IOCAS-IR  > 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, Shuangshang1,2; Xu, Qing3; Wang, Haoyu1,2; Kang, Yanyan4; Li, Xiaofeng1,2
2022-01-28
发表期刊GEOPHYSICAL RESEARCH LETTERS
ISSN0094-8276
卷号49期号:2页码:13
通讯作者Li, Xiaofeng(lixf@qdio.ac.cn)
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.
关键词synthetic aperture radar tidal flat deep learning waterline DEM
DOI10.1029/2021GL096007
收录类别SCI
语种英语
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
WOS类目Geosciences, Multidisciplinary
WOS记录号WOS:000751642800047
出版者AMER GEOPHYSICAL UNION
引用统计
被引频次:20[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.qdio.ac.cn/handle/337002/177991
专题海洋环流与波动重点实验室
通讯作者Li, Xiaofeng
作者单位1.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China
2.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao, Peoples R China
3.Ocean Univ China, Coll Marine Technol, Fac Informat Sci & Engn, Qingdao, Peoples R China
4.Hohai Univ, Coll Oceanog, Nanjing, Peoples R China
第一作者单位海洋环流与波动重点实验室;  中国科学院海洋大科学研究中心
通讯作者单位海洋环流与波动重点实验室;  中国科学院海洋大科学研究中心
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.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Geophysical Research(5243KB)期刊论文出版稿限制开放CC BY-NC-SA浏览
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Zhang, Shuangshang]的文章
[Xu, Qing]的文章
[Wang, Haoyu]的文章
百度学术
百度学术中相似的文章
[Zhang, Shuangshang]的文章
[Xu, Qing]的文章
[Wang, Haoyu]的文章
必应学术
必应学术中相似的文章
[Zhang, Shuangshang]的文章
[Xu, Qing]的文章
[Wang, Haoyu]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Geophysical Research Letters - 2022 - Zhang - Automatic Waterline Extraction and Topographic Mapping of Tidal Flats From.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

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。