气候变化领域集成服务门户(CCPortal): A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry

CCPortal

DOI	10.1016/j.rse.2020.111831
	A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry
	Li Y.; Gao H.; Zhao G.; Tseng K.-H.
发表日期	2020
ISSN	00344257
卷号	244
英文摘要	Although accurate 3-D reservoir bathymetry is a key input for multiple applications (such as global hydrological models, local water resources related studies, and others), such information is only available for very few locations. To fill this knowledge gap, we generated a 30 m resolution bathymetry dataset for 347 global reservoirs, representing a total volume of 3123 km3 (50% of the global reservoir capacity). First, Area–Elevation (A–E) relationships for the identified reservoirs were derived by combining altimetry data from multiple satellites with Landsat imagery data. Next, the resulting A–E relationships were applied to the Surface Water Occurrence (SWO) data from the JRC Global Surface Water (GSW) dataset to obtain bathymetry values for the dynamic areas of the reservoirs. Lastly, an extrapolation method was adopted to help achieve the full bathymetry dataset. The remotely sensed bathymetry results were primarily validated against the following: (1) They were validated against Area–Elevation (A–E) and Elevation–Volume (E-V) relationships derived from the in situ elevations and volumes for 16 reservoirs, with root-mean-square error (RMSE) values of elevation from 0.06 m to 1.99 m, and normalized RMSE values of storage from 0.56% to 4.40%. (2) They were also validated against survey bathymetric maps for four reservoirs, with R2 values from 0.82 to 0.99 and RMSE values from 0.13 m to 2.31 m. The projected portions have relatively large errors and uncertainties (compared to the remotely sensed portions) because the extrapolated elevations cannot fully capture the underwater topography. Overall, this approach performs better for reservoirs with a large dynamic area fractions. It can also be applied to small reservoirs (e.g., reservoirs with surface areas of a few square kilometers or less), where ICESat observations are available, and to large natural lakes. With the contribution of ICESat-2, this dataset has the potential to be expanded to thousands of reservoirs and lakes in the future. © 2020 Elsevier Inc.
英文关键词	Bathymetry; DEM; Global reservoirs; ICESat-2/ATLAS; ICESat/GLAS; Landsat; Radar altimetry
语种	英语
scopus关键词	Bathymetry; Digital storage; Extrapolation; Hydrographic surveys; Lakes; Maps; Mean square error; Remote sensing; Satellite imagery; Three dimensional computer graphics; Topography; Extrapolation methods; High resolution bathymetry; Hydrological models; Multi-source satellite imagery; Multiple applications; Multiple satellites; Root mean square errors; Underwater topographies; Reservoirs (water); bathymetry; data set; global change; ICESat; Landsat; satellite altimetry; satellite data; satellite imagery; spectral resolution
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179319
作者单位	Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX, United States; Center for Space and Remote Sensing Research, National Central University, Taoyuan, Taiwan; Institute of Hydrological and Oceanic Sciences, National Central University, Taoyuan, Taiwan
推荐引用方式 GB/T 7714	Li Y.,Gao H.,Zhao G.,et al. A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry[J],2020,244.
APA	Li Y.,Gao H.,Zhao G.,&Tseng K.-H..(2020).A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry.Remote Sensing of Environment,244.
MLA	Li Y.,et al."A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry".Remote Sensing of Environment 244(2020).