Keywords
flood relocation
Abstract
Planning support for flood relocation requires combining household-level disaster models with commuting analytics, urban opportunity measurement, and AI-assisted governance. Pre-disaster relocation research provides a behavioral foundation for modeling household response to flood risk. Commuting matrix estimation and counterfactual commuting analysis support evaluation of how relocation affects daily travel patterns. Polycentric development and urban sub-center studies explain the distribution of employment, services, and commercial activity across metropolitan space. Model-confidence research is relevant because AI-based planning tools must communicate uncertainty carefully when used for relocation prioritization or public policy explanation. Urban systems science offers a cross-scale framework for connecting these elements. This literature cluster supports integrated planning tools that evaluate flood risk, accessibility, metropolitan structure, and the reliability of computational decision support.
References
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