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Tracking annual changes of coastal tidal flats in China during 1986-2016 through analyses of Landsat images with Google Earth Engine

文献类型：期刊论文

作者Wang, Xinxin1; Xiao, Xiangming2; Zou, Zhenhua2; Chen, Bangqian3; Ma, Jun1; Dong, Jinwei4; Doughty, Russell B.2; Zhong, Qiaoyan1; Qin, Yuanwei2; Dai, Shengqi1
刊名REMOTE SENSING OF ENVIRONMENT
出版日期2020-03-01
卷号238页码:15
关键词Tidal flats Time series Landsat images Pixel and frequency-based algorithm Google Earth Engine China coastal zone
ISSN号0034-4257
DOI10.1016/j.rse.2018.11.030
通讯作者Xiao, Xiangming(xiangming.xiao@ou.edu)
英文摘要Tidal flats (non-vegetated area), along with coastal vegetation area, constitute the coastal wetlands (intertidal zone) between high and low water lines, and play an important role in wildlife, biodiversity and biogeochemical cycles. However, accurate annual maps of coastal tidal flats over the last few decades are unavailable and their spatio-temporal changes in China are unknown. In this study, we analyzed all the available Landsat TM/ETM +/OLI imagery (-44,528 images) using the Google Earth Engine (GEE) cloud computing platform and a robust decision tree algorithm to generate annual frequency maps of open surface water body and vegetation to produce annual maps of coastal tidal flats in eastern China from 1986 to 2016 at 30-m spatial resolution. The resulting map of coastal tidal flats in 2016 was evaluated using very high-resolution images available in Google Earth. The total area of coastal tidal flats in China in 2016 was about 731,170 ha, mostly distributed in the provinces around Yellow River Delta and Pearl River Delta. The interannual dynamics of coastal tidal flats area in China over the last three decades can be divided into three periods: a stable period during 1986-1992, an increasing period during 1993-2001 and a decreasing period during 2002-2016. The resulting annual coastal tidal flats maps could be used to support sustainable coastal zone management policies that preserve coastal ecosystem services and biodiversity in China.
WOS关键词DIFFERENCE WATER INDEX ; YELLOW-RIVER ; TIME-SERIES ; SATELLITE IMAGES ; SURFACE-WATER ; VEGETATION INDEXES ; CLIMATE-CHANGE ; SEDIMENT LOAD ; CLOUD SHADOW ; MODIS
资助项目National Key Research and Development Program of China[2017YFC1200100] ; Natural Science Foundation of China[41601181] ; Natural Science Foundation of China[41630528] ; Key Research Program of Frontier Sciences[QYZDB-SSW-DQC005] ; Strategic Priority Research Program of Chinese Academy of Sciences (CAS), China[XDA19040301] ; National Institutes of Health[1R01AI10102802A1]
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000523955200021
出版者ELSEVIER SCIENCE INC
资助机构National Key Research and Development Program of China ; Natural Science Foundation of China ; Key Research Program of Frontier Sciences ; Strategic Priority Research Program of Chinese Academy of Sciences (CAS), China ; National Institutes of Health
源URL[http://ir.igsnrr.ac.cn/handle/311030/133822]  
专题中国科学院地理科学与资源研究所
通讯作者Xiao, Xiangming
作者单位1.Fudan Univ, Inst Biodivers Sci, Key Lab Biodivers Sci & Ecol Engn, Minist Educ, Shanghai 200433, Peoples R China
2.Univ Oklahoma, Dept Microbiol & Plant Biol, Ctr Spatial Anal, Norman, OK 73019 USA
3.CATAS, RRI, Haikou 571737, Hainan, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Xinxin,Xiao, Xiangming,Zou, Zhenhua,et al. Tracking annual changes of coastal tidal flats in China during 1986-2016 through analyses of Landsat images with Google Earth Engine[J]. REMOTE SENSING OF ENVIRONMENT,2020,238:15.
APA Wang, Xinxin.,Xiao, Xiangming.,Zou, Zhenhua.,Chen, Bangqian.,Ma, Jun.,...&Li, Bo.(2020).Tracking annual changes of coastal tidal flats in China during 1986-2016 through analyses of Landsat images with Google Earth Engine.REMOTE SENSING OF ENVIRONMENT,238,15.
MLA Wang, Xinxin,et al."Tracking annual changes of coastal tidal flats in China during 1986-2016 through analyses of Landsat images with Google Earth Engine".REMOTE SENSING OF ENVIRONMENT 238(2020):15.

入库方式： OAI收割

来源：地理科学与资源研究所

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