Setting the standard in population modeling
Setting the standard in population modeling
High-resolution population data is essential to effective disaster prevention and response—understanding how many people may be in danger from a weather event or natural disaster, who might be impacted by a resource scarcity or other anthropogenic activities, and how to efficiently deploy limited resources in response to a crisis.
The Human Geography group reveals the dynamic human landscape—at the planet, country, neighborhood, and building levels—to identify vulnerable populations and explore the impacts of weather events, geopolitical conflicts, or changes in governmental policies.
We're looking for you...to join our team!
We're looking for you...to join our team!
Members of Human Geography span a wide range of disciplines that bring a diverse perspective in support of population research. Our researchers hold bachelor’s, master’s, and PhDs and work as cultural and spatial analysts in addition to developing software needed for population distribution and occupancy datasets.
We always need talented researchers in the fields of linguistics, urban economics, anthropology, geography, earth science, spatial demography, remote sensing, and spatial data science.
From global to local scales
Global: LandScan
Global: LandScan
ORNL’s suite of LandScan datasets provide realistic, high-resolution, annually updated population distribution datasets to help consequence assessment, emergency response, and disaster recovery efforts around the globe. LandScan Global models capture an ambient distribution of the population and their sociocultural and economic activity throughout the course of the day and night. LandScan HD provides country-level population distribution tailored to the unique geography and data conditions of individual cities, countries, or regions. LandScan USA depicts the location of people in both space and time, including diurnal variations at 90m resolution.
Neighborhoods: UrbanPOP
Neighborhoods: UrbanPOP
ORNL’s UrbanPop model simulates realistic full populations with detailed demographic, cultural, and economic characteristics, as well as residential and workplace information. These demographically and spatially detailed population datasets have been used in several studies, from determining the effect of hurricane Sandy on the most at-risk residential populations within New York to understanding the effects of electricity outages on economically vulnerable populations in the Knoxville (TN) Metro Area.
Buildings: Population Density Tables
Buildings: Population Density Tables
Population Density Tables are a global, machine learning and statistically-driven data content management system that captures snapshots of human activity through ambient building occupancy probability estimates of people per 1000 square feet at the facility level for day, night, and episodic events at regional, national, and subnational levels across the planet. The PDT database has been used for emergency preparedness and response, population mapping, and environmental and socioeconomic applications.
Our Stories
Public release of LandScan population data aids humanitarian support
Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change
ORNL researchers quantified the shifts in routine daytime activities following safer at home orders.
Researchers anticipate and help prevent national security consequences of climate crises
