Mapping surface mineralogy using imaging spectrometry
Imaging spectrometry, simultaneous measurement of spectra and images in up to hundreds of spectral channels or bands, is a proven technology for identifying and mapping minerals based on their reflectance or emissivity signatures. Also known as hyperspectral imaging or “HSI”, extraction of key spect...
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description | Imaging spectrometry, simultaneous measurement of spectra and images in up to hundreds of spectral channels or bands, is a proven technology for identifying and mapping minerals based on their reflectance or emissivity signatures. Also known as hyperspectral imaging or “HSI”, extraction of key spectral signatures from these data allows direct identification of iron minerals such as hematite, goethite, and jarosite in the visible/near infrared (VNIR); clays, carbonates, micas, sulfates, and other minerals in the short wave infrared (SWIR); and silicates and carbonates in the long wave infrared (LWIR). The unique capability of imaging spectrometry to produce detailed maps of the spatial distribution of specific minerals, mineral assemblages, and mineral variability on the surface of Earth makes it an ideal tool for enhanced geomorphic mapping. Case histories illustrate the use of HSI for characterizing and mapping active and relict geothermal/hydrothermal systems and determining relations between mineralogy and derived landforms. Imaging spectrometry, used in conjunction with complimentary datasets such as InSAR (Interferometric Synthetic Aperture Radar), Light Detection and Ranging (LiDAR), or stereo (photogrammetric-derived) digital elevation models (DEMs), provides a unique means of visualizing the spatial distribution and association of mineralogy with topography, thus contributing to the understanding of the relations between geology and landscape and to improved interpretation of surface geologic processes. |
doi_str_mv | 10.1016/j.geomorph.2010.09.032 |
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Imaging spectrometry, used in conjunction with complimentary datasets such as InSAR (Interferometric Synthetic Aperture Radar), Light Detection and Ranging (LiDAR), or stereo (photogrammetric-derived) digital elevation models (DEMs), provides a unique means of visualizing the spatial distribution and association of mineralogy with topography, thus contributing to the understanding of the relations between geology and landscape and to improved interpretation of surface geologic processes.</description><identifier>ISSN: 0169-555X</identifier><identifier>EISSN: 1872-695X</identifier><identifier>DOI: 10.1016/j.geomorph.2010.09.032</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>3-D geologic visualization ; Applied geophysics ; carbonates ; case studies ; data collection ; digital elevation models ; Earth sciences ; Earth, ocean, space ; Exact sciences and technology ; Geology ; Geomorphology, landform evolution ; goethite ; hematite ; hyperspectral imagery ; Hyperspectral imagery (HSI) ; image analysis ; Imaging ; Imaging spectrometry ; Infrared ; Internal geophysics ; jarosite ; landforms ; landscapes ; lidar ; Mapping ; Marine and continental quaternary ; Mineralogy ; Minerals ; reflectance ; Remote sensing geomorphology ; silicates ; Spectral mineral mapping ; Spectrometry ; Spectroscopy ; sulfates ; Surficial geology ; synthetic aperture radar ; topography</subject><ispartof>Geomorphology (Amsterdam), 2012-01, Vol.137 (1), p.41-56</ispartof><rights>2011 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a454t-23445aa60436a2898e0ca8e28199b9695e1e6cef7526e0c2fa60743d30a7b493</citedby><cites>FETCH-LOGICAL-a454t-23445aa60436a2898e0ca8e28199b9695e1e6cef7526e0c2fa60743d30a7b493</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0169555X11001516$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>309,310,314,776,780,785,786,3537,23909,23910,25118,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=25339963$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Kruse, Fred A.</creatorcontrib><title>Mapping surface mineralogy using imaging spectrometry</title><title>Geomorphology (Amsterdam)</title><description>Imaging spectrometry, simultaneous measurement of spectra and images in up to hundreds of spectral channels or bands, is a proven technology for identifying and mapping minerals based on their reflectance or emissivity signatures. Also known as hyperspectral imaging or “HSI”, extraction of key spectral signatures from these data allows direct identification of iron minerals such as hematite, goethite, and jarosite in the visible/near infrared (VNIR); clays, carbonates, micas, sulfates, and other minerals in the short wave infrared (SWIR); and silicates and carbonates in the long wave infrared (LWIR). The unique capability of imaging spectrometry to produce detailed maps of the spatial distribution of specific minerals, mineral assemblages, and mineral variability on the surface of Earth makes it an ideal tool for enhanced geomorphic mapping. Case histories illustrate the use of HSI for characterizing and mapping active and relict geothermal/hydrothermal systems and determining relations between mineralogy and derived landforms. Imaging spectrometry, used in conjunction with complimentary datasets such as InSAR (Interferometric Synthetic Aperture Radar), Light Detection and Ranging (LiDAR), or stereo (photogrammetric-derived) digital elevation models (DEMs), provides a unique means of visualizing the spatial distribution and association of mineralogy with topography, thus contributing to the understanding of the relations between geology and landscape and to improved interpretation of surface geologic processes.