A Novel Spectral Index for Identifying Ferronickel (Fe–Ni) Laterites from Sentinel 2 Satellite Data
Field geological mapping is the initial step of preliminary research in mining. However, in the last decades, the rapid progress of remote sensing data processing and its use for reconnaissance of geological outcrops for the purpose of locating possible mining sites gained increasing attention due t...
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description | Field geological mapping is the initial step of preliminary research in mining. However, in the last decades, the rapid progress of remote sensing data processing and its use for reconnaissance of geological outcrops for the purpose of locating possible mining sites gained increasing attention due to the significant time and cost savings. In this study, a new methodology, focused on mapping ferronickel (Fe–Ni) laterite deposits by using Sentinel-2 satellite data, is introduced. It describes a novel spectral index (called laterite spectral index (LSI)) that enhances laterite surface outcrops. To the best of our knowledge, LSI is the first spectral index tailored for this task, concerning minerals that are simultaneously rich in Fe and Ni. The LSI was applied on a continuum removed image by taking advantage of the spectral features present in two specific spectral areas of 490–560 nm and 842–945 nm. The entire methodology was tested and validated on four different excavation sites in eastern Central Greece based on known drillholes. In all excavation sites, the proposed LSI compared favorably with other relative spectral indices proposed in the literature for the detection of Fe-bearing minerals or Fe-oxides. |
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However, in the last decades, the rapid progress of remote sensing data processing and its use for reconnaissance of geological outcrops for the purpose of locating possible mining sites gained increasing attention due to the significant time and cost savings. In this study, a new methodology, focused on mapping ferronickel (Fe–Ni) laterite deposits by using Sentinel-2 satellite data, is introduced. It describes a novel spectral index (called laterite spectral index (LSI)) that enhances laterite surface outcrops. To the best of our knowledge, LSI is the first spectral index tailored for this task, concerning minerals that are simultaneously rich in Fe and Ni. The LSI was applied on a continuum removed image by taking advantage of the spectral features present in two specific spectral areas of 490–560 nm and 842–945 nm. The entire methodology was tested and validated on four different excavation sites in eastern Central Greece based on known drillholes. In all excavation sites, the proposed LSI compared favorably with other relative spectral indices proposed in the literature for the detection of Fe-bearing minerals or Fe-oxides.</description><subject>Chemistry and Earth Sciences</subject><subject>Computer Science</subject><subject>Data processing</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Excavation</subject><subject>Ferronickel</subject><subject>Fossil Fuels (incl. Carbon Capture)</subject><subject>Geography</subject><subject>Geologic mapping</subject><subject>Geological mapping</subject><subject>Iron</subject><subject>Laterites</subject><subject>Mathematical Modeling and Industrial Mathematics</subject><subject>Mineral Resources</subject><subject>Minerals</subject><subject>Nickel</subject><subject>Original Paper</subject><subject>Outcrops</subject><subject>Physics</subject><subject>Remote sensing</subject><subject>Statistics for Engineering</subject><subject>Sustainable Development</subject><issn>1520-7439</issn><issn>1573-8981</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kL1OwzAUhS0EEqXwAkyWWGAw-Cd27LEqFCpVZSjMlpPYVUqaFNtFdOMdeEOeBJcgsTHde3W-c650ADgn-JpgnN8EQjBnCFOK0s05EgdgQHjOkFSSHO53ilGeMXUMTkJY4WRikg-AHcF592YbuNjYMnrTwGlb2XfoOg-nlW1j7XZ1u4QT633X1uVLQi8n9uvjc15fwZmJ1tfRBuh8t4aLPd8mgsJFUpomSfDWRHMKjpxpgj37nUPwPLl7Gj-g2eP9dDyaoZJmKiJKOa-wcpRkjLHKOZFzrkTmHJOYEyOkI4UoZEYLaoyqcm5ZIblVwhBVVIoNwUWfu_Hd69aGqFfd1rfppaaKSMaExCRRtKdK34XgrdMbX6-N32mC9b5O3depU536p04tkon1ppDgdmn9X_Q_rm8ZmHdc</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Anifadi, A.</creator><creator>Sykioti, O.</creator><creator>Koutroumbas, K.</creator><creator>Vassilakis, E.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>KB.</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><orcidid>https://orcid.org/0000-0003-1301-6450</orcidid><orcidid>https://orcid.org/0000-0002-8480-1539</orcidid><orcidid>https://orcid.org/0000-0002-1175-3628</orcidid><orcidid>https://orcid.org/0000-0001-9476-8464</orcidid></search><sort><creationdate>20220601</creationdate><title>A Novel Spectral Index for Identifying Ferronickel (Fe–Ni) Laterites from Sentinel 2 Satellite Data</title><author>Anifadi, A. ; Sykioti, O. ; Koutroumbas, K. ; Vassilakis, E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c249t-2255d09f214333dff6755964ff38051a68f1b6b842b2aa9d75e3b85e96a19bd93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Chemistry and Earth Sciences</topic><topic>Computer Science</topic><topic>Data processing</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Excavation</topic><topic>Ferronickel</topic><topic>Fossil Fuels (incl. Carbon Capture)</topic><topic>Geography</topic><topic>Geologic mapping</topic><topic>Geological mapping</topic><topic>Iron</topic><topic>Laterites</topic><topic>Mathematical Modeling and Industrial Mathematics</topic><topic>Mineral Resources</topic><topic>Minerals</topic><topic>Nickel</topic><topic>Original Paper</topic><topic>Outcrops</topic><topic>Physics</topic><topic>Remote sensing</topic><topic>Statistics for Engineering</topic><topic>Sustainable Development</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Anifadi, A.</creatorcontrib><creatorcontrib>Sykioti, O.</creatorcontrib><creatorcontrib>Koutroumbas, K.</creatorcontrib><creatorcontrib>Vassilakis, E.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Materials Science Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><jtitle>Natural resources research (New York, N.Y.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Anifadi, A.</au><au>Sykioti, O.</au><au>Koutroumbas, K.</au><au>Vassilakis, E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Novel Spectral Index for Identifying Ferronickel (Fe–Ni) Laterites from Sentinel 2 Satellite Data</atitle><jtitle>Natural resources research (New York, N.Y.)</jtitle><stitle>Nat Resour Res</stitle><date>2022-06-01</date><risdate>2022</risdate><volume>31</volume><issue>3</issue><spage>1203</spage><epage>1224</epage><pages>1203-1224</pages><issn>1520-7439</issn><eissn>1573-8981</eissn><abstract>Field geological mapping is the initial step of preliminary research in mining. 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subjects | Chemistry and Earth Sciences Computer Science Data processing Earth and Environmental Science Earth Sciences Excavation Ferronickel Fossil Fuels (incl. Carbon Capture) Geography Geologic mapping Geological mapping Iron Laterites Mathematical Modeling and Industrial Mathematics Mineral Resources Minerals Nickel Original Paper Outcrops Physics Remote sensing Statistics for Engineering Sustainable Development |
title | A Novel Spectral Index for Identifying Ferronickel (Fe–Ni) Laterites from Sentinel 2 Satellite Data |
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