ArticleScientific data2024
A 31-year (1990-2020) global gridded population dataset generated by cluster analysis and statistical learning.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
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- China's freshwater lake storage hotspots revealed by bathymetry and typology mapping.National science review · 2026Article
- International trade and air-quality-related mortality.Nature communications · 2026Article
- How the Choice of Spatial Resolution Affects Freshwater Fish Species Distribution Models.Ecology and evolution · 2026Article
- Modeling and Evaluating Integrated Pollution Control Measures in Rivers: A Case Study of the Lianjiang River Basin.Toxics · 2026Article
- Assessing decadal changes in human exposure near wildfires in a Mediterranean region.Scientific reports · 2026Article
- Gaps in tropical science from unrepresentative distribution of sampling and citation across natural terrestrial environments.Nature communications · 2025Article
- Mosquito vector ecologies are destabilizing as a result of climate change.Research square · 2025Article
- GCSD: A comprehensive coastal indicators database for global coastal sustainable development assessment.Scientific data · 2025Article
- Mapping the mismatch between building and population growth: A global study of 1,700 cities.iScience · 2025Article
- Mosquito vector ecologies are destabilizing as a result of climate change.bioRxiv : the preprint server for biology · 2025Article
- A high resolution gridded dataset for takeaway packaging waste in China.Scientific data · 2025Article
- A 31-year (1990-2020) global gridded population dataset generated by cluster analysis and statistical learning.Scientific data · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Continuously monitoring global population spatial dynamics is crucial for implementing effective policies related to sustainable development, including epidemiology, urban planning, and global inequality. However, existing global gridded population data products lack consistent population estimates, making them unsuitable for time-series analysis. To address this issue, this study designed a data fusion framework based on cluster analysis and statistical learning approaches, which led to the generation of a continuous global gridded population dataset (GlobPOP). The GlobPOP dataset was evaluated through two-tier spatial and temporal validation to demonstrate its accuracy and applicability. The spatial validation results show that the GlobPOP dataset is highly accurate. The temporal validation results also reveal that the GlobPOP dataset performs consistently well across eight representative countries and cities despite their unique population dynamics. With the availability of GlobPOP datasets in both population count and population density formats, researchers and policymakers can leverage the new dataset to conduct time-series analysis of the population and explore the spatial patterns of population development at global, national, and city levels.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.