Automatic Waterline Extraction and Topographic Mapping of Tidal Flats From SAR Images Based on Deep Learning

doi:10.1029/2021GL096007

CORC > 海洋研究所 > 中国科学院海洋研究所 > 海洋环流与波动重点实验室

	Automatic Waterline Extraction and Topographic Mapping of Tidal Flats From SAR Images Based on Deep Learning
	Zhang, Shuangshang 3,4; Xu, Qing 2; Wang, Haoyu 3,4; Kang, Yanyan 1; Li, Xiaofeng 3,4
刊名	GEOPHYSICAL RESEARCH LETTERS
	2022-01-28
卷号	49 期号:2 页码:13
关键词	synthetic aperture radar tidal flat deep learning waterline DEM
ISSN号	0094-8276
DOI	10.1029/2021GL096007
通讯作者	Li, Xiaofeng(lixf@qdio.ac.cn)
英文摘要	This study presented an intuitive approach to derive large-scale tidal flat's Digital Elevation Model (DEM). We first developed an automated method for accurately extracting the waterline from Synthetic Aperture Radar images acquired in Subei Sandbanks along the Yellow Sea coast of China between 2015 and 2020 based on deep convolutional neural networks. The statistical results show this method has appreciable accuracy for efficient waterline extraction even under complex imaging conditions with a mean recall and precision of 0.90 and 0.80, respectively. Then the pixel-level extracted waterlines are calibrated with a global tide model to construct the large-scale tidal flat's DEM in the study region. The comparison against in situ topographic data shows an error of 29 cm, demonstrating the usefulness of monitoring the morpho-sedimentary evolution in intertidal areas. Furthermore, the Subei Sandbanks remained stable from 2015 to 2020, while the coastal region changed drastically due to human activities.
资助项目	Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB42040401] ; Key R&D project of Shandong Province[2019JZZY010102] ; National Natural Science Foundation of China-Shandong Science Foundation[U2006211] ; Key deployment project of Center for Ocean Mega-Science, CAS[COMS2019R02] ; CAS[Y9KY04101 L] ; National Natural Science Foundation of China[41976163]
WOS研究方向	Geology
语种	英语
出版者	AMER GEOPHYSICAL UNION
WOS记录号	WOS:000751642800047
内容类型	期刊论文
源URL	[http://ir.qdio.ac.cn/handle/337002/177990]
专题	海洋研究所_海洋环流与波动重点实验室
通讯作者	Li, Xiaofeng
作者单位	1.Hohai Univ, Coll Oceanog, Nanjing, Peoples R China 2.Ocean Univ China, Coll Marine Technol, Fac Informat Sci & Engn, Qingdao, Peoples R China 3.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao, Peoples R China 4.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Shuangshang,Xu, Qing,Wang, Haoyu,et al. Automatic Waterline Extraction and Topographic Mapping of Tidal Flats From SAR Images Based on Deep Learning[J]. GEOPHYSICAL RESEARCH LETTERS,2022,49(2):13.
APA	Zhang, Shuangshang,Xu, Qing,Wang, Haoyu,Kang, Yanyan,&Li, Xiaofeng.(2022).Automatic Waterline Extraction and Topographic Mapping of Tidal Flats From SAR Images Based on Deep Learning.GEOPHYSICAL RESEARCH LETTERS,49(2),13.
MLA	Zhang, Shuangshang,et al."Automatic Waterline Extraction and Topographic Mapping of Tidal Flats From SAR Images Based on Deep Learning".GEOPHYSICAL RESEARCH LETTERS 49.2(2022):13.