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

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...

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Published inRemote sensing of environment Vol. 238; no. C; p. 110987
Main Authors Wang, Xinxin, Xiao, Xiangming, Zou, Zhenhua, Chen, Bangqian, Ma, Jun, Dong, Jinwei, Doughty, Russell B., Zhong, Qiaoyan, Qin, Yuanwei, Dai, Shengqi, Li, Xiangping, Zhao, Bin, Li, Bo
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.03.2020
Elsevier BV
Elsevier
Subjects
Algorithms
Biodiversity
Biogeochemical cycles
China
China coastal zone
Cloud computing
Coastal dynamics
Coastal ecosystems
Coastal management
Coastal zone
Coastal zone management
decision support systems
Decision trees
Earth
Ecosystem management
Ecosystem services
Google Earth Engine
image analysis
Image resolution
Internet
Intertidal zone
issues and policy
Landsat
Landsat satellites
littoral zone
Pixel and frequency-based algorithm
Remote sensing
river deltas
Rivers
Satellite imagery
Spatial discrimination
Spatial resolution
Surface water
Tidal flats
Time series Landsat images
Vegetation
Water bodies
Wetlands
Wildlife
Yellow River
China
Yellow River
Pixel and frequency-based algorithm
China coastal zone
Google Earth Engine
Time series Landsat images
Tidal flats
Online AccessGet full text
ISSN0034-4257
1879-0704
1879-0704
DOI10.1016/j.rse.2018.11.030

Cover

Abstract 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. •Mapping tidal flats in China for 1986–2016 using time series Landsat imagery•Spatial distribution of tidal flats in China in 2016•Temporal variations of tidal flats from 1986 to 2016 and its driving factors•Erosion and expansion of tidal flats in the Yellow River and Yangtze River Delta
AbstractList 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.
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.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.
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. •Mapping tidal flats in China for 1986–2016 using time series Landsat imagery•Spatial distribution of tidal flats in China in 2016•Temporal variations of tidal flats from 1986 to 2016 and its driving factors•Erosion and expansion of tidal flats in the Yellow River and Yangtze River Delta
ArticleNumber 110987
Author Wang, Xinxin
Dong, Jinwei
Zou, Zhenhua
Doughty, Russell B.
Chen, Bangqian
Li, Bo
Xiao, Xiangming
Zhong, Qiaoyan
Li, Xiangping
Ma, Jun
Zhao, Bin
Qin, Yuanwei
Dai, Shengqi
AuthorAffiliation b Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA
d Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
a Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
c Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS), Hainan Province 571737, China
AuthorAffiliation_xml – name: b Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA
– name: c Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS), Hainan Province 571737, China
– name: d Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
– name: a Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
Author_xml – sequence: 1
  givenname: Xinxin
  orcidid: 0000-0002-8338-7997
  surname: Wang
  fullname: Wang, Xinxin
  organization: Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
– sequence: 2
  givenname: Xiangming
  orcidid: 0000-0002-1682-0893
  surname: Xiao
  fullname: Xiao, Xiangming
  email: xiangming.xiao@ou.edu
  organization: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA
– sequence: 3
  givenname: Zhenhua
  surname: Zou
  fullname: Zou, Zhenhua
  organization: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA
– sequence: 4
  givenname: Bangqian
  orcidid: 0000-0003-0209-4285
  surname: Chen
  fullname: Chen, Bangqian
  organization: Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS), Hainan Province 571737, China
– sequence: 5
  givenname: Jun
  surname: Ma
  fullname: Ma, Jun
  organization: Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
– sequence: 6
  givenname: Jinwei
  surname: Dong
  fullname: Dong, Jinwei
  organization: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
– sequence: 7
  givenname: Russell B.
  surname: Doughty
  fullname: Doughty, Russell B.
  organization: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA
– sequence: 8
  givenname: Qiaoyan
  surname: Zhong
  fullname: Zhong, Qiaoyan
  organization: Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
– sequence: 9
  givenname: Yuanwei
  surname: Qin
  fullname: Qin, Yuanwei
  organization: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA
– sequence: 10
  givenname: Shengqi
  surname: Dai
  fullname: Dai, Shengqi
  organization: Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
– sequence: 11
  givenname: Xiangping
  orcidid: 0000-0001-5777-6799
  surname: Li
  fullname: Li, Xiangping
  organization: Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
– sequence: 12
  givenname: Bin
  orcidid: 0000-0002-3530-2469
  surname: Zhao
  fullname: Zhao, Bin
  organization: Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
– sequence: 13
  givenname: Bo
  surname: Li
  fullname: Li, Bo
  organization: Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China
BackLink https://www.ncbi.nlm.nih.gov/pubmed/32863440$$D View this record in MEDLINE/PubMed
https://www.osti.gov/biblio/1691977$$D View this record in Osti.gov
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Snippet Tidal flats (non-vegetated area), along with coastal vegetation area, constitute the coastal wetlands (intertidal zone) between high and low water lines, and...
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SubjectTerms Algorithms
Biodiversity
Biogeochemical cycles
China
China coastal zone
Cloud computing
Coastal dynamics
Coastal ecosystems
Coastal management
Coastal zone
Coastal zone management
decision support systems
Decision trees
Earth
Ecosystem management
Ecosystem services
Google Earth Engine
image analysis
Image resolution
Internet
Intertidal zone
issues and policy
Landsat
Landsat satellites
littoral zone
Pixel and frequency-based algorithm
Remote sensing
river deltas
Rivers
Satellite imagery
Spatial discrimination
Spatial resolution
Surface water
Tidal flats
Time series Landsat images
Vegetation
Water bodies
Wetlands
Wildlife
Yellow River
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Title Tracking annual changes of coastal tidal flats in China during 1986–2016 through analyses of Landsat images with Google Earth Engine
URI https://dx.doi.org/10.1016/j.rse.2018.11.030
https://www.ncbi.nlm.nih.gov/pubmed/32863440
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