWIR) spectroscopy mineral databases from multiple instruments and for vectoring analysis exploration |
| title_sort | evaluation of normalization methods applied to short wavelength infrared swir spectroscopy mineral databases from multiple instruments and for vectoring analysis exploration |
| topic | Reflectance spectroscopy SWIR White mica database normalization |
| url | https://revistas.unal.edu.co/index.php/rbct/article/view/113445 |
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