Prioritizing Urban Underground Space for Sustainable and Resilient Cities: An SDG-Based Fuzzy AHP–TOPSIS Approach in Vietnam

Abstract This study proposes an integrated decision-support framework combining the fuzzy analytical hierarchy process (AHP) and the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to prioritize urban underground space (UUS) functions based on their contributions to the sustainable development goals (SDGs). Ho Chi Minh City, Vietnam, is selected as a representative case study due to its rapid urbanization, infrastructure overload, and high exposure to climate risks. The findings indicate that urban utility services are the highest priority for investment, followed by public transport services, regional infrastructure, and geothermal energy, reflecting the urgent need to strengthen foundational infrastructure systems to enhance urban resilience and sustainability. The prioritization results are shown to be robust through sensitivity analysis, with rankings remaining stable under variations in criteria weights. The study contributes by operationalizing the linkage between UUS and the SDGs within a hybrid fuzzy multicriteria decision-making framework, providing a transparent and systematic approach for infrastructure prioritization under uncertainty, and offering practical guidance for policymakers and urban planners in Vietnam and other rapidly urbanizing cities toward more strategic and sustainability-oriented underground space development.