ArticleScientific data2025
3D-LAKES: Three-Dimensional Global Lake and Reservoir Bathymetry from ICESat-2 Altimetry and Landsat Imagery.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- A global dataset of reservoir in-situ water levels for hydrological and remote sensing applications.Scientific data · 2026Article
- 3D-LAKES: Three-Dimensional Global Lake and Reservoir Bathymetry from ICESat-2 Altimetry and Landsat Imagery.Scientific data · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Quantification of the water storage dynamics in global lakes and reservoirs is pivotal for understanding the roles of surface water in regional climatology, mitigating natural disasters, and preserving ecosystems. However, the ability to accurately comprehend these storage dynamics is significantly hindered by the lack of reliable and cost-effective global bathymetry information. This study introduces the 3D-LAKES dataset, which contains the area-elevation (A-E) relationship and three-dimensional (3D) bathymetry information for 510,530 global lakes and reservoirs, representing 98.9% of global surface water storage capacity. This dataset was validated using 214 A-E relationships and 12 bathymetry maps collected from in-situ measurements, showing strong agreement. The A-E relationships yield an RMSE of 0.60 m, a NRMSE of 0.14, and an R
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Registered trials
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