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An improved global river vector dataset based on multi-source river data fusion

文献类型：期刊论文

作者Liu, Yesen3; Wang, Jianhua3; Liu, Changjun3; Huang, Yaohuan1,2; Liu, Yuanyuan3,4; Liu, Jie3; Chai, Fuxin3,4; Chen, Sheng3; Li, Min3; Qu, Wei3
刊名SCIENTIFIC DATA
出版日期2025-12-12
卷号13期号:1页码:88
DOI10.1038/s41597-025-06399-2
产权排序2
文献子类Article
英文摘要High-precision global river datasets are crucial for hydrology and environmental research. Although several global river datasets have been developed and widely adopted, they often suffer from significant deviations from actual river distributions in many areas. In this study, we propose a multi-source vector river data fusion framework to generate a high spatial accuracy global river dataset with topological information, named GSriver. By integrating high-spatial-resolution but topologically incomplete OpenStreetMap (OSM) waterways with HydroRIVERS and supplementing missing segments with the Global River Topology (GRIT) dataset, GSriver preserves complete river topology while significantly enhancing spatial accuracy. Validation against the high-precision NHDPlus dataset of the United States reveals that GSriver improves spatial accuracy over MERIT, GRIT, and HydroRIVERS by 36.3%, 40.7%, and 56.7%, respectively. More than 40% of nodes in GSriver deviate less than 10 meters from NHDPlus. This approach addresses the spatial accuracy limitations of conventional DEM-derived river datasets by leveraging the advantages of crowdsourced data, offering a scalable and cost-effective solution for constructing large-scale river datasets. GSriver is publicly available at https://doi.org/10.6084/m9.figshare.30119851.v31.
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WOS研究方向Science & Technology - Other Topics
语种英语
WOS记录号WOS:001667673400002
出版者NATURE PORTFOLIO
源URL[http://ir.igsnrr.ac.cn/handle/311030/219752]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Huang, Yaohuan
作者单位1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China;
2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;
3.China Inst Water Resources & Hydropower Res, State Key Lab Water Cycle & Water Secur, Beijing 100038, Peoples R China;
4.Minist Water Resources, China Key Lab River Basin Digital Twinning, Beijing 100038, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Yesen,Wang, Jianhua,Liu, Changjun,et al. An improved global river vector dataset based on multi-source river data fusion[J]. SCIENTIFIC DATA,2025,13(1):88.
APA Liu, Yesen.,Wang, Jianhua.,Liu, Changjun.,Huang, Yaohuan.,Liu, Yuanyuan.,...&Qu, Wei.(2025).An improved global river vector dataset based on multi-source river data fusion.SCIENTIFIC DATA,13(1),88.
MLA Liu, Yesen,et al."An improved global river vector dataset based on multi-source river data fusion".SCIENTIFIC DATA 13.1(2025):88.

入库方式： OAI收割

来源：地理科学与资源研究所

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