Revolutionizing flood resilience: Human-centred AI for adaptive and regenerative urban design

• Gorzka, Jakub ^[1] ; Burda, Izabela ^[1] ; Józekowski, Jacek ^[1] ; Nyka, Lucyna ^[1]
  1. [1] Gdańsk University of Technology

     Gdańsk University of Technology

     Gdańsk, Polonia

     
• Localización: Land use policy: The International Journal Covering All Aspects of Land Use, ISSN 0264-8377, ISSN-e 1873-5754, Nº. 170, 2026
• Idioma: inglés
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• Resumen

  • Urban flooding poses escalating risks under climate change, requiring planning approaches that integrate technological precision with human and ecological values. This study introduces a Human-Centred Artificial Intelligence (HCAI) framework for adaptive and regenerative flood-resilient urban design. Unlike conventional AI approaches focused on optimisation, HCAI embeds ethical, participatory, and context-sensitive principles into land-use governance. The paper develops a four-pillar analytical framework – technical integration, institutional arrangements, stakeholder engagement, and land-use innovation – operationalised through a document-based comparative analysis of nine cities representing diverse flood typologies, governance regimes, and documented AI/digital flood-resilience activity. Documentary evidence suggests that AI tools such as Machine Learning, Deep Learning, and Graph Neural Networks are reported to support flood-risk prediction and response coordination in flood-risk applications, while their planning relevance depends on inclusive decision-making and regenerative land-use strategies. Cities with stronger institutional embedding of AI-enabled or digital tools within adaptive regulatory systems and participatory platforms (e.g., Rotterdam, Copenhagen, Bangkok) show clearer planning-policy pathways, whereas those relying on fragmented or project-based deployments (e.g., Venice, Sydney) show limited continuity. Findings suggest that technical capability alone is insufficient: planning relevance depends on governance maturity, ethical safeguards, civic legitimacy, and linkage to spatial planning instruments. By coupling algorithmic intelligence with participatory and regulatory innovation, the study advances a policy-oriented framework for embedding HCAI into spatial governance and identifying conditions that may support a shift from defensive flood control toward regenerative, socially just urbanism. The framework guides AI institutionalisation within land-use systems and contributes to debates on equitable, data-driven climate adaptation.