Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Ageing population and green space dynamics for climate change adaptation in Southeast Asia

Nature Climate Change (2024)Cite this article

Subjects

Abstract

Climate change adaptation efforts are challenged by rapid population ageing and thus an increased proportion of vulnerable individuals. Despite its importance for adaptation planning, the link between ageing demographics and climate adaptation, particularly green infrastructure development, remains unexplored. Here we employ high-resolution satellite images and the difference-in-differences framework to assess the spatiotemporal relationship between ageing demographics and green space coverage change patterns across 26,885 Southeast Asian communities over the past two decades. We find that cities with an increased concentration of elderly residents exhibit greater vulnerability due to inadequate green infrastructure provision. The findings reveal green space reduction in ageing communities, which is more pronounced in socio-economically disadvantaged, rapidly ageing cities. Nonetheless, coastal cities, facing higher climate risks, exhibit no such decline due to their functional demand. Our results support considering socio-demographic shifts and geospatial disparities in city adaptation strategies.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Relationship between ageing population and green space dynamics in climate change vulnerability.
Fig. 2: β coefficient plot representing the regression results.

Similar content being viewed by others

Data availability

The data used for this study can be accessed via figshare at https://doi.org/10.6084/m9.figshare.25331881.v1 (ref. 73).

References

  1. IPCC Climate Change 2022: Impacts, Adaptation, and Vulnerability (eds Pörtner, H.-O. et al.) (Cambridge Univ. Press, 2022).

  2. Berrang-Ford, L. et al. Tracking global climate change adaptation among governments. Nat. Clim. Change 9, 440–449 (2019).

    Article  Google Scholar 

  3. Frantzeskaki, N. et al. Nature-based solutions for urban climate change adaptation: linking science, policy, and practice communities for evidence-based decision-making. BioScience 69, 455–466 (2019).

    Article  Google Scholar 

  4. Jorgenson, A. K. et al. Social science perspectives on drivers of and responses to global climate change. WIREs Clim. Change 10, e554 (2019).

    Article  Google Scholar 

  5. Füssel, H.-M. & Klein, R. J. Climate change vulnerability assessments: an evolution of conceptual thinking. Clim. Change 75, 301–329 (2006).

    Article  Google Scholar 

  6. Jarzebski, M. P. et al. Ageing and population shrinking: implications for sustainability in the urban century. NPJ Urban Sustain. https://doi.org/10.1038/s42949-021-00023-z (2021).

  7. Thomas, K. et al. Explaining differential vulnerability to climate change: a social science review. WIREs Clim. Change 10, e565 (2019).

    Article  Google Scholar 

  8. Gamble, J. L. et al. Climate change and older Americans: state of the science. Environ. Health Perspect. 121, 15–22 (2013).

    Article  Google Scholar 

  9. Li, T. et al. Aging will amplify the heat-related mortality risk under a changing climate: projection for the elderly in Beijing, China. Sci. Rep. 6, 28161 (2016).

    Article  CAS  Google Scholar 

  10. Molinsky, J. & Forsyth, A. Climate change, aging, and well-being: how residential setting matters. Hous. Policy Debate 33, 1029–1054 (2022).

    Article  Google Scholar 

  11. Huang, C. et al. Mortality burden attributable to heatwaves in Thailand: a systematic assessment incorporating evidence-based lag structure. Environ. Int. 121, 41–50 (2018).

    Article  Google Scholar 

  12. Dang, T. N. et al. Effects of extreme temperatures on mortality and hospitalization in Ho Chi Minh City, Vietnam. Int. J. Environ. Res. Public Health 16, 432 (2019).

    Article  Google Scholar 

  13. Gray, J., Lloyd, S., Healey, S. & Opdyke, A. Urban and rural patterns of typhoon mortality in the Philippines. Prog. Disaster Sci. 14, 100234 (2022).

    Article  Google Scholar 

  14. Sahani, M. et al. A case-crossover analysis of forest fire haze events and mortality in Malaysia. Atmos. Environ. 96, 257–265 (2014).

    Article  CAS  Google Scholar 

  15. Gosling, S. N., Lowe, J. A., McGregor, G. R., Pelling, M. & Malamud, B. D. Associations between elevated atmospheric temperature and human mortality: a critical review of the literature. Climatic Change 92, 299–341 (2009).

    Article  Google Scholar 

  16. Bunker, A. et al. Effects of air temperature on climate-sensitive mortality and morbidity outcomes in the elderly; a systematic review and meta-analysis of epidemiological evidence. eBioMedicine 6, 258–268 (2016).

