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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Annals</journal-id>
<journal-title-group>
<journal-title>ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Annals</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9050</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-annals-IV-2-W1-13-2016</article-id>
<title-group>
<article-title>THE MOST COMMON GEOMETRIC AND SEMANTIC ERRORS IN CITYGML
DATASETS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Biljecki</surname>
<given-names>F.</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>Ledoux</surname>
<given-names>H.</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>Du</surname>
<given-names>X.</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>Stoter</surname>
<given-names>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>Soon</surname>
<given-names>K. H.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Khoo</surname>
<given-names>V. H. S.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>3D Geoinformation, Delft University of Technology, Delft, the Netherlands</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Singapore Land Authority, Singapore</addr-line>
</aff>
<pub-date pub-type="epub">
<day>05</day>
<month>10</month>
<year>2016</year>
</pub-date>
<volume>IV-2/W1</volume>
<fpage>13</fpage>
<lpage>22</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2016 F. Biljecki et al.</copyright-statement>
<copyright-year>2016</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
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<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/IV-2-W1/13/2016/isprs-annals-IV-2-W1-13-2016.pdf">The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/IV-2-W1/13/2016/isprs-annals-IV-2-W1-13-2016.pdf</self-uri>
<abstract>
<p>To be used as input in most simulation and modelling software, 3D city models should be geometrically and topologically valid,
and semantically rich. We investigate in this paper what is the quality of currently available CityGML datasets, i.e. we validate the
geometry/topology of the 3D primitives (Solid and MultiSurface), and we validate whether the semantics of the boundary surfaces
of buildings is correct or not. We have analysed all the CityGML datasets we could find, both from portals of cities and on different
websites, plus a few that were made available to us. We have thus validated 40M surfaces in 16M 3D primitives and 3.6M buildings
found in 37 CityGML datasets originating from 9 countries, and produced by several companies with diverse software and acquisition
techniques. The results indicate that CityGML datasets without errors are rare, and those that are nearly valid are mostly simple
LOD1 models. We report on the most common errors we have found, and analyse them. One main observation is that many of these
errors could be automatically fixed or prevented with simple modifications to the modelling software. Our principal aim is to highlight
the most common errors so that these are not repeated in the future. We hope that our paper and the open-source software we have
developed will help raise awareness for data quality among data providers and 3D GIS software producers.</p>
</abstract>
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