An improved global river vector dataset based on multi-source river data fusion
Yesen Liu, Jianhua Wang, Changjun Liu, Yaohuan Huang, Yuanyuan Liu, Jie Liu, Fuxin Chai, Sheng Chen, Min Li, Wei Qu · 2025
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Description
Yesen Liu and co-authors fused three river data sets into a sharper map of the world's rivers, in a 2025 study. Existing global river maps often wander from the real channels. Their framework takes the accurate but broken lines of OpenStreetMap, completes the network with the HydroRIVERS set, and patches gaps with a topology data set. The merged product, GSriver, keeps full river topology while fixing positions.
Checked against a high-precision United States river data set, the fused map beat each parent source by wide margins, improving accuracy by roughly a third to a half depending on the rival. Over forty percent of its points sit within ten meters of the reference. The authors release the data set openly and pitch the recipe as a cheap way to build large river maps from crowdsourced parts, for flood and water research.
Catalog record
| CREATOR | Yesen Liu, Jianhua Wang, Changjun Liu, Yaohuan Huang, Yuanyuan Liu, Jie Liu, Fuxin Chai, Sheng Chen, Min Li, Wei Qu |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 83 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |