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Estimation Method of Chlorophyll Concentration Distribution Based on UAV Aerial Images Considering Turbid Water Distribution in a Reservoir
http://hdl.handle.net/10458/0002001144
http://hdl.handle.net/10458/000200114491672921-1648-4488-8759-d12eac775fe1
| 名前 / ファイル | ライセンス | アクション |
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| アイテムタイプ | 学術雑誌論文 / Journal Article(1) | |||||||||||||||
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| 公開日 | 2025-03-31 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | Estimation Method of Chlorophyll Concentration Distribution Based on UAV Aerial Images Considering Turbid Water Distribution in a Reservoir | |||||||||||||||
| 言語 | en | |||||||||||||||
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| 言語 | eng | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | en | |||||||||||||||
| キーワード | algae | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | chlorophyll-a; turbidity | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | reservoir | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | machine learning | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | UAV | |||||||||||||||
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| 言語 | en | |||||||||||||||
| 資源タイプ | ||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||
| アクセス権 | ||||||||||||||||
| アクセス権 | open access | |||||||||||||||
| 著者 |
入江, 光輝
× 入江, 光輝
WEKO
35012
× Manabe, Yugen
× Yamashita, Masafumi
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| 内容記述タイプ | Abstract | |||||||||||||||
| 内容記述 | The observation of the phytoplankton distribution with a high spatiotemporal resolution is necessary to track the nutrient sources that cause algal blooms and to understand their behavior in response to hydraulic phenomena. Photography from UAVs, which has an excellent temporal and spatial resolution, is an effective method to obtain water quality information comprehensively. In this study, we attempted to develop a method for estimating the chlorophyll concentration from aerial images using machine learning that considers brightness correction based on insolation and the spatial distribution of turbidity evaluated by satellite image analysis. The reflectance of harmful algae bloom (HAB) was different from that of phytoplankton seen under normal conditions; so, the images containing HAB were the causes of error in the estimation of the chlorophyll concentration. First, the images when the bloom occurred were extracted by the discrimination with machine learning. Then, the other images were used for the regression of the concentration. Finally, the coefficient of determination between the estimated chlorophyll concentration when no bloom occurred by the image analysis and the observed value reached 0.84. The proposed method enables the detailed depiction of the spatial distribution of the chlorophyll concentration, which contributes to the improvement in water quality management in reservoirs. | |||||||||||||||
| 言語 | en | |||||||||||||||
| 内容記述 | ||||||||||||||||
| 内容記述タイプ | Other | |||||||||||||||
| 内容記述 | Citation: Irie, M.; Manabe, Y.; Yamashita, M. Estimation Method of Chlorophyll Concentration Distribution Based on UAV Aerial Images Considering Turbid Water Distribution in a Reservoir. Drones 2024, 8, 224. https://doi.org/10.3390/drones8060224 | |||||||||||||||
| 言語 | en | |||||||||||||||
| bibliographic_information |
en : Drones 巻 8, 号 6, p. 224, 発行日 2024-05-29 |
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| 出版者 | ||||||||||||||||
| 出版者 | MDPI AG | |||||||||||||||
| 言語 | en | |||||||||||||||
| ISSN | ||||||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||||||
| 収録物識別子 | 2504-446X | |||||||||||||||
| item_10001_relation_14 | ||||||||||||||||
| 関連タイプ | isVersionOf | |||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||
| 関連識別子 | https://doi.org/10.3390/drones8060224 | |||||||||||||||
| 権利 | ||||||||||||||||
| 権利情報 | © 2024 by the authors. | |||||||||||||||
| 言語 | en | |||||||||||||||
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| 出版タイプ | VoR | |||||||||||||||
