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LandScan Global 30 Arcsecond Annual Global Gridded Population Datasets from 2000 to 2022

Viswadeep Lebakula, Kelly Sims, Andrew Reith, Amy Rose, Jake McKee, Phil Coleman, Jason Kaufman, Marie Urban, Warren C. Jochem, Carrie Whitlock, Mitchell Ogden, J. A. Pyle, Darrell Roddy, Justin Epting, Eddie Bright

2025Scientific Data74 citationsDOIOpen Access PDF

Abstract

Oak Ridge National Laboratory (ORNL) annually develops the LandScan Global (LSG) dataset, a 30 arcsecond global gridded population dataset representing global ambient human population distribution. This multivariable dasymetric model disaggregates census counts within administrative boundaries using ancillary data. Each country's distribution reflects cultural and socioeconomic patterns; manual validations yield a unique global dataset for assessing populations at risk. For over two decades, LSG has been a standard for estimating populations at risk, aiding U.S. federal government, academia and humanitarian organizations. During disasters such as the 2004 Indian Ocean tsunami and the 2010 Haiti earthquake and geopolitical crises such as the Syrian civil war and the 2022 Russian invasion of Ukraine, LSG supported scientific and operational communities in emergency response and recovery. In 2022, LSG datasets from 2000 onward were made publicly available through ORNL's LandScan Portal. This data descriptor details our methodology and the application of geospatial science and machine learning to geographic and demographic data, highlighting uses in urban resiliency, emergency management, disaster response, and human health and security.

Topics & Concepts

Geospatial analysisGeographyCensusPopulationGovernment (linguistics)CartographyRegional scienceEnvironmental resource managementEnvironmental healthEnvironmental scienceMedicinePhilosophyLinguisticsImpact of Light on Environment and HealthHuman Mobility and Location-Based AnalysisData-Driven Disease Surveillance