A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topography
Water depth, a fundamental characteristic of a lake, is important for understanding climatic, ecological, and hydrological processes. However, lake water depth data are still scarce due to the high cost of in-situ measurements and the limitations of remote sensing observations. In this study, a nove...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | International Journal of Digital Earth |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2024.2440443 |
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| author | Yunzhe Lv Li Jia Massimo Menenti Chaolei Zheng Min Jiang Jing Lu Yelong Zeng Qiting Chen Ali Bennour |
| author_facet | Yunzhe Lv Li Jia Massimo Menenti Chaolei Zheng Min Jiang Jing Lu Yelong Zeng Qiting Chen Ali Bennour |
| author_sort | Yunzhe Lv |
| collection | DOAJ |
| description | Water depth, a fundamental characteristic of a lake, is important for understanding climatic, ecological, and hydrological processes. However, lake water depth data are still scarce due to the high cost of in-situ measurements and the limitations of remote sensing observations. In this study, a novel method was developed to estimate time series of pixel-wise water depths of lakes that have ever exposed their bottom by remote sensing observations. Lake water depths were calculated as the difference between the elevations of the dynamic water surface and the historical lakebed elevations using optical images and DEM data. The method was applied in the Sahel-Sudano-Guinean region of Africa where complex climatic conditions and rare in-situ measurements. Experiments showed that the proposed method could get consistent water depths compared with the HydroLAKES data, i.e. with a MAE of 0.86 m and a RMSE of 1.69 m, and water surface elevations similar to the estimates derived from ICESat/ICESat-2 measurements with a MAE of 3.79 m and a RMSE of 5.92 m. The method can provide pixel-wise information on lake water depth at high temporal frequency, and is expected to provide an efficient solution to gather essential information on lakes. |
| format | Article |
| id | doaj-art-697e5619c2c34ee686fea37e0a73e963 |
| institution | OA Journals |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-697e5619c2c34ee686fea37e0a73e9632025-08-20T01:58:20ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552024-12-0117110.1080/17538947.2024.2440443A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topographyYunzhe Lv0Li Jia1Massimo Menenti2Chaolei Zheng3Min Jiang4Jing Lu5Yelong Zeng6Qiting Chen7Ali Bennour8Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaWater depth, a fundamental characteristic of a lake, is important for understanding climatic, ecological, and hydrological processes. However, lake water depth data are still scarce due to the high cost of in-situ measurements and the limitations of remote sensing observations. In this study, a novel method was developed to estimate time series of pixel-wise water depths of lakes that have ever exposed their bottom by remote sensing observations. Lake water depths were calculated as the difference between the elevations of the dynamic water surface and the historical lakebed elevations using optical images and DEM data. The method was applied in the Sahel-Sudano-Guinean region of Africa where complex climatic conditions and rare in-situ measurements. Experiments showed that the proposed method could get consistent water depths compared with the HydroLAKES data, i.e. with a MAE of 0.86 m and a RMSE of 1.69 m, and water surface elevations similar to the estimates derived from ICESat/ICESat-2 measurements with a MAE of 3.79 m and a RMSE of 5.92 m. The method can provide pixel-wise information on lake water depth at high temporal frequency, and is expected to provide an efficient solution to gather essential information on lakes.https://www.tandfonline.com/doi/10.1080/17538947.2024.2440443Lake water depthwater-land boundaryland surface waterwater surface elevation |
| spellingShingle | Yunzhe Lv Li Jia Massimo Menenti Chaolei Zheng Min Jiang Jing Lu Yelong Zeng Qiting Chen Ali Bennour A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topography International Journal of Digital Earth Lake water depth water-land boundary land surface water water surface elevation |
| title | A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topography |
| title_full | A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topography |
| title_fullStr | A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topography |
| title_full_unstemmed | A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topography |
| title_short | A novel remote sensing method to estimate pixel-wise lake water depth using dynamic water-land boundary and lakebed topography |
| title_sort | novel remote sensing method to estimate pixel wise lake water depth using dynamic water land boundary and lakebed topography |
| topic | Lake water depth water-land boundary land surface water water surface elevation |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2024.2440443 |
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