A Knowledge-Based Strategy for Interpretation of SWIR Hyperspectral Images of Rocks
Strategies to interpret short-wave infrared hyperspectral images of rocks involve the application of analysis and classification steps that guide the extraction of geological and mineralogical information with the aim of creating mineral maps. Pre-existing strategies often rely on the use of statist...
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| Published in | Remote sensing (Basel, Switzerland) Vol. 17; no. 15; p. 2555 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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Basel
MDPI AG
23.07.2025
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2072-4292 2072-4292 |
| DOI | 10.3390/rs17152555 |
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| Abstract | Strategies to interpret short-wave infrared hyperspectral images of rocks involve the application of analysis and classification steps that guide the extraction of geological and mineralogical information with the aim of creating mineral maps. Pre-existing strategies often rely on the use of statistical measures between reference and image spectra that are scene dependent. Therefore, classification thresholds based on statistical measures to create mineral maps are also scene dependent. This is problematic because thresholds must be adjusted between images to produce mineral maps of the same accuracy. We developed an innovative, knowledge-based strategy to perform mineralogical analyses and create classifications that overcome this problem by using physics-based wavelength positions of absorption features that are invariant between scenes as the main sources of mineral information. The strategy to interpret short-wave infrared hyperspectral images of rocks is implemented using the open source Hyperspectral Python package (HypPy) and demonstrated on a series of hyperspectral images of hydrothermally altered rock samples. The results show how expert knowledge can be embedded into a standardized processing chain to develop reproducible mineral maps without relying on statistical matching criteria. |
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| AbstractList | Strategies to interpret short-wave infrared hyperspectral images of rocks involve the application of analysis and classification steps that guide the extraction of geological and mineralogical information with the aim of creating mineral maps. Pre-existing strategies often rely on the use of statistical measures between reference and image spectra that are scene dependent. Therefore, classification thresholds based on statistical measures to create mineral maps are also scene dependent. This is problematic because thresholds must be adjusted between images to produce mineral maps of the same accuracy. We developed an innovative, knowledge-based strategy to perform mineralogical analyses and create classifications that overcome this problem by using physics-based wavelength positions of absorption features that are invariant between scenes as the main sources of mineral information. The strategy to interpret short-wave infrared hyperspectral images of rocks is implemented using the open source Hyperspectral Python package (HypPy) and demonstrated on a series of hyperspectral images of hydrothermally altered rock samples. The results show how expert knowledge can be embedded into a standardized processing chain to develop reproducible mineral maps without relying on statistical matching criteria. |
| Author | Hein, Kim A. A. van Ruitenbeek, Frank J. A. Hecker, Christoph A. Bakker, Wim H. van der Werff, Harald M. A. van Eijndthoven, Wijnand |
| Author_xml | – sequence: 1 givenname: Frank J. A. orcidid: 0000-0003-2347-1625 surname: van Ruitenbeek fullname: van Ruitenbeek, Frank J. A. – sequence: 2 givenname: Wim H. orcidid: 0000-0003-0382-7225 surname: Bakker fullname: Bakker, Wim H. – sequence: 3 givenname: Harald M. A. orcidid: 0000-0002-2871-3913 surname: van der Werff fullname: van der Werff, Harald M. A. – sequence: 4 givenname: Christoph A. orcidid: 0000-0001-6802-5042 surname: Hecker fullname: Hecker, Christoph A. – sequence: 5 givenname: Kim A. A. surname: Hein fullname: Hein, Kim A. A. – sequence: 6 givenname: Wijnand surname: van Eijndthoven fullname: van Eijndthoven, Wijnand |
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| SubjectTerms | Algorithms Automation Cameras Classification Geological mapping hyperspectal imaging Hyperspectral imaging Image classification Infrared analysis Infrared imagery interpretation strategy Machine learning Mapping mineral analysis mineral mapping Mineralogy Minerals Python Rocks Short wave radiation short-wave infrared Statistics Thresholds |
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| Title | A Knowledge-Based Strategy for Interpretation of SWIR Hyperspectral Images of Rocks |
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