A Spatiotemporal Analysis of Potential Demand for Urban Parks Using Long-Term Population Projections

In the Republic of Korea, the problems of low birth rate and population aging are accelerating population decline at the regional level, leading to the phenomena of local extinction and urban shrinkage. These phenomena, coupled with the projected nationwide population decline, pose a fundamental threat to the sustainability of essential infrastructure such as urban parks. The conventional growth-oriented paradigm of urban planning has shown clear limitations in quantitatively forecasting future demand, constraining proactive management strategies for the era of population decline. To address this gap, this study develops a policy-decision-support framework that integrates long-term population projections, grid-based population data, the DEGURBA urban classification system—a global standard for delineating urban and rural areas— and network-based accessibility analysis. For the entire Republic of Korea, we (1) constructed a 1 km resolution time-series population dataset for 2022–2072; (2) applied DEGURBA to quantify transitions among urban, semi-urban, and rural types; and (3) assessed changes in potential user populations within the defined service catchments. The results indicate that while population concentration in the Seoul Capital Area persists, under the low-variant scenario, a projected average decline of 40% in potential user populations by 2072 will lead to significant functional changes, with 53.6% of municipalities nationwide transitioning to “semi-urban” or “rural” areas. This spatial shift is projected to decrease the proportion of urban parks located in “urban” areas from 83.3% to 75.0%, while the total potential user population is expected to plummet from approximately 44.4 million to 25.8 million, a 42.0% reduction. This study underscores the need for urban park policy to move beyond quantitative expansion and toward quality-oriented management based on selection and concentration. By uniquely integrating long-term demographic scenarios, the Degree of Urbanization (DEGURBA), and spatial accessibility analysis, this study provides a foundational scientific basis for forecasting future demand and supports the formulation of sustainable, data-driven strategies for urban park restructuring under conditions of demographic change.