Sustainable urban growth scenario for climate-vulnerable coastal cities: An analysis based on ubiquitous big data and a hybrid fuzzy-cellular automata

Coastal cities face significant challenges in urban growth planning due to rapid urbanization, exposure to natural hazards, and heightened vulnerability to climate change. These challenges are particularly acute in developing countries, which host nearly 90% of at-risk coastal populations. However, effective planning in these contexts is often constrained by the scarcity of reliable spatial data. To address this issue, this study integrates ubiquitous big data sources and SDG-based parameters to develop a Sustainable Urban Growth Scenario (SUGS) and a Normal Urban Growth Scenario (NUGS). A hybrid cellular automata approach combining Fuzzy-CA and CA-Markov was applied to project land-use change in Chabahar and Konarak on Iran’s Makran coast. Results indicate that under NUGS, the cities may expand by over 1.9 million hectares by 2050, leading to extensive development within environmentally sensitive zones. In contrast, SUGS promotes a leapfrog development pattern. This study contributes an SDG-guided, ubiquitous big data-driven framework for guiding urban growth in coastal cities facing environmental challenges. The findings offer useful insights for policymakers and regional planners seeking to support resilient coastal urban management and disaster risk reduction, particularly in least developed countries.