Analysis of Riverine Flood Dynamics by using Sentinel-1 Satellite Imagery in An Giang, Vietnam
Vol. 134 No. 1S-1 (2025), Special Issue: IFGTM 2025
Vol. 134 No. 1S-1 (2025)

Analysis of Riverine Flood Dynamics by using Sentinel-1 Satellite Imagery in An Giang, Vietnam

Special Issue: IFGTM 2025
https://doi.org/10.26459/hueunijns.v134i1S-1.7934
Published 2025-12-29
Ngoc Nhu Y Ho
Faculty of Engineering, Vietnamese-German University, Thoi Hoa Ward, Ho Chi Minh City, Vietnam
Sameh A. Kantoush
Disaster Prevention Research Institute, Kyoto University, Goka-sho, Uji City, Kyoto, Japan
Manh-Hung Le
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Duong Cao Phan
Ireland's Centre for AI, School of Computer Science, University of Dublin, Belfield, Dublin 4, Ireland
Doan Van Binh*
Faculty of Engineering, Vietnamese-German University, Thoi Hoa Ward, Ho Chi Minh City, Vietnam
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Keywords

Vietnamese Mekong Delta, flooding, remote sensing, Sentinel-1A

How to Cite

1.
Ho NNY, Kantoush SA, Le M-H, Phan DC, Doan VB. Analysis of Riverine Flood Dynamics by using Sentinel-1 Satellite Imagery in An Giang, Vietnam. hueuni-jns [Internet]. 2025Dec.29 [cited 2026Jan.23];134(1S-1):127-40. Available from: http://222.255.146.83/index.php/hujos-ns/article/view/7934
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Abstract

The Vietnamese Mekong Delta (VMD) is frequently affected by seasonal floods, especially with An Giang Province being one of the most vulnerable regions. In the context of climate change and human activities, such as dam construction and dyke development, the flood regime in this area is rapidly and unpredictably changing. These alterations have exacerbated challenges in agriculture, water management, and local livelihoods, yet reliable long-term flood maps and early-warning tools remain limited. This study used Sentinel-1 satellite imagery on the Google Earth Engine (GEE) platform to monitor and evaluate flood dynamics in An Giang from 2015 to 2024. The results show that flooding still occurred in low-lying areas without closed-dike protection, though the overall flooded extent slightly decreased during 2015–2024. However, the annual patterns showed considerable variability: while 2017–2018 recorded extensive flooding with peak inundation exceeding 30,000 ha, 2019–2020 experienced minimal flood extent. This sharp contrast highlights the increasing irregularity of the flood regime in An Giang. This study created a long-term remote sensing dataset for An Giang by using Sentinel-1 and GEE, providing a scientific basis for flood monitoring, agricultural adaptation, and advancing remote sensing applications in deltaic flood monitoring.

https://doi.org/10.26459/hueunijns.v134i1S-1.7934
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