气候变化领域集成服务门户(CCPortal): Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery

CCPortal

DOI	10.1016/j.rse.2020.112281
	Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery
	Wang Z.; Liu J.; Li J.; Meng Y.; Pokhrel Y.; Zhang H.
发表日期	2021
ISSN	00344257
卷号	255
英文摘要	Extraction of drainage networks is an important element of river flow routing in hydrology and large-scale estimates of river behaviors in Earth sciences. Emerging studies with a focus on greenhouse gases reveal that small rivers can contribute to more than half of the global carbon emissions from inland waters (including lakes and wetlands). However, large-scale extraction of drainage networks is constrained by the coarse resolution of observational data and models, which hinders assessments of terrestrial hydrological and biogeochemical cycles. Recognizing that Sentinel-2 satellite can detect surface water up to a 10-m resolution over large scales, we propose a new method named Remote Sensing Stream Burning (RSSB) to integrate high-resolution observational flow location with coarse topography to improve the extraction of drainage network. In RSSB, satellite-derived input is integrated in a spatially continuous manner, producing a quasi-bathymetry map where relative relief is enforced, enabling a fine-grained, accurate, and multitemporal extraction of drainage network. RSSB was applied to the Lancang-Mekong River basin to derive a 10-m resolution drainage network, with a significant reduction in location errors as validated by the river centerline measurements. The high-resolution extraction resulted in a realistic representation of meanders and detailed network connections. Further, RSSB enabled a multitemporal extraction of river networks during wet/dry seasons and before/after the formation of new channels. The proposed method is fully automated, meaning that the network extraction preserves basin-wide connectivity without requiring any postprocessing, hence facilitating the construction of drainage networks data with openly accessible imagery. The RSSB method provides a basis for the accurate representation of drainage networks that maintains channel connectivity, allows a more realistic inclusion of small rivers and streams, and enables a greater understanding of complex but active exchange between inland water and other related Earth system components. © 2020 The Author(s)
英文关键词	Drainage networks; High-resolution; Remote sensing; River networks; Sentinel-2; Small rivers; Stream burning
语种	英语
scopus关键词	Behavioral research; Biogeochemistry; Catchments; Data mining; Extraction; Greenhouse gases; Remote sensing; Rivers; Topography; Biogeochemical cycle; Drainage networks; Global carbon emission; Mekong river basins; Network connection; Network extractions; Observational data; River flow routing; Drainage
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/178965
作者单位	School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China; Department of Geography, The University of Hong Kong, Hong Kong, SAR, Hong Kong; Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, United States
推荐引用方式 GB/T 7714	Wang Z.,Liu J.,Li J.,et al. Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery[J],2021,255.
APA	Wang Z.,Liu J.,Li J.,Meng Y.,Pokhrel Y.,&Zhang H..(2021).Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery.Remote Sensing of Environment,255.
MLA	Wang Z.,et al."Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery".Remote Sensing of Environment 255(2021).