Spatiotemporal Population Projections within the Framework of Shared Socioeconomic Pathways: A Seoul, Korea, Case Study

Abstract

Despite evidence of the growing importance of shared socioeconomic pathways (SSPs) in addressing climate change globally, there is a gap in research concerning the prediction of regional SSP populations. This study aims to project Seoul’s population from 2020 to 2100 under various SSPs and to interpolate this population through a spatiotemporal approach. Utilizing data from the Korea National Statistical Office and international socioeconomic scenario data, we applied a regression model for predicting population growth. This was supplemented with population projections derived from cohort modeling to enhance accuracy. Population allocation within each grid was determined based on the total floor area of residential buildings. To reflect shifting population demands, we adjusted long-term population trends using observed building completion dates from 2010 to 2020. By 2100, SSP3 is projected to have Seoul’s lowest population at 2,344,075, while SSP5 is expected to have the highest at 5,683,042. We conducted an analysis of grid population characteristics based on SSPs and verified the accuracy of our findings. Our results underscore the importance of refined population estimates for sustainable urban planning, indicating the potential for extending grid population estimates to other regions.