    Article  Google Scholar 

  17. Mora, C. et al. Global risk of deadly heat. Nat. Clim. Change 7, 501–506 (2017).

    Article  Google Scholar 

  18. Dong, Z. et al. Heatwaves in Southeast Asia and their changes in a warmer world. Earth’s Future 9, e2021EF001992 (2021).

    Article  Google Scholar 

  19. Social Policies Catalogue on Population Ageing: A Rapid Scoping Review (UNFPA, 2020).

  20. Hunter, L. M. et al. Scales and sensitivities in climate vulnerability, displacement, and health. Popul. Environ. 43, 61–81 (2021).

    Article  Google Scholar 

  21. Rhoades, J. L., Gruber, J. S. & Horton, B. Developing an in-depth understanding of elderly adult’s vulnerability to climate change. Gerontologist 58, 567–577 (2017).

    Article  Google Scholar 

  22. Sturiale, L. & Scuderi, A. The role of green infrastructures in urban planning for climate change adaptation. Climate 7, 119 (2019).

    Article  Google Scholar 

  23. Goodwin, S., Olazabal, M., Castro, A. J. & Pascual, U. Global mapping of urban nature-based solutions for climate change adaptation. Nat. Sustain. 6, 458–469 (2023).

    Article  Google Scholar 

  24. Matsler, A. M., Meerow, S., Mell, I. C. & Pavao-Zuckerman, M. A. A ‘green’ chameleon: exploring the many disciplinary definitions, goals, and forms of “green infrastructure”. Landsc. Urban Plan. 214, 104145 (2021).

    Article  Google Scholar 

  25. Nieuwenhuijsen, M. J. Green infrastructure and health. Annu. Rev. Public Health 42, 317–328 (2021).

    Article  Google Scholar 

  26. Meerow, S. & Newell, J. P. Spatial planning for multifunctional green infrastructure: growing resilience in Detroit. Landsc. Urban Plan. 159, 62–75 (2017).

    Article  Google Scholar 

  27. Demuzere, M. et al. Mitigating and adapting to climate change: multi-functional and multi-scale assessment of green urban infrastructure. J. Environ. Manage. 146, 107–115 (2014).

    Article  CAS  Google Scholar 

  28. Matthews, T., Lo, A. Y. & Byrne, J. A. Reconceptualizing green infrastructure for climate change adaptation: barriers to adoption and drivers for uptake by spatial planners. Landsc. Urban Plan. 138, 155–163 (2015).

    Article  Google Scholar 

  29. Hansen, R. & Pauleit, S. From multifunctionality to multiple ecosystem services? A conceptual framework for multifunctionality in green infrastructure planning for urban areas. Ambio 43, 516–529 (2014).

    Article  Google Scholar 

  30. Ge, F. et al. Risks of precipitation extremes over Southeast Asia: does 1.5 °C or 2 °C global warming make a difference? Environ. Res. Lett. https://doi.org/10.1088/1748-9326/aaff7e (2019).

  31. Ge, F., Zhu, S., Luo, H., Zhi, X. & Wang, H. Future changes in precipitation extremes over Southeast Asia: insights from CMIP6 multi-model ensemble. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/abd7ad (2021).

  32. Sun, X., Ge, F., Fan, Y., Zhu, S. & Chen, Q. Will population exposure to heat extremes intensify over Southeast Asia in a warmer world? Environ. Res. Lett. https://doi.org/10.1088/1748-9326/ac48b6 (2022).

  33. Sietsma, A. J., Ford, J. D., Callaghan, M. W. & Minx, J. C. Progress in climate change adaptation research. Environ. Res. Lett. 16, 054038 (2021).

    Article  Google Scholar 

  34. Varquez, A. C. G., Darmanto, N. S., Honda, Y., Ihara, T. & Kanda, M. Future increase in elderly heat-related mortality of a rapidly growing Asian megacity. Sci. Rep. 10, 9304 (2020).

    Article  CAS  Google Scholar 

  35. Implementing a Green Recovery in Southeast Asia Report No. 9292695096 (Asian Development Bank Institute, 2022).

  36. Le, T. D. N. Climate change adaptation in coastal cities of developing countries: characterizing types of vulnerability and adaptation options. Mitig. Adapt. Strateg. Glob. Change 25, 739–761 (2020).

    Article  Google Scholar 

  37. Regional Framework on Healthy Ageing (2018–2022) Report No. 9789290226154 (World Health Organization, Regional Office for South-East Asia, 2018).

