Selection of Landsat-8 Operational Land Imager (OLI) Optimal Band Combinations for Mapping Alteration Zones
In typical alteration extraction methods, e.g., band math and principal component analysis (PCA), the bands or band combinations unitized to extract altered minerals are usually selected based on empirical models or previous rules. This results in significant differences in the alteration of mineral...
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MDPI AG
2024-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/2/392 |
| _version_ | 1797342558461886464 |
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| author | Chen Yang Hekun Jia Lifang Dong Haishi Zhao Minghao Zhao |
| author_facet | Chen Yang Hekun Jia Lifang Dong Haishi Zhao Minghao Zhao |
| author_sort | Chen Yang |
| collection | DOAJ |
| description | In typical alteration extraction methods, e.g., band math and principal component analysis (PCA), the bands or band combinations unitized to extract altered minerals are usually selected based on empirical models or previous rules. This results in significant differences in the alteration of mineral mapping even in the same area, thus greatly increasing the uncertainty of mineral resource prediction. In this paper, an intelligent alteration extraction approach was proposed in which an optimization algorithm, i.e., a genetic algorithm (GA), was introduced into the PCA; this approach is termed GA-PCA and is used for selecting the optimized band combinations of mineralized alterations. The proposed GA-PCA was employed to map iron oxides and hydroxyl minerals using the most commonly adopted multispectral data, i.e., Landsat-8 OLI data, at the Lalingzaohuo polymetallic deposits, China. The results showed that the spectral characteristics of GA-PCA-selected OLI band combinations in the research area were beneficial for enhancing alteration information and were more capable of suppressing the interference of vegetation information. The mapping alteration zones using the GA-PCA approach had a higher agreement with known ore spots, i.e., 25% and 33.3% in ferrous-bearing and hydroxyl-bearing deposits, compared to the classical PCA. Furthermore, two predicted targets (not shown in the classical PCA results) were precisely obtained via analyzing the GA-PCA alteration maps combined with the ore-forming geological conditions of the mine and its tectonic characteristics. This indicated that the intelligent selection of mineral alteration band combinations increased the reliability of remote sensing-based mineral exploration. |
| first_indexed | 2024-03-08T10:35:03Z |
| format | Article |
| id | doaj.art-0903efd34a504b6a83bc3d0f45ef6d15 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-08T10:35:03Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj.art-0903efd34a504b6a83bc3d0f45ef6d152024-01-26T18:19:49ZengMDPI AGRemote Sensing2072-42922024-01-0116239210.3390/rs16020392Selection of Landsat-8 Operational Land Imager (OLI) Optimal Band Combinations for Mapping Alteration ZonesChen Yang0Hekun Jia1Lifang Dong2Haishi Zhao3Minghao Zhao4College of Earth Sciences, Jilin University, Changchun 130061, ChinaCollege of Earth Sciences, Jilin University, Changchun 130061, ChinaCollege of Earth Sciences, Jilin University, Changchun 130061, ChinaCollege of Computer Science and Technology, Jilin University, Changchun 130012, ChinaCollege of Earth Sciences, Jilin University, Changchun 130061, ChinaIn typical alteration extraction methods, e.g., band math and principal component analysis (PCA), the bands or band combinations unitized to extract altered minerals are usually selected based on empirical models or previous rules. This results in significant differences in the alteration of mineral mapping even in the same area, thus greatly increasing the uncertainty of mineral resource prediction. In this paper, an intelligent alteration extraction approach was proposed in which an optimization algorithm, i.e., a genetic algorithm (GA), was introduced into the PCA; this approach is termed GA-PCA and is used for selecting the optimized band combinations of mineralized alterations. The proposed GA-PCA was employed to map iron oxides and hydroxyl minerals using the most commonly adopted multispectral data, i.e., Landsat-8 OLI data, at the Lalingzaohuo polymetallic deposits, China. The results showed that the spectral characteristics of GA-PCA-selected OLI band combinations in the research area were beneficial for enhancing alteration information and were more capable of suppressing the interference of vegetation information. The mapping alteration zones using the GA-PCA approach had a higher agreement with known ore spots, i.e., 25% and 33.3% in ferrous-bearing and hydroxyl-bearing deposits, compared to the classical PCA. Furthermore, two predicted targets (not shown in the classical PCA results) were precisely obtained via analyzing the GA-PCA alteration maps combined with the ore-forming geological conditions of the mine and its tectonic characteristics. This indicated that the intelligent selection of mineral alteration band combinations increased the reliability of remote sensing-based mineral exploration.https://www.mdpi.com/2072-4292/16/2/392alteration zone mappingLandsat-8 OLIoptimized band combinationsprincipal component analysisgenetic algorithm |
| spellingShingle | Chen Yang Hekun Jia Lifang Dong Haishi Zhao Minghao Zhao Selection of Landsat-8 Operational Land Imager (OLI) Optimal Band Combinations for Mapping Alteration Zones Remote Sensing alteration zone mapping Landsat-8 OLI optimized band combinations principal component analysis genetic algorithm |
| title | Selection of Landsat-8 Operational Land Imager (OLI) Optimal Band Combinations for Mapping Alteration Zones |
| title_full | Selection of Landsat-8 Operational Land Imager (OLI) Optimal Band Combinations for Mapping Alteration Zones |
| title_fullStr | Selection of Landsat-8 Operational Land Imager (OLI) Optimal Band Combinations for Mapping Alteration Zones |
| title_full_unstemmed | Selection of Landsat-8 Operational Land Imager (OLI) Optimal Band Combinations for Mapping Alteration Zones |
| title_short | Selection of Landsat-8 Operational Land Imager (OLI) Optimal Band Combinations for Mapping Alteration Zones |
| title_sort | selection of landsat 8 operational land imager oli optimal band combinations for mapping alteration zones |
| topic | alteration zone mapping Landsat-8 OLI optimized band combinations principal component analysis genetic algorithm |
| url | https://www.mdpi.com/2072-4292/16/2/392 |
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