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Long Time Series Water Extent Analysis for SDG 6.6.1 Based on the GEE Platform: A Case Study of Dongting Lake

Authors :
Chunlin Wang
Weiguo Jiang
Yue Deng
Ziyan Ling
Yawen Deng
Source :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 490-503 (2022)
Publication Year :
2022
Publisher :
IEEE, 2022.

Abstract

Understanding the variation regularity of water extent can provide insights into lake conservation and management. In this study, inter- and inner-annual variations of water extent during the period of 1987–2020 were analyzed to understand the temporal and spatial distribution characteristics of Dongting Lake. We applied the Multiple Index Water Detection Rule to extract the Dongting Lake water extent quickly and accurately based on Google Earth Engine platform, and then assessed the extraction accuracy. The water surface analysis results showed that (1) based on sustainable development goals (SDG) 6.6.1, the trend of water extent showed the downward fluctuating trend from 1987 to 2020, with the overall average water extent being 1894.48 km². (2) Among the monthly average water area, the largest extent was 2477.14km² (July) and the smallest was 848.14 km² (January). Among the seasonal mean water area, summer was the largest, with an area of 2438.06 km², and winter was the smallest at 967.34 km². (3) For the water inundation frequency, seasonal water bodies accounted for the largest proportion, with 1577.85 km²; the nonwater area was the smallest, with the area of 573.02 km²; and the permanent water area was 1086.21 km². Through the analysis of the historical water body extent of the long time series of Dongting Lake, this study reflected support for SDG, for which the research idea and design can help us understand the importance and feasibility of the SDG 6.6.1 indicator.

Details

Language :
English
ISSN :
21511535
Volume :
15
Database :
Directory of Open Access Journals
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.60f5ea72cc64478b216050e2ec1a8e5
Document Type :
article
Full Text :
https://doi.org/10.1109/JSTARS.2021.3088127