  38. Asia-Pacific Report on Population Ageing 2022: Trends, Policies and Good Practices Regarding Older Persons and Population Ageing (UN ESCAP, 2022).

  39. Mortreux, C. & Barnett, J. Adaptive capacity: exploring the research frontier. WIREs Clim. Change 8, e467 (2017).

    Article  Google Scholar 

  40. Kim, S. K., Bennett, M. M., van Gevelt, T. & Joosse, P. Urban agglomeration worsens spatial disparities in climate adaptation. Sci. Rep. 11, 8446 (2021).

    Article  CAS  Google Scholar 

  41. Wu, L., Kim, S. K. & Lin, C. Socioeconomic groups and their green spaces availability in urban areas of China: a distributional justice perspective. Environ. Sci. Policy 131, 26–35 (2022).

    Article  Google Scholar 

  42. Chen, W. Y. & Wang, D. T. Economic development and natural amenity: an econometric analysis of urban green spaces in China. Urban For. Urban Green. 12, 435–442 (2013).

    Article  CAS  Google Scholar 

  43. Dobbs, C., Nitschke, C. & Kendal, D. Assessing the drivers shaping global patterns of urban vegetation landscape structure. Sci. Total Environ. 592, 171–177 (2017).

    Article  CAS  Google Scholar 

  44. Garcia-Lamarca, M. et al. Urban green boosterism and city affordability: for whom is the ‘branded’ green city? Urban Stud. 58, 90–112 (2021).

    Article  Google Scholar 

  45. Richards, D. R., Passy, P. & Oh, R. R. Y. Impacts of population density and wealth on the quantity and structure of urban green space in tropical Southeast Asia. Landsc. Urban Plan. 157, 553–560 (2017).

    Article  Google Scholar 

  46. Wolch, J. R., Byrne, J. & Newell, J. P. Urban green space, public health, and environmental justice: the challenge of making cities ‘just green enough’. Landsc. Urban Plan. 125, 234–244 (2014).

    Article  Google Scholar 

  47. Glaeser, E. Cities, productivity, and quality of life. Science 333, 592–594 (2011).

    Article  CAS  Google Scholar 

  48. Estoque, R. C. et al. The future of Southeast Asia’s forests. Nat. Commun. 10, 1829 (2019).

    Article  Google Scholar 

  49. Sodhi, N. S. et al. The state and conservation of Southeast Asian biodiversity. Biodivers. Conserv. 19, 317–328 (2010).

    Article  Google Scholar 

  50. Providing Income Security for the Elderly (UN ESCAP, 2013).

  51. Mather, M. & Scommegna, P. How neighborhoods affect the health and well-being of older Americans. Today’s Res. Aging 35, 1–11 (2017).

    Google Scholar 

  52. Luís, S., Vauclair, C.-M. & Lima, M. L. Raising awareness of climate change causes? Cross-national evidence for the normalization of societal risk perception of climate change. Environ. Sci. Policy 80, 74–81 (2018).

    Article  Google Scholar 

  53. Mears, M., Brindley, P., Maheswaran, R. & Jorgensen, A. Understanding the socioeconomic equity of publicly accessible greenspace distribution: the example of Sheffield, UK. Geoforum 103, 126–137 (2019).

    Article  Google Scholar 

  54. Wüstemann, H., Kalisch, D. & Kolbe, J. Access to urban green space and environmental inequalities in Germany. Landsc. Urban Plan. 164, 124–131 (2017).

    Article  Google Scholar 

  55. Sulla-Menashe, D., Gray, J. M., Abercrombie, S. P. & Friedl, M. A. Hierarchical mapping of annual global land cover 2001 to present: the MODIS Collection 6 Land Cover product. Remote Sens. Environ. 222, 183–194 (2019).

    Article  Google Scholar 

  56. Peng, J., Zhao, M., Guo, X., Pan, Y. & Liu, Y. Spatial–temporal dynamics and associated driving forces of urban ecological land: a case study in Shenzhen City, China. Habitat Int. 60, 81–90 (2017).

    Article  Google Scholar 

  57. Salhab, M. & Basiri, A. Spatial data quality evaluation for land cover classification approaches. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 3, 681–687 (2020).

    Article  Google Scholar 

  58. Pezzulo, C. et al. Sub-national mapping of population pyramids and dependency ratios in Africa and Asia. Sci. Data 4, 170089 (2017).

