Siying Li , Yi Tang , Yuting Zhao , Xiaojun Ning , Yifan Zhang , Siran Lv , Chenshu Liu
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引用次数: 0
Abstract
Flood disasters pose increasingly severe threats to densely populated and economically critical regions under changing climate conditions. In this study, we conducted a comprehensive flood risk assessment of the Beijing-Tianjin-Hebei (BTH) region, integrating multi-source remote sensing data and explainable machine learning methods. First, flood inundation areas during the 2023 extreme rainfall event were identified using Sentinel-1 SAR imagery. Based on the assessment framework of hazard, exposure, and vulnerability, key factors influencing flood risk were quantified using a XGBboost model and SHAP (Shapley Additive Explanations) analysis. The results revealed that terrain ruggedness, elevation, precipitation, dependency ratio, and GDP (Gross Domestic Product) were the primary drivers of flood risk distribution. Subsequently, future flood risk patterns for 2030 were projected under four Shared Socioeconomic Pathways (SSP126, SSP245, SSP370, and SSP585), combining projected environmental and socio-economic variables with the established model. The findings indicate a clear trend of flood risk intensification under higher emission scenarios, with high-risk areas expanding significantly under SSP370 and SSP585. These results emphasize the urgent need for differentiated flood management strategies, combining climate mitigation, resilient urban planning, and adaptive infrastructure development to effectively reduce future flood risks. It provides a scientific basis for climate-resilient disaster risk governance in rapidly urbanizing regions.
期刊介绍:
The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems