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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLVI-4-W2-2021-103-2021</article-id>
<title-group>
<article-title>A VECTOR ANALYTICAL FRAMEWORK FOR POPULATION MODELING</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Moehl</surname>
<given-names>J. J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Weber</surname>
<given-names>E. M.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>McKee</surname>
<given-names>J. J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Oak Ridge National Laboratory, Oak Ridge, TN, USA</addr-line>
</aff>
<pub-date pub-type="epub">
<day>19</day>
<month>08</month>
<year>2021</year>
</pub-date>
<volume>XLVI-4/W2-2021</volume>
<fpage>103</fpage>
<lpage>108</lpage>
<permissions>
<copyright-statement>Copyright: © 2021 J. J. Moehl et al.</copyright-statement>
<copyright-year>2021</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLVI-4-W2-2021-103-2021.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLVI-4-W2-2021-103-2021.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLVI-4-W2-2021-103-2021.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLVI-4-W2-2021-103-2021.pdf</self-uri>
<abstract>
<p>We propose a vector alternative to the typical raster based population modeling framework. When compared with rasters, vectors are more precise, have the ability to hold more information, and are more conducive to areal constructs such as building and parcel outlines. While rasters have traditionally provided computational efficiency, much of this efficiency is reduced at finer resolutions and computational resources are more plentiful today. Herein we describe the approach and implementation methodology. We also describe the output data stack for the United States and provide examples and applications.</p>
</abstract>
<counts><page-count count="6"/></counts>
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