Mapping high-resolution global gridded population distribution from 1870 to 2100

Long-term global gridded population data is crucial in deepening our understanding of spatiotemporal population dynamics and essential in disaster exposure assessment studies. Several gridded population datasets exist but only cover a single period of observational, historical, or future. Here, based on a unified data and method framework, we created a coherent and consistent gridded population dataset at 1 km resolution with a 10-year interval spanning from 1870 to 2100. Using the observed population maps (2000-2020), historical population hindcast (1870-2000), and future population projection (2020-2100) under the Shared Socioeconomic Pathways (SSPs) were modeled. The validation shows that the constructed dataset achieves a high quantitative agreement with existing datasets and can better distribute the population within the built-up area, resulting in a more reasonable allocation. The constructed gridded population dataset can clearly show the evolution of population distribution over a long period in a spatially explicit way and exhibit high temporal consistency. From 1870 to 2100 (SSPs), the global population showed an S-shaped growth pattern, increasing by about 4.17 to 8.49 times, which has exerted substantial pressure on global sustainable development. At the local scale, the consistent, long-term, high-resolution gridded population data reveals diverse spatial (cluster, linear, and ring) and temporal (emergence, increase, stable, decrease) dynamics of population patterns across distinct regions, periods, and scenarios. Applying the long-term gridded population data, we revealed a substantial increase in the proportion of the global population exposed to floods, rising from 10.61 % in 1870 to 11.98 %-13.93 % in 2100 (SSPs), highlighting a rapid population expansion within flood-prone areas. In general, this study provides a consistent global gridded population dataset spanning over 200 years, which can provide insights into the whole life cycle of the global population spatiotemporal dynamics and holds great application value in various fields.