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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-XLIX-B4-2026-41-2026</article-id>
<title-group>
<article-title>Integrating Microsoft Building Footprints and OpenStreetMap to Improve Building Representation</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Fonte</surname>
<given-names>Cidália C.</given-names>
<ext-link>https://orcid.org/0000-0001-9408-8100</ext-link>
</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>Patriarca</surname>
<given-names>Joaquim</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Duarte</surname>
<given-names>Diogo</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>University of Coimbra, Department of Mathematics, Largo D. Dinis, 3000 – 143 Coimbra, Portugal</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Institute for Systems Engineering and Computers at Coimbra- INESCC, Rua Sílvio Lima, 3030-790 Coimbra, Portugal</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>University of Coimbra, CISUC, Department of Informatics Engineering, Rua Sílvio Lima, 3030-290 Coimbra, Portugal</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>University of Coimbra, Department of Electrotechnical Engineering, Rua Sílvio Lima, 3030-790 Coimbra, Portugal</addr-line>
</aff>
<pub-date pub-type="epub">
<day>04</day>
<month>08</month>
<year>2026</year>
</pub-date>
<volume>XLIX-B4-2026</volume>
<fpage>41</fpage>
<lpage>47</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Cidália C. Fonte 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://isprs-archives.copernicus.org/articles/XLIX-B4-2026/41/2026/isprs-archives-XLIX-B4-2026-41-2026.html">This article is available from https://isprs-archives.copernicus.org/articles/XLIX-B4-2026/41/2026/isprs-archives-XLIX-B4-2026-41-2026.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLIX-B4-2026/41/2026/isprs-archives-XLIX-B4-2026-41-2026.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIX-B4-2026/41/2026/isprs-archives-XLIX-B4-2026-41-2026.pdf</self-uri>
<abstract>
<p>This paper investigates whether integrating the Microsoft Building Footprints (MBF) dataset with building footprints contributed by the OpenStreetMap (OSM) community can improve the spatial quality of building data. Specifically, we assess whether the resulting hybrid dataset enhances completeness and positional accuracy relative to the original MBF and OSM datasets. The evaluation was conducted in a study area encompassing both urban and rural environments, using 1:5,000 topographic cartography as the reference dataset. The merged MBF+OSM dataset successfully captured 87% of the buildings represented in the reference cartography, outperforming the standalone MBF and OSM datasets, which captured 81% and 70%, respectively. These results demonstrate that combining MBF and OSM footprints provides a more comprehensive representation of buildings and can offer a valuable alternative for applications requiring detailed, up-to-date building information.</p>
</abstract>
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