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Automatic extraction of water inundation areas using Sentinel-1 data for large plain areas.

Hu, Shunshi; Qin, Jianxin; Ren, Jinchang; Zhao, Huimin; Ren, Jie; Hong, Haoran

Authors

Shunshi Hu

Jianxin Qin

Huimin Zhao

Jie Ren

Haoran Hong



Abstract

Accurately quantifying water inundation dynamics in terms of both spatial distributions and temporal variability is essential for water resources management. Currently, the water map is usually derived from synthetic aperture radar (SAR) data with the support of auxiliary datasets, using thresholding methods and followed by morphological operations to further refine the results. However, auxiliary datasets may lose efficacy on large plain areas, whilst the parameters of morphological operations are hard to be decided in different situations. Here, a heuristic and automatic water extraction (HAWE) method is proposed to extract the water map from Sentinel-1 SAR data. In the HAWE, we integrate tile-based thresholding and the active contour model, in which the former provides a convincing initial water map used as a heuristic input, and the latter refines the initial map by using image gradient information. The proposed approach was tested on the Dongting Lake plain (China) by comparing the extracted water map with the reference data derived from the Sentinel-2 dataset. For the two selected test sites, the overall accuracy of water classification is between 94.90% and 97.21% whilst the Kappa coefficient is within the range of 0.89 and 0.94. For the entire study area, the overall accuracy is between 94.32% and 96.7% and the Kappa coefficient ranges from 0.80 to 0.90. The results show that the proposed method is capable of extracting water inundations with satisfying accuracy.

Citation

HU, S., QIN, J., REN, J., ZHAO, H., REN, J., and HONG, H. 2020. Automatic extraction of water inundation areas using sentinel-1 data for large plain areas. Remote sensing [online], 12(2), article 243. Available from: https://doi.org/10.3390/rs12020243

Journal Article Type Article
Acceptance Date Jan 8, 2020
Online Publication Date Jan 10, 2020
Publication Date Jan 31, 2020
Deposit Date May 2, 2022
Publicly Available Date Mar 29, 2024
Journal Remote Sensing
Electronic ISSN 2072-4292
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 12
Issue 2
Article Number 243
DOI https://doi.org/10.3390/rs12020243
Keywords Water inundations; Heuristic and automatic water extraction (HAWE); Sentinel-1; Synthetic aperture radar (SAR); Dongting Lake (China); Remote sensing
Public URL https://rgu-repository.worktribe.com/output/1085653

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