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author:

Gan, Z. (Gan, Z..) [1] | Guo, S. (Guo, S..) [2] | Chen, C. (Chen, C..) [3] | Zheng, H. (Zheng, H..) [4] | Hu, Y. (Hu, Y..) [5] | Su, H. (Su, H..) [6] | Wu, W. (Wu, W..) [7]

Indexed by:

Scopus

Abstract:

Tidal flats in northern China are essential parts of the East Asian-Australasian Flyway, the densest pathway for migratory waterbirds, and are of great ecological and economic importance. They are threatened by human activities and climate change, raising the urgency surrounding tracking the spatiotemporal dynamics of tidal flats. However, there is no cost-effective way to map morphological changes on a large spatial scale due to the inaccessibility of the mudflats. In this study, we proposed a pixel-based multi-indices tidal flat mapping algorithm that precisely characterizes 2D/3D morphological changes in tidal flats in northern China using time-series remote sensing data. An overall accuracy of 0.95 in delineating tidal flats to a 2D extent was achieved, with 11,716 verification points. Our results demonstrate that the reduction in sediment discharge from rivers along the coastlines of the Yellow and Bohai Seas has resulted in an overall decline in the area of tidal flats, from 4856.40 km2 to 4778.32 km2. Specifically, 3D analysis showed that significant losses were observed in the mid-to-high-tidal flat zones, while low-elevation tidal flats experienced an increase in area due to the transformations in mid-to-high-tidal flats. Our results indicate that the sediment inputs from rivers and the succession of native vegetation are the primary drivers leading to 2D/3D morphological changes of tidal flats following the cessation of extensive land reclamation in northern China. © 2024 by the authors.

Keyword:

2D/3D morphological changes remote sensing tidal flats time series Yellow and Bohai Seas

Community:

  • [ 1 ] [Gan Z.]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, 350108, China
  • [ 2 ] [Guo S.]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, 350108, China
  • [ 3 ] [Chen C.]State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200050, China
  • [ 4 ] [Chen C.]Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, United Kingdom
  • [ 5 ] [Zheng H.]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, 350108, China
  • [ 6 ] [Hu Y.]State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200050, China
  • [ 7 ] [Su H.]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, 350108, China
  • [ 8 ] [Wu W.]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, 350108, China
  • [ 9 ] [Wu W.]State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200050, China

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Source :

Remote Sensing

ISSN: 2072-4292

Year: 2024

Issue: 5

Volume: 16

4 . 2 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

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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