LandScan is one of ORNL’s flagship datasets — the community standard for human dynamics and distribution modeling. It’s part of a proud heritage that started decades earlier.
“Population modeling has been a component of the Lab’s research and development efforts since the 1970s,” said Eddie Bright, retired ORNL scientist. “And in the early 1980s, we began working on detailed population distributions around all of the nuclear power plants in the U.S. for the Nuclear Regulatory Commission — this was post-Three Mile Island incident — and also for certain naval bases.”
Their research produced detailed population estimates for rings out to 10 miles from these sites. For consequence analysis and potential emergency response efforts, the team knew a uniform distribution of census counts would be useless.
Instead, Bright and his colleagues conducted a labor-intensive form of dasymetric modeling that would prove useful when the LandScan project came about some 15 years later.
“We manipulated existing census data to move people out of areas where we knew they were not living, such as lakes and really steep slopes, and moved them to areas where they most likely lived — cities, suburban areas and along rural roads,” Bright said. “This analysis seems simple now, but this was before national digital databases of land cover, roads, et cetera. We hand digitized various features from topographic maps and aerial photographs.”
Their work eventually drew interest from other federal agencies and ultimately grew into LandScan. Now, for the first time in the project’s history, the full suite of LandScan products — USA, Global and HD — are available publicly as open-source datasets.
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