Flood risk is a significant challenge for sustainable spatial planning, particularly concerning climate change and urbanization. Phrasing suitable land planning strategies requires assessing future flood risk and predicting the impact of urban sprawl. This study aims to develop an innovative approach combining land use change and hydraulic models to explore future urban flood risk, aiming to reduce it under different vulnerability and exposure scenarios. SPOT-3 and Sentinel-2 images were processed and classified to create land cover maps for 1995 and 2019, and these were used to predict the 2040 land cover using the Land Change Modeler Module of Terrset. Flood risk was computed by combining hazard, exposure, and vulnerability using hydrodynamic modeling and the Analytic Hierarchy Process method. We have compared flood risk in 1995, 2019, and 2040. Although flood risk increases with urbanization, population density, and the number of hospitals in the flood plain, especially in the coastal region, the area exposed to high and very high risks decreases due to a reduction in poverty rate. This study can provide a theoretical framework supporting climate change related to risk assessment in other metropolitan regions. Methodologically, it underlines the importance of using satellite imagery and the continuity of data in the planning-related decision-making process.

The primary aim of this study is to propose a potential landscape value assessment from different dimensions rather than the traditional approach of a composite indicator. The method used in this study is the combination of data collection from stakeholder survey, score measurement for landscape value dimensions using Structural Equation Modeling (SEM), and spatial representation with the support of Geographic Information System (GIS). From a large-scale (n = 400) investigation in the Moc Chau district, the statistical data extracted from the survey provides input data for the score determination process. SEM analysis shows that each landscape site has 11 determinants influencing the landscape value assessment. Using the RMSE comparison (for validation) with different interpolation methods, the ordinary kriging method is chosen to model the aggregation landscape value map of Moc Chau District. About 24.97% total area of the study area has great potential for tourism development, being mainly distributed in the center of a high mountainous area. This approach can be used as a model to advocate local and regional assessment and enhance value-based management in other territories in Vietnam and beyond.