000103663 001__ 103663
000103663 005__ 20240411071509.0
000103663 02470 $$ahttps://doi.org/10.48690/1524215$$2DOI
000103663 037__ $$aACQUIRED
000103663 041__ $$aeng
000103663 245__ $$aLandScan Global 2012
000103663 260__ $$bOak Ridge National Laboratory 
000103663 269__ $$a2013-07-01
000103663 336__ $$aImage
000103663 518__ $$d2012$$oCollected
000103663 520__ $$aAt approximately 1 km resolution (30" X 30"), LandScan is the finest resolution global population distribution data available and represents an ambient population (average over 24 hours). The LandScan algorithm uses spatial data and imagery analysis technologies and a multi-variable dasymetric modeling approach to disaggregate census counts within an administrative boundary. Since no single population distribution model can account for the differences in spatial data availability, quality, scale, and accuracy as well as the differences in cultural settlement practices, LandScan population distribution models are tailored to match the data conditions and geographical nature of each individual country and region.$$7Abstract
000103663 540__ $$aCC-BY-4.0$$uhttp://creativecommons.org/licenses/by/4.0/
000103663 650__ $$aEarth and related environmental sciences
000103663 6531_ $$aLandScan
000103663 6531_ $$asatellite imagery
000103663 6531_ $$ahuman geography 
000103663 655__ $$aGeospatial
000103663 7001_ $$aOak Ridge National Laboratory $$1https://ror.org/01qz5mb56$$2ROR$$4https://landscan.ornl.gov/$$5Other$$7Organizational
000103663 720__ $$eDataCollector$$7Organizational
000103663 85641 $$uhttps://landscan.ornl.gov/
000103663 909CO $$ooai:data.library.wustl.edu:103663$$pdataset
000103663 974__ $$aGlobal
000103663 975__ $$d-180$$e180$$f-90$$g90
000103663 980__ $$aGeospatial Data Collection