中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Automatic Waterline Extraction and Topographic Mapping of Tidal Flats From SAR Images Based on Deep Learning

文献类型:期刊论文

作者Zhang, Shuangshang2,4; Xu, Qing3; Wang, Haoyu2,4; Kang, Yanyan1; Li, Xiaofeng2,4
刊名GEOPHYSICAL RESEARCH LETTERS
出版日期2022-01-28
卷号49期号:2页码:13
ISSN号0094-8276
关键词synthetic aperture radar tidal flat deep learning waterline DEM
DOI10.1029/2021GL096007
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
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.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China
3.Ocean Univ China, Coll Marine Technol, Fac Informat Sci & Engn, Qingdao, Peoples R China
4.Chinese Acad Sci, Ctr Ocean Megasci, 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.

入库方式: OAI收割

来源:海洋研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。