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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-XLII-2-W13-1539-2019</article-id>
<title-group>
<article-title>DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Fissore</surname>
<given-names>E.</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>Pirotti</surname>
<given-names>F.</given-names>
<ext-link>https://orcid.org/0000-0002-4796-6406</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-group><aff id="aff1">
<label>1</label>
<addr-line>CIRGEO - Interdepartmental Research Center of Geomatics, University of Padova, Viale dell’Università 16, Legnaro (PD), Italy</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>TESAF Department, University of Padova, Viale dell’Università 16, Legnaro (PD), Italy</addr-line>
</aff>
<pub-date pub-type="epub">
<day>05</day>
<month>06</month>
<year>2019</year>
</pub-date>
<volume>XLII-2/W13</volume>
<fpage>1539</fpage>
<lpage>1544</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2019 E. Fissore</copyright-statement>
<copyright-year>2019</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/XLII-2-W13/1539/2019/isprs-archives-XLII-2-W13-1539-2019.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-2-W13/1539/2019/isprs-archives-XLII-2-W13-1539-2019.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-2-W13/1539/2019/isprs-archives-XLII-2-W13-1539-2019.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-2-W13/1539/2019/isprs-archives-XLII-2-W13-1539-2019.pdf</self-uri>
<abstract>
<p>Using multiple sources of 3D information over buildings to go from building footprints (LOD0) to higher LODs in CityGML models is a widely investigated topic. In this investigation we propose to use a very common 2.5D product, i.e. digital terrain and surface models (DTMs and DSMs), to test how much they can contribute to improve a CityGML model. The minimal information required to represents a 3 dimensional space in an urban environment is the combination of a DTM, the footprints of buildings and their heights; in this way a representation of urban environment to define LOD1 CityGML is guaranteed. In this paper we discuss the following research questions: can DTMs and DSMs provide significant information for modelling buildings at higher LODs? What characteristics can be extracted depending on the ground sampling distance (GSD) of the DTM/DSM? Results show that the used DTM/DSM at 1&amp;thinsp;m GSD provides potential significant information for higher LODs and that the conversion of the unstructured point cloud to a regular grid helps in defining single buildings using connected component analysis. Regularization of the original point cloud does loose accuracy of the source information due to smoothing or interpolation, but has the advantage of providing a predictable distance between points, thus allowing to join points belonging to the same building and provide initial primitives for further modelling.</p>
</abstract>
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