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Agent-based intra-regional relocation model considering spatial local amenity for urban planning-based flood risk management: Assessing the impact of urban development on flood exposure
被引:0
|作者:
Tanaka, Tomohiro
[1
]
Koga, Asuka
[2
]
Yokomatsu, Muneta
[3
]
机构:
[1] Kyoto Univ, Grad Sch Engn, Kyoto, Kyoto, Japan
[2] CTI Engn Co Ltd, Chuo, Tokyo, Japan
[3] Int Inst Appl Syst Anal, Adv Syst Anal Program, Laxenburg, Austria
来源:
关键词:
agent-based model;
flood risk management;
household relocation;
spatial distance management;
CHAIN MIGRATION;
AREA;
D O I:
10.1111/jfr3.13035
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Integrated flood risk management based on urban policies remains challenging compared with infrastructure due to the unclear risk-reduction effects over time. To consider heterogeneity in social responses to urban planning measures, a previous study developed an agent-based household relocation model under flood risk (AHR-FLOOD) by combining flood-inundation and agent-based relocation models. However, accurate modelling of relocation incentives remains challenging. This study aimed to improve AHR-FLOOD by introducing spatial amenities based on transportation convenience and reflecting their impact on the decision-making processes of agents to analyze the development of different flood risk areas. AHR-FLOOD considering access to public transportation reproduced the spatial characteristics of the actual population and housing prices. The development of low-risk areas reduced flood exposure and resulting flood damage. However, this effect was less clear for low-income individuals, but the development of low-amenity areas had the potential to induce low-income population to move to safe areas. Chain migration was observed as a long-term effect of the spatial amenity policy. This study presents insights into the effect of transportation policies on flood safety for long-term spatial distance management in an agent-based approach with the rigorous modelling and validation of local amenity impact on household relocation choices.
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