Human activities have contributed to major greenhouse gas emissions and resource consumption at both regional and global levels 2. Global climate change and sustainable development are receiving increasing attention both from researchers and policymakers 1. 3569 provinces (almost all provinces on the globe) and more than 480 thousand grids are taken into verification, and the results show that our dataset can serve as an input for predictive research in various fields. The spatially explicit population dataset we predicted in this research is validated by comparing it with the WorldPop dataset both at the sub-national and grid level. Our dataset is quantitatively consistent with the Shared Socioeconomic Pathways’ (SSPs) national population. Based on the WorldPop dataset, we present a global gridded population dataset covering 248 countries or areas at 30 arc-seconds (approximately 1 km) spatial resolution with 5-year intervals for the period 2020–2100 by implementing Random Forest (RF) algorithm. Several gridded datasets already exist, but global data, especially high-resolution data on future populations are largely lacking. Spatially explicit population grid can play an important role in climate change, resource management, sustainable development and other fields.
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