Citation: Tuholske, Cascade, Andrea E. Gaughan, Alessandro Sorichetta, Alex de Sherbinin, Agathe Bucherie, Carolynne Hultquist, Forrest Stevens, Andrew Kruczkiewicz, Charles Huyck, and Greg Yetman. 2021. "Implications for Tracking SDG Indicator Metrics with Gridded Population Data" Sustainability 13, no. 13: 7329. https://doi.org/10.3390/su13137329

Citation: Chen, R., Yan, H., Liu, F., Du, W., & Yang, Y. (2020). "Multiple Global Population Datasets: Differences and Spatial Distribution Characteristics." ISPRS International Journal of Geo-Information 9(11): 637, https://doi.org/10.3390/ijgi9110637

Two recent papers evaluate the accuracy of global gridded population data products against reference data sets. The first paper, published in Population and Environment, conducts a pixel level evaluation of population counts across space (different levels of urbanization) and time.

This article published in Nature cites POPGRID for a comparative overview of inputs and methodology of different gridded population datasets.

Citation: Falchetta, G., Pachauri, S., Parkinson, S. et al. A high-resolution gridded dataset to assess electrification in sub-Saharan Africa. Sci Data 6, 110 (2019). https://doi.org/10.1038/s41597-019-0122-6

Nature Abstract:

As communities around the world grapple with the devastating effects of COVID-19, the importance of timely, disaggregated, and accurate data has never been clearer. It is vital that we understand where populations are located, the available infrastructure, and their access to critical services to ensure that everyone can understand their risk and take appropriate action. From new platforms, analysis, and available datasets, read more on how participants in the POPGRID Data Collaborative are helping to fight this pandemic.