Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices
Sun, Shaobo2,3; Zhang, Yonggen2,3; Song, Zhaoliang2,3; Chen, Baozhang4; Zhang, Yangjian5; Yuan, Wenping6; Chen, Chu7; Chen, Wei2,3; Ran, Xiangbin8; Wang, Yidong1
刊名REMOTE SENSING
2020-12-01
卷号12期号:24页码:16
关键词coastal wetlands remote sensing machine learning Google Earth Engine (GEE) SAR random forest
DOI10.3390/rs12244114
通讯作者Song, Zhaoliang(zhaoliang.song@tju.edu.cn)
英文摘要Coastal wetlands provide essential ecosystem services and are closely related to human welfare. However, they can experience substantial degradation, especially in regions in which there is intense human activity. To control these increasingly severe problems and to develop corresponding management policies in coastal wetlands, it is critical to accurately map coastal wetlands. Although remote sensing is the most efficient way to monitor coastal wetlands at a regional scale, it traditionally involves a large amount of work, high cost, and low spatial resolution when mapping coastal wetlands at a large scale. In this study, we developed a workflow for rapidly mapping coastal wetlands at a 10 m spatial resolution, based on the recently emergent Google Earth Engine platform, using a machine learning algorithm, open-access Synthetic Aperture Radar (SAR) and optical images from the Sentinel satellites, and two terrain indices. We then generated a coastal wetland map of the Bohai Rim (BRCW10) based on the workflow. It has a producer accuracy of 82.7%, according to validation using 150 wetland samples. The BRCW10 data reflected finer information when compared to wetland maps derived from two sets of global high-spatial-resolution land cover data, due to the fusion of multiple data sources. The study highlights the benefits of simultaneously merging SAR and optical remote sensing images when mapping coastal wetlands.
资助项目Natural Science Foundation of Tianjin City[20JCQNJC01560] ; National Natural Science Foundation of China[41801061] ; National Natural Science Foundation of China[41930862] ; Peiyang Young Scholar Program of Tianjin University[2020XRG-0066]
WOS关键词LAND RECLAMATION ; CHINA ; CLASSIFICATION ; LAKES
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing
语种英语
出版者MDPI
WOS记录号WOS:000603180100001
资助机构Natural Science Foundation of Tianjin City ; National Natural Science Foundation of China ; Peiyang Young Scholar Program of Tianjin University
内容类型期刊论文
源URL[http://ir.igsnrr.ac.cn/handle/311030/137369]  
专题中国科学院地理科学与资源研究所
通讯作者Song, Zhaoliang
作者单位1.Tianjin Normal Univ, Tianjin Key Lab Water Resources & Environm, Tianjin 300387, Peoples R China
2.Tianjin Univ, Inst Surface Earth Syst Sci, Sch Earth Syst Sci, Tianjin 300072, Peoples R China
3.Tianjin Univ, Tianjin Key Lab Earth Crit Zone Sci & Sustainable, Tianjin 300072, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
6.Sun Yat Sen Univ, Sch Atmospher Sci, Guangdong Prov Key Lab Climate Change & Nat Disas, Zhuhai Key Lab Dynam Urban Climate & Ecol, Zhuhai 510245, Peoples R China
7.Tianjin Inst Surveying & Mapping Co Ltd, Tianjin 300381, Peoples R China
8.Minist Nat Resources, First Inst Oceanog, Res Ctr Marine Ecol, Qingdao 266061, Peoples R China
推荐引用方式
GB/T 7714
Sun, Shaobo,Zhang, Yonggen,Song, Zhaoliang,et al. Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices[J]. REMOTE SENSING,2020,12(24):16.
APA Sun, Shaobo.,Zhang, Yonggen.,Song, Zhaoliang.,Chen, Baozhang.,Zhang, Yangjian.,...&Wang, Yidong.(2020).Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices.REMOTE SENSING,12(24),16.
MLA Sun, Shaobo,et al."Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices".REMOTE SENSING 12.24(2020):16.
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