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...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2024.2440443 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| ISSN: | 1753-8947 1753-8955 |