Classification Technique of Algae Using Hyperspectral Images of Algae Culture Media
Increases in algal growth have been reported in rivers, reservoirs, and other water resources worldwide, including Korea. Algal overgrowth can result in algal bloom, which has several negative impacts, such as ecosystem degradation and economic losses. Mitigation measures employed in Korea include a...
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MDPI AG
2023-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/7/4631 |
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| author | Gwang Soo Kim Yeonghwa Gwon Eun Ji Oh Dongsu Kim Jae Hyun Kwon Young Do Kim |
| author_facet | Gwang Soo Kim Yeonghwa Gwon Eun Ji Oh Dongsu Kim Jae Hyun Kwon Young Do Kim |
| author_sort | Gwang Soo Kim |
| collection | DOAJ |
| description | Increases in algal growth have been reported in rivers, reservoirs, and other water resources worldwide, including Korea. Algal overgrowth can result in algal bloom, which has several negative impacts, such as ecosystem degradation and economic losses. Mitigation measures employed in Korea include an algal warning system and survey-based water quality forecast systems. However, these methods are time-consuming and require sample collection from the site. On the other hand, remote sensing techniques that use chlorophyll a are unable to distinguish between different types of algal species. In this paper, we aimed to identify a classification technique based on remote sensing methods that can be used to distinguish between blue-green algae and green algae. We acquired and prepared an algal culture solution and used a hyperspectral sensor to obtain an algae spectrum. Thereafter, we measured the absorption and emission spectra of blue-green and green algae and distinguished them using the instantaneous slope change of the spectrum. The absorption spectra for green algae showed two peaks at 417–437 nm and 661–673 nm, whereas those of blue-green algae showed three peaks at 449–529 nm, 433–437 nm, and 669–677 nm. The results of this study could form a basis for developing mitigation measures for algal overgrowth. |
| first_indexed | 2024-03-11T05:41:56Z |
| format | Article |
| id | doaj.art-76e6e939152740529ef3e59317f9f821 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T05:41:56Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-76e6e939152740529ef3e59317f9f8212023-11-17T16:23:21ZengMDPI AGApplied Sciences2076-34172023-04-01137463110.3390/app13074631Classification Technique of Algae Using Hyperspectral Images of Algae Culture MediaGwang Soo Kim0Yeonghwa Gwon1Eun Ji Oh2Dongsu Kim3Jae Hyun Kwon4Young Do Kim5Department of Civil & Environmental Engineering, Myongji University, Yongin 17058, Republic of KoreaDepartment of Civil & Environmental Engineering, Dankook University, Yongin 16890, Republic of KoreaNakdong River Basin Environmental Office, Changwon 51439, Republic of KoreaDepartment of Civil & Environmental Engineering, Dankook University, Yongin 16890, Republic of KoreaDepartment of Civil and Environmental Engineering, Nakdong River Basin Environmental Research Center, Inje University, Gimhae 50834, Republic of KoreaDepartment of Civil & Environmental Engineering, Myongji University, Yongin 17058, Republic of KoreaIncreases in algal growth have been reported in rivers, reservoirs, and other water resources worldwide, including Korea. Algal overgrowth can result in algal bloom, which has several negative impacts, such as ecosystem degradation and economic losses. Mitigation measures employed in Korea include an algal warning system and survey-based water quality forecast systems. However, these methods are time-consuming and require sample collection from the site. On the other hand, remote sensing techniques that use chlorophyll a are unable to distinguish between different types of algal species. In this paper, we aimed to identify a classification technique based on remote sensing methods that can be used to distinguish between blue-green algae and green algae. We acquired and prepared an algal culture solution and used a hyperspectral sensor to obtain an algae spectrum. Thereafter, we measured the absorption and emission spectra of blue-green and green algae and distinguished them using the instantaneous slope change of the spectrum. The absorption spectra for green algae showed two peaks at 417–437 nm and 661–673 nm, whereas those of blue-green algae showed three peaks at 449–529 nm, 433–437 nm, and 669–677 nm. The results of this study could form a basis for developing mitigation measures for algal overgrowth.https://www.mdpi.com/2076-3417/13/7/4631Chl-aphycocyaninblue-green algaealgae |
| spellingShingle | Gwang Soo Kim Yeonghwa Gwon Eun Ji Oh Dongsu Kim Jae Hyun Kwon Young Do Kim Classification Technique of Algae Using Hyperspectral Images of Algae Culture Media Applied Sciences Chl-a phycocyanin blue-green algae algae |
| title | Classification Technique of Algae Using Hyperspectral Images of Algae Culture Media |
| title_full | Classification Technique of Algae Using Hyperspectral Images of Algae Culture Media |
| title_fullStr | Classification Technique of Algae Using Hyperspectral Images of Algae Culture Media |
| title_full_unstemmed | Classification Technique of Algae Using Hyperspectral Images of Algae Culture Media |
| title_short | Classification Technique of Algae Using Hyperspectral Images of Algae Culture Media |
| title_sort | classification technique of algae using hyperspectral images of algae culture media |
| topic | Chl-a phycocyanin blue-green algae algae |
| url | https://www.mdpi.com/2076-3417/13/7/4631 |
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