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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-XLVIII-4-W4-2022-169-2022</article-id>
<title-group>
<article-title>DEVELOPMENT AND TESTING OF THE CITYJSON ENERGY EXTENSION FOR SPACE HEATING DEMAND CALCULATION</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Tufan</surname>
<given-names>Ö.</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>Arroyo Ohori</surname>
<given-names>K.</given-names>
<ext-link>https://orcid.org/0000-0002-9863-0152</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>León-Sánchez</surname>
<given-names>C.</given-names>
<ext-link>https://orcid.org/0000-0002-9696-7229</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Agugiaro</surname>
<given-names>G.</given-names>
<ext-link>https://orcid.org/0000-0002-2611-4650</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</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="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Delft University of Technology, Faculty of Architecture and the Built Environment, the Netherlands</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>3D Geoinformation group, Delft University of Technology, Faculty of Architecture and the Built Environment, the Netherlands</addr-line>
</aff>
<pub-date pub-type="epub">
<day>14</day>
<month>10</month>
<year>2022</year>
</pub-date>
<volume>XLVIII-4/W4-2022</volume>
<fpage>169</fpage>
<lpage>176</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2022 Ö. Tufan et al.</copyright-statement>
<copyright-year>2022</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/XLVIII-4-W4-2022/169/2022/isprs-archives-XLVIII-4-W4-2022-169-2022.html">This article is available from https://isprs-archives.copernicus.org/articles/XLVIII-4-W4-2022/169/2022/isprs-archives-XLVIII-4-W4-2022-169-2022.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLVIII-4-W4-2022/169/2022/isprs-archives-XLVIII-4-W4-2022-169-2022.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVIII-4-W4-2022/169/2022/isprs-archives-XLVIII-4-W4-2022-169-2022.pdf</self-uri>
<abstract>
<p>3D city models are frequently used to acquire and store energy-related information of buildings for energy applications. In this context, CityGML is the most common data model, and the Energy ADE, one of its most complex extensions, provides a systematic way of storing detailed energy-related data in XML format. Contrarily, even though CityGML’s JSON-based encoding, CityJSON, has an extension mechanism, an energy-related CityJSON Extension is missing. This paper, therefore, presents the first results of the development of a CityJSON Energy Extension and space heating demand calculation is utilized as the use case. The simplified version of the Energy ADE, called the Energy ADE KIT profile, is used to create a semi-direct translation to the CityJSON Energy Extension. This Extension is then validated through the official validator of CityJSON and the use case, and improvements are made considering the validation results. The space heating demand is calculated according to the Dutch standard NTA 8800 for a subset of Rijssen-Holten in the Netherlands although the solar gains calculation requires further review. The results show that the final CityJSON Energy Extension provides full support for space heating demand calculations based on the NTA 8800 and eliminates the deep hierarchical structure of the Energy ADE. A comparison on CityJSON file sizes shows a 25.2 MB increase after the required input data is stored in a CityJSON + Energy Extension file, which is not significant considering the high amount of data stored in the file. Overall, this paper shows that the CityJSON Energy Extension could provide an easy-to-use alternative to the CityGML Energy ADE.</p>
</abstract>
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