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  <titleInfo>
    <title>Ukraine LandScan HD data</title>
    <subTitle>LandScan High Definition (HD) data for Ukraine</subTitle>
  </titleInfo>
  <titleInfo type="alternative">
    <title>LandScan HD Ukraine v1.0</title>
  </titleInfo>
  <name type="corporate">
    <namePart>Oak Ridge National Laboratory.</namePart>
    <namePart>Geospatial Science and Human Security Division.</namePart>
    <namePart>Human Geography Group,</namePart>
    <role>
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    <namePart>United States Department of Defense,</namePart>
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  <genre authority="marcgt">map</genre>
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  <genre authority="rdacontent">cartographic image</genre>
  <genre authority="rdacontent">cartographic dataset</genre>
  <genre authority="lcgft">Maps.</genre>
  <genre authority="lcgft">Digital maps.</genre>
  <genre authority="lcgft">Raster data.</genre>
  <genre authority="lcgft">Data sets.</genre>
  <genre authority="lcgft">Geospatial data.</genre>
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    <dateIssued encoding="marc">2021</dateIssued>
    <issuance>monographic</issuance>
    <edition>v 1.0.</edition>
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  <originInfo eventType="publication">
    <place>
      <placeTerm type="text">[Oak Ridge, Tennessee] :</placeTerm>
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    <agent>
      <namePart>Oak Ridge National Laboratory, Geospatial Science and Human Security Division, Human Geography Group,</namePart>
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    <dateIssued>2021.</dateIssued>
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  <note type="statement of responsibility">Human Geography Group, Geospatial Science and Human Security Division, Oak Ridge National Laboratory; US DOD.</note>
  <note>Population (by estimate) as of November 1, 2021.</note>
  <note>LandScan HD for Ukraine was completed and released in January 2022. LandScan High Definition (HD) provides gridded population estimates at 3 arc-second (100m) resolution. Values for each LandScan HD cell represent an ambient (i.e. 24 hour average) population count estimate. In this way, the data capture the full potential activity space of people throughout the course of the day and night rather than just a residential location. The LandScan HD model incorporates current land use and infrastructure data from a variety of sources, applies facility occupancy estimates from ORNL's Population Density Tables (PDT) project, and leverages novel image processing algorithms developed at ORNL to rapidly map building structures and neighborhood areas using high-performance computing environments.</note>
  <note>LandScan HD is developed for individual countries around the world and provides gridded population estimates at 3 arc-second resolution. The LandScan HD model incorporates current land use and infrastructure data from a variety of sources, applies facility occupancy estimates from ORNL's Population Density Tables (PDT) project, and leverages novel image processing algorithms developed at ORNL to rapidly map building structures and neighborhood areas using high-performance computing environments. In this way, LandScan HD is developed using a 'bottom-up' approach where high resolution population estimates are not dependent on a recently conducted, high quality census. This approach is particularly useful for parts of the world that regularly experience large changes in population distribution due to rapid growth, natural hazards, or conflict.</note>
  <note>LandScan HD was developed for the U.S. Department of Defense and is used for rapid consequence and risk assessment as well as emergency planning and management.</note>
  <note>Source: National Geospatial-Intelligence Agency (NGA) via the EnhancedView Web-Hosting Service (EVWHS)/Global Enhanced GEOINT Delivery (G-EGD).</note>
  <subject>
    <cartographics>
      <scale>Scale not determined</scale>
      <coordinates>(E 22.1250000000°--E 40.2249999928°/N 50.4000000000°--N 44.1750000033°)</coordinates>
    </cartographics>
  </subject>
  <subject authority="lcsh">
    <topic>Population density</topic>
    <geographic>Ukraine</geographic>
    <genre>Maps</genre>
  </subject>
  <classification authority="lcc">G7101.E2</classification>
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    <url displayLabel="dataset" usage="primary display">https://hd.loc.gov/loc.gov/gdcdatasets.2021386802</url>
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  <identifier type="lccn">2021386802</identifier>
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