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Urban areas are increasingly vulnerable to climate-related stresses such as heatwaves, flooding, and resource inefficiencies, requiring integrated, data-driven strategies to enhance resilience and sustainability. This study presents a modular assessment and planning framework that combines Geographic Information Systems (GIS), Building Information Modeling (BIM), City Information Modeling (CIM), microclimate simulations (ENVI-met, SWMM), Life Cycle Assessment (LCA), and remote sensing within a unified decision support interface (DSI). The framework operates across multiple spatial scales—from individual buildings to entire cities—to assess climate vulnerability, support evidence-based urban regeneration, and inform sustainable renovation strategies. It enables the identification of multifunctional interventions that reduce climate risks while improving energy efficiency, resource management, and environmental quality. Urban areas are classified based on their exposure and sensitivity to climate stressors, providing a systematic basis for prioritizing adaptation and mitigation measures. The approach is validated through a case study in Daegu, Republic of Korea, a city facing an aging building stock and increasing climatic pressures. The framework is presented as a conceptual design operating at Technology Readiness Level (TRL) 3–4, indicating that it has passed its proof-of-concept, with key components including ENVI-met microclimate simulations and Sentinel-2/Landsat remote sensing processing demonstrably operational for the Daegu context. Illustrative performance benchmarks drawn from the peer-reviewed literature demonstrate that framework-guided interventions can achieve urban heat island reductions of 1.5–4.0 °C via green roof and reflective surface combinations; stormwater runoff reductions of 30–60% through sustainable urban drainage systems; and building energy savings of 25–45 kWh/m2/yr from deep façade renovation. Its modular and transferable design ensures applicability across diverse urban contexts with similar climatic and infrastructural challenges.
Kim et al. (Wed,) studied this question.