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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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GlobPOP: A 33-year (1990-2022) global gridded population dataset (Version 2.0-test-beta)

Authors: Liu, Luling; Cao, Xin; Li, Shijie; Jie, Na;

GlobPOP: A 33-year (1990-2022) global gridded population dataset (Version 2.0-test-beta)

Abstract

Data Usage Notice This version is not recommended for download. Please check the newest version. We would like to inform you that the updated GlobPOP dataset (2021-2022) have been available in version 2.0. The GlobPOP dataset (2021-2022) in the current version is not recommended for your work. The GlobPOP dataset (1990-2020) in the current version is the same as version 1.0. Thank you for your continued support of the GlobPOP. If you encounter any issues, please contact us via email at lulingliu@mail.bnu.edu.cn. Introduction Continuously monitoring global population spatial dynamics is essential for implementing effective policies related to sustainable development, such as epidemiology, urban planning, and global inequality. Here, we present GlobPOP, a new continuous global gridded population product with a high-precision spatial resolution of 30 arcseconds from 1990 to 2020. Our data-fusion framework is based on cluster analysis and statistical learning approaches, which intends to fuse the existing five products(Global Human Settlements Layer Population (GHS-POP), Global Rural Urban Mapping Project (GRUMP), Gridded Population of the World Version 4 (GPWv4), LandScan Population datasets and WorldPop datasets to a new continuous global gridded population (GlobPOP). The spatial validation results demonstrate that the GlobPOP dataset is highly accurate. To validate the temporal accuracy of GlobPOP at the country level, we have developed an interactive web application, accessible at https://globpop.shinyapps.io/GlobPOP/, where data users can explore the country-level population time-series curves of interest and compare them with census data. With the availability of GlobPOP dataset in both population count and population density formats, researchers and policymakers can leverage our dataset to conduct time-series analysis of population and explore the spatial patterns of population development at various scales, ranging from national to city level. Data description The product is produced in 30 arc-seconds resolution(approximately 1km in equator) and is made available in GeoTIFF format. There are two population formats, one is the 'Count'(Population count per grid) and another is the 'Density'(Population count per square kilometer each grid) Each GeoTIFF filename has 5 fields that are separated by an underscore "_". A filename extension follows these fields. The fields are described below with the example filename: GlobPOP_Count_30arc_1990_I32 Field 1: GlobPOP(Global gridded population)Field 2: Pixel unit is population "Count" or population "Density"Field 3: Spatial resolution is 30 arc secondsField 4: Year "1990"Field 5: Data type is I32(Int 32) or F32(Float32) More information Please refer to the paper for detailed information: Liu, L., Cao, X., Li, S. et al. A 31-year (1990–2020) global gridded population dataset generated by cluster analysis and statistical learning. Sci Data 11, 124 (2024). https://doi.org/10.1038/s41597-024-02913-0. The fully reproducible codes are publicly available at GitHub: https://github.com/lulingliu/GlobPOP.

This research was supported by the National Natural Science Foundation of China (Grant No. 42192584 and 42371334) and Open Fund of State Key Laboratory of Remote Sensing Science and Beijing Engineering Research Center for Global Land Remote Sensing Products (Grant No. OF202316).

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Keywords

Sustainability sciences

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average