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<front>
<journal-meta>
<journal-id journal-id-type="publisher">AGILE-GISS</journal-id>
<journal-title-group>
<journal-title>AGILE: GIScience Series</journal-title>
<abbrev-journal-title abbrev-type="publisher">AGILE-GISS</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">AGILE GIScience Ser.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2700-8150</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/agile-giss-7-27-2026</article-id>
<title-group>
<article-title>Measuring regional accessibility in urban form: A reproducible approach for urban analytics</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jehling</surname>
<given-names>Mathias</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>Kluwe</surname>
<given-names>Lucie</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kleiner</surname>
<given-names>Caspar</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Leibniz Institute of Ecological Urban and Regional Development (IOER), Dresden, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Dresden University of Technology (TUD), Dresden, Germany</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Technical University of Dortmund, Department of Spatial Planning, Dortmund, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>10</day>
<month>06</month>
<year>2026</year>
</pub-date>
<volume>7</volume>
<elocation-id>27</elocation-id>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Mathias Jehling et al.</copyright-statement>
<copyright-year>2026</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://agile-giss.copernicus.org/articles/7/27/2026/agile-giss-7-27-2026.html">This article is available from https://agile-giss.copernicus.org/articles/7/27/2026/agile-giss-7-27-2026.html</self-uri>
<self-uri xlink:href="https://agile-giss.copernicus.org/articles/7/27/2026/agile-giss-7-27-2026.pdf">The full text article is available as a PDF file from https://agile-giss.copernicus.org/articles/7/27/2026/agile-giss-7-27-2026.pdf</self-uri>
<abstract>
<p>Across countries, urban form is characterised by polycentric city-regions. This entails challenges in analysing urban structures with regard to their locations within these city-regions. In particular, research in regional and urban planning lacks medium-scale analytical approaches. We present a fully reproducible approach to describe regional location within urban form through accessibility. Our network-based approach relies on street-network data to derive a weighted centrality measure for each location in a region (Closeness Centrality). Considering a distance decay, we retrieve travel impediments for two modes of transportation: car-based transport and short-distance mobility (walking/cycling). To apply the approach for questions of urban analytics, we use the example of vacant lots. Given their key role for infill development, we analyse their distribution across four regions with distinct urban form characteristics. The results indicate that the approach allows for an analysis within a region to show the distribution of an urban structure of interest across different levels of centrality. The standardised description of a regional score of centrality also allows for comparing the distributions across regions. Our research contributes to align urban analytics closer to relevant conceptions of functional city-regions with urban cores, suburbs and peripheries.</p>
</abstract>
<counts><page-count count="7"/></counts>
</article-meta>
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