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author:

Wu, Wenting (Wu, Wenting.) [1] | Lin, Zhibin (Lin, Zhibin.) [2] | Chen, Chunpeng (Chen, Chunpeng.) [3] | Chen, Zuoqi (Chen, Zuoqi.) [4] | Zhao, Zhiyuan (Zhao, Zhiyuan.) [5] | Su, Hua (Su, Hua.) [6]

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EI

Abstract:

Tidal wetlands provide a variety of ecosystem services to coastal communities but suffer severe losses due to anthropogenic activities in the Yangtze River Estuary (YRE). However, the detailed dynamics of tidal wetlands have not been well studied with sufficient spatiotemporal resolution. Here, we proposed a rapid classification method that integrates the COntinuous monitoring of Land Disturbance (COLD) algorithm and Median Composite (MC) based on the dense Landsat time series to track the dynamic processes of tidal wetlands in the YRE from 1990 to 2020. The results showed that the COLD-MC demonstrated remarkable effectiveness in detecting the change of tidal wetlands and excellent overall accuracy and kappa coefficient ranging from 90% to 96% and 0.89–0.95, respectively. The overall accuracy of change detection was 97% with an absolute error of 0.4 years. We found that the total area of tidal wetlands experienced a net loss of 59.75 km2 in the YRE, but the gain and loss of the study period were 1556.07 and 1615.82 km2, respectively. Land reclamation, sediment reduction, and Spartina alterniflora invasion pose significant threats to tidal wetlands. Sustainable management could be implemented through the establishment of nature reserves and ecological sediment enhancement engineering projects. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Keyword:

Ecosystems Land reclamation Land use Reclamation Sediments Time series Wetlands

Community:

  • [ 1 ] [Wu, Wenting]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou, China
  • [ 2 ] [Wu, Wenting]State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, China
  • [ 3 ] [Lin, Zhibin]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou, China
  • [ 4 ] [Chen, Chunpeng]State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, China
  • [ 5 ] [Chen, Chunpeng]Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom
  • [ 6 ] [Chen, Zuoqi]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou, China
  • [ 7 ] [Zhao, Zhiyuan]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou, China
  • [ 8 ] [Su, Hua]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou, China

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Source :

International Journal of Digital Earth

ISSN: 1753-8947

Year: 2024

Issue: 1

Volume: 17

3 . 7 0 0

JCR@2023

Cited Count:

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SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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