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Implementation of an Improved Water Change Tracking (IWCT) Algorithm: Monitoring the Water Changes in Tianjin over 1984–2019 Using Landsat Time-Series Data.

Authors :
Han, Xingxing
Chen, Wei
Ping, Bo
Hu, Yong
Duan, Weili
Maskey, Shreedhar
Chaffe, Pedro Luiz Borges
Luo, Pingping
He, Bin
Wu, Yiping
Hou, Jingming
Source :
Remote Sensing. Feb2021, Vol. 13 Issue 3, p493. 1p.
Publication Year :
2021

Abstract

Tianjin is the largest open city along the coastline in Northern China, which has several important wetland ecosystems. However, no systematic study has assessed the water body changes over the past few decades for Tianjin, not to mention their response to human activities and climate change. Here, based on the water change tracking (WCT) algorithm, we proposed an improved water change tracking (IWCT) algorithm, which could remove built-up shade noise (account for 0.4%~6.0% of the final water area) and correct omitted water pixels (account for 1.1%~5.1% of the final water area) by taking the time-series data into consideration. The seasonal water product of the Global Surface Water Data (GSWD) was used to provide a comparison with the IWCT results. Significant changes in water bodies of the selected area in Tianjin were revealed from the time-series water maps. The permanent water area of Tianjin decreased 282.5 km2 from 1984 to 2019. Each time after the dried-up period, due to government policies, the land reclamation happened in Tuanbo Birds Nature Reserve (TBNR), and, finally, 12.6 km2 of the lake has been reclaimed. Meanwhile, 488.6 km2 of land has been reclaimed from the sea along the coastal zone in the past 16 years at a speed of 28.74 km2 yr−1 in the Binhai New Area (BHNA). The method developed in this study could be extended to other sensors which have similar band settings with Landsat; the products acquired in this study could provide fundamental reference for the wetland management in Tianjin. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
13
Issue :
3
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
148502813
Full Text :
https://doi.org/10.3390/rs13030493