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Estimation of Gridded Population with Spatial Downscaling in South Korea

Author

Listed:
  • Sungdon Kim

    (Department of Information and Statistics, Gyeongsang National University, Jinju 52828, Republic of Korea)

  • Youngmi Lee

    (Department of Statistics and Research Institute of Applied Statistics, Jeonbuk National University, Jeonju 54896, Republic of Korea)

  • Haejune Oh

    (Department of Information and Statistics, Gyeongsang National University, Jinju 52828, Republic of Korea)

Abstract

South Korea faces serious challenges regarding population imbalance and sustainability due to low birth rates and the aging population. This study utilizes future population projection scenarios provided by Statistics Korea to estimate population distributions at both regional and grid levels. The analysis applies an urban growth model for administrative divisions and a modified gravity model for grid-level estimations. The modified gravity model enhances the prediction accuracy by effectively accounting for multi-centered urban structures and excluding non-residential areas such as mountains, rivers, and parks. Additionally, a novel spatial weight matrix considering train station connectivity is introduced. The results show that incorporating public transportation infrastructure around cities slows the rate of population decline, highlighting its mitigating effects on regional extinction. The study predicts that over 30 cities will face depopulation risks by 2072, while population concentration in the Seoul metropolitan area will persist. The grid-level analysis reveals detailed patterns of population imbalance within regions, particularly identifying uninhabited areas and their spatial distribution. These findings carry significant implications for infrastructure planning and regional development. By employing innovative modeling approaches and high-resolution projections, this study provides policymakers with valuable insights into South Korea’s demographic challenges and potential advances in sustainable urban and regional development.

Suggested Citation

  • Sungdon Kim & Youngmi Lee & Haejune Oh, 2025. "Estimation of Gridded Population with Spatial Downscaling in South Korea," Sustainability, MDPI, vol. 17(4), pages 1-26, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:4:p:1511-:d:1589486
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    References listed on IDEAS

    as
    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Daisuke Murakami & Yoshiki Yamagata, 2019. "Estimation of Gridded Population and GDP Scenarios with Spatially Explicit Statistical Downscaling," Sustainability, MDPI, vol. 11(7), pages 1-18, April.
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    Cited by:

    1. Daeho Kim & Yoonji Kim & Hyun Chan Sung & Seongwoo Jeon, 2025. "A Spatiotemporal Analysis of Potential Demand for Urban Parks Using Long-Term Population Projections," Land, MDPI, vol. 14(10), pages 1-33, October.

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