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author:

Wu, Wenting (Wu, Wenting.) [1] (Scholars:吴文挺) | Zhi, Chao (Zhi, Chao.) [2] | Chen, Chunpeng (Chen, Chunpeng.) [3] | Tian, Bo (Tian, Bo.) [4] | Chen, Zuoqi (Chen, Zuoqi.) [5] (Scholars:陈佐旗) | Su, Hua (Su, Hua.) [6] (Scholars:苏华)

Indexed by:

SCIE

Abstract:

Intertidal vegetation plays an essential role in habitat provision for waterbirds but suffers great losses due to human activities. However, it is challenging in tracking the human-driven loss and degradation of intertidal vegetation due to rapid urbanization in a high temporal resolution. In this study, a methodological framework based on full Landsat time-series (FLTS) is proposed to detect the year of change (YOC) of intertidal vegetation converted to impervious surfaces (ISs) and artificial ponds (APs), and the condition of the remaining intertidal vegetation was also assessed by FLTS, in the Fujian province, a subtropical coastal area lying in southeast China. The accuracies of the YOC detection of intertidal vegetation converted to IS and AP were 91.84% and 72.73%, with mean absolute errors of 0.26 and 1.06, respectively. The total areas of intertidal vegetation encroached by IS and AP were 31.68 km(2) and 23.85 km(2), respectively. Most ISs were developed later than 2010, and most APs were developed earlier than 2005, which are highly related to the implementation of local policies for economic development. The remaining intertidal vegetation in growing, stable, and degraded conditions were 43.05%, 56.38%, and 0.57%, respectively. The results indicated that areas of intertidal vegetation were reclaimed for anthropogenic uses at a considerable rate, although the intertidal vegetation still increased owing to natural development after the establishment of natural reserves. The study demonstrates that the FLTS has capacities in monitoring the dynamics in coastal zones solely for its dense earth observations.

Keyword:

change detection condition assessment full Landsat time-series human activities Intertidal vegetation

Community:

  • [ 1 ] [Wu, Wenting]Fuzhou Univ, Natl & Local Joint Engn Res Ctr Satellite Geospati, Key Lab Spatial Data Min, Informat Sharing Minist Educ, Fuzhou, Peoples R China
  • [ 2 ] [Zhi, Chao]Fuzhou Univ, Natl & Local Joint Engn Res Ctr Satellite Geospati, Key Lab Spatial Data Min, Informat Sharing Minist Educ, Fuzhou, Peoples R China
  • [ 3 ] [Chen, Zuoqi]Fuzhou Univ, Natl & Local Joint Engn Res Ctr Satellite Geospati, Key Lab Spatial Data Min, Informat Sharing Minist Educ, Fuzhou, Peoples R China
  • [ 4 ] [Su, Hua]Fuzhou Univ, Natl & Local Joint Engn Res Ctr Satellite Geospati, Key Lab Spatial Data Min, Informat Sharing Minist Educ, Fuzhou, Peoples R China
  • [ 5 ] [Chen, Chunpeng]East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai, Peoples R China
  • [ 6 ] [Tian, Bo]East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai, Peoples R China

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Source :

GISCIENCE & REMOTE SENSING

ISSN: 1548-1603

Year: 2022

Issue: 1

Volume: 59

Page: 2266-2282

6 . 7

JCR@2022

6 . 0 0 0

JCR@2023

ESI Discipline: GEOSCIENCES;

ESI HC Threshold:51

JCR Journal Grade:1

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 3

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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