</description><subject>3-D geologic visualization</subject><subject>Applied geophysics</subject><subject>carbonates</subject><subject>case studies</subject><subject>data collection</subject><subject>digital elevation models</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>Geology</subject><subject>Geomorphology, landform evolution</subject><subject>goethite</subject><subject>hematite</subject><subject>hyperspectral imagery</subject><subject>Hyperspectral imagery (HSI)</subject><subject>image analysis</subject><subject>Imaging</subject><subject>Imaging spectrometry</subject><subject>Infrared</subject><subject>Internal geophysics</subject><subject>jarosite</subject><subject>landforms</subject><subject>landscapes</subject><subject>lidar</subject><subject>Mapping</subject><subject>Marine and continental quaternary</subject><subject>Mineralogy</subject><subject>Minerals</subject><subject>reflectance</subject><subject>Remote sensing geomorphology</subject><subject>silicates</subject><subject>Spectral mineral mapping</subject><subject>Spectrometry</subject><subject>Spectroscopy</subject><subject>sulfates</subject><subject>Surficial geology</subject><subject>synthetic aperture 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ocean, space</topic><topic>Exact sciences and technology</topic><topic>Geology</topic><topic>Geomorphology, landform evolution</topic><topic>goethite</topic><topic>hematite</topic><topic>hyperspectral imagery</topic><topic>Hyperspectral imagery (HSI)</topic><topic>image analysis</topic><topic>Imaging</topic><topic>Imaging spectrometry</topic><topic>Infrared</topic><topic>Internal geophysics</topic><topic>jarosite</topic><topic>landforms</topic><topic>landscapes</topic><topic>lidar</topic><topic>Mapping</topic><topic>Marine and continental quaternary</topic><topic>Mineralogy</topic><topic>Minerals</topic><topic>reflectance</topic><topic>Remote sensing geomorphology</topic><topic>silicates</topic><topic>Spectral mineral mapping</topic><topic>Spectrometry</topic><topic>Spectroscopy</topic><topic>sulfates</topic><topic>Surficial geology</topic><topic>synthetic aperture radar</topic><topic>topography</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kruse, Fred A.</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Aqualine</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Geomorphology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kruse, Fred A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mapping surface mineralogy using imaging spectrometry</atitle><jtitle>Geomorphology (Amsterdam)</jtitle><date>2012-01-15</date><risdate>2012</risdate><volume>137</volume><issue>1</issue><spage>41</spage><epage>56</epage><pages>41-56</pages><issn>0169-555X</issn><eissn>1872-695X</eissn><abstract>Imaging spectrometry, simultaneous measurement of spectra and images in up to hundreds of spectral channels or bands, is a proven technology for identifying and mapping minerals based on their reflectance or emissivity signatures. Also known as hyperspectral imaging or “HSI”, extraction of key spectral signatures from these data allows direct identification of iron minerals such as hematite, goethite, and jarosite in the visible/near infrared (VNIR); clays, carbonates, micas, sulfates, and other minerals in the short wave infrared (SWIR); and silicates and carbonates in the long wave infrared (LWIR). The unique capability of imaging spectrometry to produce detailed maps of the spatial distribution of specific minerals, mineral assemblages, and mineral variability on the surface of Earth makes it an ideal tool for enhanced geomorphic mapping. Case histories illustrate the use of HSI for characterizing and mapping active and relict geothermal/hydrothermal systems and determining relations between mineralogy and derived landforms. Imaging spectrometry, used in conjunction with complimentary datasets such as InSAR (Interferometric Synthetic Aperture Radar), Light Detection and Ranging (LiDAR), or stereo (photogrammetric-derived) digital elevation models (DEMs), provides a unique means of visualizing the spatial distribution and association of mineralogy with topography, thus contributing to the understanding of the relations between geology and landscape and to improved interpretation of surface geologic processes.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.geomorph.2010.09.032</doi><tpages>16</tpages></addata></record> |
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subjects | 3-D geologic visualization Applied geophysics carbonates case studies data collection digital elevation models Earth sciences Earth, ocean, space Exact sciences and technology Geology Geomorphology, landform evolution goethite hematite hyperspectral imagery Hyperspectral imagery (HSI) image analysis Imaging Imaging spectrometry Infrared Internal geophysics jarosite landforms landscapes lidar Mapping Marine and continental quaternary Mineralogy Minerals reflectance Remote sensing geomorphology silicates Spectral mineral mapping Spectrometry Spectroscopy sulfates Surficial geology synthetic aperture radar topography |
title | Mapping surface mineralogy using imaging spectrometry |
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