High-Resolution Hyperspectral Mineral Mapping: Case Studies in the Edwards Limestone, Texas, USA and Sulfide-Rich Quartz Veins from the Ladakh Batholith, Northern Pakistan
The study of hand samples is a significant aspect of geoscience. This work showcases a technique for relatively quick and inexpensive mineral characterization, applied to a Cretaceous limestone formation and for sulfide-rich quartz vein samples from Northern Pakistan. Spectral feature parameters are...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-10-01
|
| Series: | Minerals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-163X/10/11/967 |
| _version_ | 1797549378584444928 |
|---|---|
| author | Diana Krupnik Shuhab D. Khan |
| author_facet | Diana Krupnik Shuhab D. Khan |
| author_sort | Diana Krupnik |
| collection | DOAJ |
| description | The study of hand samples is a significant aspect of geoscience. This work showcases a technique for relatively quick and inexpensive mineral characterization, applied to a Cretaceous limestone formation and for sulfide-rich quartz vein samples from Northern Pakistan. Spectral feature parameters are derived from mineral mixtures of known abundance and are used for mineral mapping. Additionally, three well-known classification techniques—Spectral Angle Mapper (SAM), Support Vector Machine (SVM), and Neural Network—are compared. Point counting results from petrographic thin sections are used for validation the limestone samples, and QEMSCAN mineral maps for the sulfide samples. For classifying the carbonates, the SVM classifier produced results that are closest to the training set—with 84.4% accuracy and a kappa coefficient of 0.8. For classifying sulfides, SAM produced mineral abundances that were closest to the validation data, possibly due to the low reflectance of sulfides throughout the short-wave infrared spectrum with some differences in the overall spectral shape. |
| first_indexed | 2024-03-10T15:14:48Z |
| format | Article |
| id | doaj.art-5f65fcc8dc694790891da80ba448dd4d |
| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-03-10T15:14:48Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-5f65fcc8dc694790891da80ba448dd4d2023-11-20T19:02:57ZengMDPI AGMinerals2075-163X2020-10-01101196710.3390/min10110967High-Resolution Hyperspectral Mineral Mapping: Case Studies in the Edwards Limestone, Texas, USA and Sulfide-Rich Quartz Veins from the Ladakh Batholith, Northern PakistanDiana Krupnik0Shuhab D. Khan1Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX 77204, USADepartment of Earth and Atmospheric Sciences, University of Houston, Houston, TX 77204, USAThe study of hand samples is a significant aspect of geoscience. This work showcases a technique for relatively quick and inexpensive mineral characterization, applied to a Cretaceous limestone formation and for sulfide-rich quartz vein samples from Northern Pakistan. Spectral feature parameters are derived from mineral mixtures of known abundance and are used for mineral mapping. Additionally, three well-known classification techniques—Spectral Angle Mapper (SAM), Support Vector Machine (SVM), and Neural Network—are compared. Point counting results from petrographic thin sections are used for validation the limestone samples, and QEMSCAN mineral maps for the sulfide samples. For classifying the carbonates, the SVM classifier produced results that are closest to the training set—with 84.4% accuracy and a kappa coefficient of 0.8. For classifying sulfides, SAM produced mineral abundances that were closest to the validation data, possibly due to the low reflectance of sulfides throughout the short-wave infrared spectrum with some differences in the overall spectral shape.https://www.mdpi.com/2075-163X/10/11/967hyperspectral imagingimage classificationcarbonategold mineralization |
| spellingShingle | Diana Krupnik Shuhab D. Khan High-Resolution Hyperspectral Mineral Mapping: Case Studies in the Edwards Limestone, Texas, USA and Sulfide-Rich Quartz Veins from the Ladakh Batholith, Northern Pakistan Minerals hyperspectral imaging image classification carbonate gold mineralization |
| title | High-Resolution Hyperspectral Mineral Mapping: Case Studies in the Edwards Limestone, Texas, USA and Sulfide-Rich Quartz Veins from the Ladakh Batholith, Northern Pakistan |
| title_full | High-Resolution Hyperspectral Mineral Mapping: Case Studies in the Edwards Limestone, Texas, USA and Sulfide-Rich Quartz Veins from the Ladakh Batholith, Northern Pakistan |
| title_fullStr | High-Resolution Hyperspectral Mineral Mapping: Case Studies in the Edwards Limestone, Texas, USA and Sulfide-Rich Quartz Veins from the Ladakh Batholith, Northern Pakistan |
| title_full_unstemmed | High-Resolution Hyperspectral Mineral Mapping: Case Studies in the Edwards Limestone, Texas, USA and Sulfide-Rich Quartz Veins from the Ladakh Batholith, Northern Pakistan |
| title_short | High-Resolution Hyperspectral Mineral Mapping: Case Studies in the Edwards Limestone, Texas, USA and Sulfide-Rich Quartz Veins from the Ladakh Batholith, Northern Pakistan |
| title_sort | high resolution hyperspectral mineral mapping case studies in the edwards limestone texas usa and sulfide rich quartz veins from the ladakh batholith northern pakistan |
| topic | hyperspectral imaging image classification carbonate gold mineralization |
| url | https://www.mdpi.com/2075-163X/10/11/967 |
| work_keys_str_mv | AT dianakrupnik highresolutionhyperspectralmineralmappingcasestudiesintheedwardslimestonetexasusaandsulfiderichquartzveinsfromtheladakhbatholithnorthernpakistan AT shuhabdkhan highresolutionhyperspectralmineralmappingcasestudiesintheedwardslimestonetexasusaandsulfiderichquartzveinsfromtheladakhbatholithnorthernpakistan |