FuturePop - Constructing global gridded population maps at multiple scales for SSP scenarios

Climate change significantly impacts health, environments, and socioeconomics, but these effects are not evenly distributed globally. Variations in the spatial distribution, age and sex structure, and rate of growth of human populations drive different vulnerabilities to climate change. Maps of future population scenarios are therefore essential for understanding, planning, and responding to these impacts now and long into the future. 

While efforts have been made to generate gridded future population maps, key gaps remain: a) consistency with historical datasets containing population (e.g., HYDE) for climate simulations; b) updates aligned with the latest SSP estimates; c) use of up-to-date data and methods; d) high-resolution outputs (100m) to support detailed climate impact studies; e) disaggregation by age/sex to assess specific vulnerabilities; and f) inclusion and communication of uncertainty. To address these, we launched the FuturePop project. 

Here we present the latest updates to FuturePop. FuturePop V0.2 (Bondarenko et al., 2025) produced 1km global maps for population count between 2025 to 2100 from the latest Shared Socio-economic Pathway (SSP) population estimates (SSP Database V3.2), with these maps now extended to 2300. In turn this FuturePop data has been harmonized with past (HYDE & GHS-Pop) and present (WorldPop) population data to contribute to CMIP7 forcing data (Paprotny et al., 2025), with extensions made until 2300. 

We present our initial maps for FuturePop V1.0. FuturePop V1.0 adds enhancements by explicitly incorporating SSP urbanisation rates and using SSP informed building volume estimates for spatial disaggregation. The latest work to create sub-national SSP population estimates and progress to create age/sex disaggregated maps will also be introduced.  

Lastly, we present initial maps from “FuturePop Japan.” These are informed by Japanese adaptations of the SSPs (Chen et al., 2020), which provide greater national nuance than the global SSPs. Japan is a particularly interesting case, as its population is ageing and declining. It also had a high building vacancy rate of 22% in 2015, projected to reach 66–78% by 2100 (Yoshikawa et al., 2025). Although Japan is extreme, understanding how to spatially disaggregate shrinking populations is critical, as nearly 60% of countries are projected to decline by 2100 under SSP Database V3.2. We focus on the Japan SSP1 scenario, which includes planned urban compaction through the government-led “compact plus network” initiative.  

• Bondarenko, M., Tejedor Garavito, N., Priyatikanto, R., Zhang, W., Fang, W., Nosatiuk, B., & Tatem, A. (2025). Global 1-km population projections for 2025–2100 under SSP3.2 (v0.2). University of Southampton. https://doi.org/10.5258/SOTON/WP00849 

• Paprotny, D., Hawker, L., Bondarenko, M., Hilton, J., Garavito, N. T., Noi, E., & Tatem, A. (2025). input4MIPs: CMIP7 PIK-CMIP-1-0-0. Oak Ridge National Laboratory. https://doi.org/10.25981/ESGF.input4MIPs.CMIP7/2583900  

• Chen, H., Matsuhashi, K., Takahashi, K., Fujimori, S., Honjo, K., & Gomi, K. (2020). Adapting shared socioeconomic pathways for Japan. Sustainability Science, 15(3), 985–1000. https://doi.org/10.1007/s11625-019-00780-y  

• Yoshikawa, S., Imamura, K., Takahashi, K., & Matsuhashi, K. (2025). Development of scenarios for climate impacts in Japan. In N. Mimura & S. Takewaka (Eds.), Climate Change Impacts and Adaptation in Japan (Springer). https://doi.org/10.1007/978-981-96-2436-2_36-2436-2_3