Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways.

ABSTRACT: Spatially explicit population grid can play an important role in climate change, resource management, sustainable development and other fields. Several gridded datasets already exist, but global data, especially high-resolution data on future populations are largely lacking. 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. Our dataset is quantitatively consistent with the Shared Socioeconomic Pathways' (SSPs) national population. The spatially explicit population dataset we predicted in this research is validated by comparing it with the WorldPop dataset both at the sub-national an

SUBMITTER: Wang X 

PROVIDER: S-EPMC9466344 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature