中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Improved maps of surface water bodies, large dams, reservoirs, and lakes in China

文献类型:期刊论文

作者Wang, Xinxin2,3; Xiao, Xiangming3; Qin, Yuanwei3; Dong, Jinwei1; Wu, Jihua4,5; Li, Bo2,6,7
刊名EARTH SYSTEM SCIENCE DATA
出版日期2022-08-23
卷号14期号:8页码:3757-3771
ISSN号1866-3508
DOI10.5194/essd-14-3757-2022
通讯作者Xiao, Xiangming(xiangming.xiao@ou.edu) ; Li, Bo(bool@fudan.edu.cn)
英文摘要Data and knowledge of surface water bodies (SWB), including large lakes and reservoirs (surface water areas > 1 km(2)), are critical for the management and sustainability of water resources. However, the existing global or national dam datasets have large georeferenced coordinate offsets for many reservoirs, and some datasets have not reported reservoirs and lakes separately. In this study, we generated China's surface water bodies, Large Dams, Reservoirs, and Lakes (China-LDRL) dataset by analyzing all available Landsat imagery in 2019 (19 338 images) in Google Earth Engine and very-high spatial resolution imagery in Google Earth Pro. There were similar to 3.52 x 10(6) yearlong SWB polygons in China for 2019, only 0.01 x 10(6) of them (0.43 %) were of large size (> 1 km(2)). The areas of these large SWB polygons accounted for 83.54 % of the total 214.92 x 10(3) km(2) yearlong surface water area (SWA) in China. We identified 2418 large dams, including 624 off-stream dams and 1794 on-stream dams, 2194 large reservoirs (16.35 x 10(3) km(2)), and 3051 large lakes (73.38 x 10(3) km(2)). In general, most of the dams and reservoirs in China were distributed in South China, East China, and Northeast China, whereas most of lakes were located in West China, the lower Yangtze River basin, and Northeast China. The provision of the reliable, accurate China-LDRL dataset on large reservoirs/dams and lakes will enhance our understanding of water resources management and water security in China. The China-LDRL dataset is publicly available at https://doi.org/10.6084/m9.figshare.16964656.v3 (Wang et al., 2021b).
WOS关键词RESOURCES ; DATABASE ; DATASET ; AREA
资助项目U.S. National Science Foundation[1911955] ; Natural Science Foundation of China[81961128002] ; China Postdoctoral Science Foundation[2021M700835] ; China Postdoctoral Science Foundation[2021TQ0072] ; China Scholarship Council[201906100124]
WOS研究方向Geology ; Meteorology & Atmospheric Sciences
语种英语
出版者COPERNICUS GESELLSCHAFT MBH
WOS记录号WOS:000843213300001
资助机构U.S. National Science Foundation ; Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Scholarship Council
源URL[http://ir.igsnrr.ac.cn/handle/311030/166692]  
专题中国科学院地理科学与资源研究所
通讯作者Xiao, Xiangming; Li, Bo
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
2.Fudan Univ, Sch Life Sci,Key Lab Biodivers Sci & Ecol Engn, Inst Biodivers Sci & Inst Eco Chongming,Minist Ed, Natl Observat & Res Stn Wetland Ecosyst Yangtze E, Shanghai 200438, Peoples R China
3.Univ Oklahoma, Ctr Earth Observat & Modeling, Dept Microbiol & Plant Biol, Norman, OK 73019 USA
4.Lanzhou Univ, State Key Lab Grassland Agroecosyst, Lanzhou 730000, Gansu, Peoples R China
5.Lanzhou Univ, Coll Ecol, Lanzhou 730000, Gansu, Peoples R China
6.Yunnan Univ, Sch Ecol & Environm Sci, Inst Biodivers, Yunnan Key Lab Plant Reprod Adaptat & Evolutionar, Kunming 650504, Yunnan, Peoples R China
7.Yunnan Univ, Sch Ecol & Environm Sci, Inst Biodivers, Ctr Invas Biol, Kunming 650504, Yunnan, Peoples R China
推荐引用方式
GB/T 7714
Wang, Xinxin,Xiao, Xiangming,Qin, Yuanwei,et al. Improved maps of surface water bodies, large dams, reservoirs, and lakes in China[J]. EARTH SYSTEM SCIENCE DATA,2022,14(8):3757-3771.
APA Wang, Xinxin,Xiao, Xiangming,Qin, Yuanwei,Dong, Jinwei,Wu, Jihua,&Li, Bo.(2022).Improved maps of surface water bodies, large dams, reservoirs, and lakes in China.EARTH SYSTEM SCIENCE DATA,14(8),3757-3771.
MLA Wang, Xinxin,et al."Improved maps of surface water bodies, large dams, reservoirs, and lakes in China".EARTH SYSTEM SCIENCE DATA 14.8(2022):3757-3771.

入库方式: OAI收割

来源:地理科学与资源研究所

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