Spatio-temporal dynamics monitoring of surface water bodies in Nhat Le River Basin, Vietnam, by Google Earth Engine

Minh Anh Vu, D. N. Quang, Tinh Xuan Nguyen, L. Ribbe
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Abstract

Consistent monitoring of surface water dynamics is essential for water resources, flood risk management, and addressing the challenges posed by climate change, urbanization. Located in Central Vietnam, Nhat Le River Basin witnesses significant and noticeable dynamics in surface water on a yearly basis due to water-related disasters like floods and droughts. This article presents the first comprehensive study to systematically map and analyse the long-term (2016–2022) spatiotemporal dynamics of surface water in the Nhat Le River Basin of Vietnam, utilizing Sentinel-1 data. The results reveal that the optimal threshold for separating water from non-water pixels is −19 dB, with an overall accuracy of 0.93–0.94 and a Kappa coefficient of 0.77–0.82. Through quantitative analysis, the study characterizes seasonal and interannual variations in the surface water extent, contributing to an enhanced understanding of flood patterns and associated risks in a data-scarce region. Our analysis reveals the Kien Giang river delta as the most flooding-vulnerable sub-region, underscoring the importance of targeted risk management and adaptation planning in this area. A Google Earth Engine Tool is developed for automatic detecting, monitoring, and accessing the spatiotemporal dynamics of surface water in Nhat Le River Basin over the period 2016–2022 and is freely available on GitHub (https://github.com/MinhVu25/Surface_Water_Dynamics_2023).
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谷歌地球引擎对越南 Nhat Le 河流域地表水体的时空动态监测
地表水动态的持续监测对于水资源、洪水风险管理以及应对气候变化和城市化带来的挑战至关重要。北黎河流域位于越南中部,由于洪水和干旱等与水有关的灾害,每年地表水都会发生显著变化。本文是首次利用哨兵 1 号数据,对越南北黎河流域地表水的长期(2016-2022 年)时空动态进行系统测绘和分析的综合性研究。研究结果表明,将水像素与非水像素区分开来的最佳阈值为-19 dB,总体准确度为 0.93-0.94 ,Kappa 系数为 0.77-0.82 。通过定量分析,该研究描述了地表水范围的季节和年际变化特征,有助于加深对数据稀缺地区的洪水模式和相关风险的理解。我们的分析表明,建江三角洲是最易受洪水影响的次区域,这突出了在该地区进行有针对性的风险管理和适应规划的重要性。我们开发了一个谷歌地球引擎工具,用于自动探测、监测和获取 2016-2022 年期间那乐河流域地表水的时空动态,该工具可在 GitHub 上免费获取 (https://github.com/MinhVu25/Surface_Water_Dynamics_2023)。
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