Spatial Component Analysis to Improve Mineral Estimation Using Sentinel-2 Band Ratio: Application to a Greek Bauxite Residue
Remote sensing can be fruitfully used in the characterization of metals within stockpiles and tailings, produced from mining activities. Satellite information, in the form of band ratio, can act as an auxiliary variable, with a certain correlation with the ground primary data. In the presence of thi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Minerals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-163X/11/6/549 |
| _version_ | 1797533217158332416 |
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| author | Roberto Bruno Sara Kasmaeeyazdi Francesco Tinti Emanuele Mandanici Efthymios Balomenos |
| author_facet | Roberto Bruno Sara Kasmaeeyazdi Francesco Tinti Emanuele Mandanici Efthymios Balomenos |
| author_sort | Roberto Bruno |
| collection | DOAJ |
| description | Remote sensing can be fruitfully used in the characterization of metals within stockpiles and tailings, produced from mining activities. Satellite information, in the form of band ratio, can act as an auxiliary variable, with a certain correlation with the ground primary data. In the presence of this auxiliary variable, modeled with nested structures, the spatial components without correlation can be filtered out, so that the useful correlation with ground data grows. This paper investigates the possibility to substitute in a co-kriging system, the whole band ratio information, with only the correlated components. The method has been applied over a bauxite residues case study and presents three estimation alternatives: ordinary kriging, co-kriging, component co-kriging. Results have shown how using the most correlated component reduces the estimation variance and improves the estimation results. In general terms, when a good correlation with ground samples exists, co-kriging of the satellite band-ratio Component improves the reconstruction of mineral grade distribution, thus affecting the selectivity. On the other hand, the use of the components approach exalts the distance variability. |
| first_indexed | 2024-03-10T11:11:25Z |
| format | Article |
| id | doaj.art-8bb02c3e914c418589993423a024a91a |
| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-03-10T11:11:25Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-8bb02c3e914c418589993423a024a91a2023-11-21T20:47:05ZengMDPI AGMinerals2075-163X2021-05-0111654910.3390/min11060549Spatial Component Analysis to Improve Mineral Estimation Using Sentinel-2 Band Ratio: Application to a Greek Bauxite ResidueRoberto Bruno0Sara Kasmaeeyazdi1Francesco Tinti2Emanuele Mandanici3Efthymios Balomenos4Department of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, 40136 Bologna, ItalyDepartment of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, 40136 Bologna, ItalyDepartment of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, 40136 Bologna, ItalyDepartment of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, 40136 Bologna, ItalyMetallurgy Business Unit, MYTILINEOS S.A., Ag. Nikolaos, 320 03 Viotia, GreeceRemote sensing can be fruitfully used in the characterization of metals within stockpiles and tailings, produced from mining activities. Satellite information, in the form of band ratio, can act as an auxiliary variable, with a certain correlation with the ground primary data. In the presence of this auxiliary variable, modeled with nested structures, the spatial components without correlation can be filtered out, so that the useful correlation with ground data grows. This paper investigates the possibility to substitute in a co-kriging system, the whole band ratio information, with only the correlated components. The method has been applied over a bauxite residues case study and presents three estimation alternatives: ordinary kriging, co-kriging, component co-kriging. Results have shown how using the most correlated component reduces the estimation variance and improves the estimation results. In general terms, when a good correlation with ground samples exists, co-kriging of the satellite band-ratio Component improves the reconstruction of mineral grade distribution, thus affecting the selectivity. On the other hand, the use of the components approach exalts the distance variability.https://www.mdpi.com/2075-163X/11/6/549resources characterizationbauxite residuesband ratiokriging of componentmineral grade |
| spellingShingle | Roberto Bruno Sara Kasmaeeyazdi Francesco Tinti Emanuele Mandanici Efthymios Balomenos Spatial Component Analysis to Improve Mineral Estimation Using Sentinel-2 Band Ratio: Application to a Greek Bauxite Residue Minerals resources characterization bauxite residues band ratio kriging of component mineral grade |
| title | Spatial Component Analysis to Improve Mineral Estimation Using Sentinel-2 Band Ratio: Application to a Greek Bauxite Residue |
| title_full | Spatial Component Analysis to Improve Mineral Estimation Using Sentinel-2 Band Ratio: Application to a Greek Bauxite Residue |
| title_fullStr | Spatial Component Analysis to Improve Mineral Estimation Using Sentinel-2 Band Ratio: Application to a Greek Bauxite Residue |
| title_full_unstemmed | Spatial Component Analysis to Improve Mineral Estimation Using Sentinel-2 Band Ratio: Application to a Greek Bauxite Residue |
| title_short | Spatial Component Analysis to Improve Mineral Estimation Using Sentinel-2 Band Ratio: Application to a Greek Bauxite Residue |
| title_sort | spatial component analysis to improve mineral estimation using sentinel 2 band ratio application to a greek bauxite residue |
| topic | resources characterization bauxite residues band ratio kriging of component mineral grade |
| url | https://www.mdpi.com/2075-163X/11/6/549 |
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