    Article  Google Scholar 

  59. Kumar, M. D. et al. A framework for risk-based assessment of urban floods in coastal cities. Nat. Hazards 110, 2035–2057 (2022).

    Article  Google Scholar 

  60. Hinkel, J. “Indicators of vulnerability and adaptive capacity”: towards a clarification of the science–policy interface. Glob. Environ. Change 21, 198–208 (2011).

    Article  Google Scholar 

  61. Knapp, K. R. et al. International Best Track Archive for Climate Stewardship (IBTrACS) Project Version 3 (NOAA National Centers for Environmental Information, 2018); https://doi.org/10.7289/V5NK3BZP

  62. Feindouno, S., Guillaumont, P. & Simonet, C. The physical vulnerability to climate change index: an index to be used for international policy. Ecol. Econ. 176, 106752 (2020).

    Article  Google Scholar 

  63. Adler, R. et al. Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR) (National Centers for Environmental Information, 2016).

  64. Khasanov, K. in IOP Conference Series: Materials Science and Engineering 012063 (IOP, 2020).

  65. Szabó, G., Singh, S. K. & Szabó, S. Slope angle and aspect as influencing factors on the accuracy of the SRTM and the ASTER GDEM databases. Phys. Chem. Earth Parts A/B/C 83, 137–145 (2015).

    Article  Google Scholar 

  66. Siswanto, S. & Sule, M. in IOP Conference Series: Earth and Environmental Science 012059 (IOP, 2019).

  67. Zhao, M. et al. Mapping urban dynamics (1992–2018) in Southeast Asia using consistent nighttime light data from DMSP and VIIRS. Remote Sens. Environ. 248, 111980 (2020).

    Article  Google Scholar 

  68. Siders, A. R. Adaptive capacity to climate change: a synthesis of concepts, methods, and findings in a fragmented field. WIREs Clim. Change 10, e573 (2019).

    Article  Google Scholar 

  69. Goodman-Bacon, A. Difference-in-differences with variation in treatment timing. J. Econ. 225, 254–277 (2021).

    Article  Google Scholar 

  70. Callaway, B. & Sant’Anna, P. H. C. Difference-in-differences with multiple time periods. J. Econ. 225, 200–230 (2021).

    Article  Google Scholar 

  71. Human Development Report 2020 (UNDP, 2020).

  72. Andrew, N. L., Bright, P., de la Rua, L., Teoh, S. J. & Vickers, M. Coastal proximity of populations in 22 Pacific island countries and territories. PLoS ONE 14, e0223249 (2019).

    Article  CAS  Google Scholar 

  73. Kim, S. & Kim, J. Aging population and green space dynamics. figshare https://doi.org/10.6084/m9.figshare.25331881.v1 (2024).

Download references

Acknowledgements

This research was supported in part by the Korea Advanced Institute of Science and Technology (grant no. G04220032) and in part by the National Research Foundation of Korea grant funded by the Korean government (no. 2021H1D3A2A03097768) to S.K.K.

Author information

Authors and Affiliations

  1. Moon Soul Graduate School of Future Strategy, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

    Ji Soo Kim & Seung Kyum Kim

Authors
  1. Ji Soo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Seung Kyum Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.K. contributed to conceptualization, data collection, writing of the original draft and paper editing. S.K.K. contributed to conceptualization, methodology, data analysis, code development, validation and paper editing. Both authors contributed to paper revision.

Corresponding author

Correspondence to Seung Kyum Kim.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Climate Change thanks Sirkku Juhola and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Aging population trend by coastal and inland region.

The aging rate in the coastal region exhibits a steeper incline compared to that of the inland region. Starting from 2013, the coastal region’s aging rate surpasses that of the inland region, indicating a more rapid rise in the proportion of the elderly population along the coast. Data are mean ± SEM. The shaded areas show the 95% confidence interval on the predicted values.

Extended Data Fig. 2 Map of the study area.

The study area encompasses nine nations situated in Southeast Asia, all of which are members of the Association of Southeast Asian Nations. Illustration by authors using ArcMap software (ArcMap 10.8). Mapping source: Esri, Garmin, GEBCO, NOAA NGDC, and other contributors.

Supplementary information

Supplementary Information

Supplementary Fig. 1 and Tables 1–8.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, J.S., Kim, S.K. Ageing population and green space dynamics for climate change adaptation in Southeast Asia. Nat. Clim. Chang. (2024). https://doi.org/10.1038/s41558-024-01980-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41558-024-01980-w

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing