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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-XII-4-W1-2026-343-2026</article-id>
<title-group>
<article-title>Spatially Constrained Clustering Framework for Urban Heat Risk Zone Identification</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zabuska</surname>
<given-names>Agata</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>Vitanova</surname>
<given-names>Lidia Lazarova</given-names>
<ext-link>https://orcid.org/0000-0003-1789-3901</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Trendafilova</surname>
<given-names>Tereza</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>Petrova-Antonova</surname>
<given-names>Dessislava</given-names>
<ext-link>https://orcid.org/0000-0002-9920-8877</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>GATE Institute, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria</addr-line>
</aff>
<pub-date pub-type="epub">
<day>28</day>
<month>09</month>
<year>2026</year>
</pub-date>
<volume>XII-4/W1-2026</volume>
<fpage>343</fpage>
<lpage>350</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Agata Zabuska 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-annals.copernicus.org/articles/XII-4-W1-2026/343/2026/isprs-annals-XII-4-W1-2026-343-2026.html">This article is available from https://isprs-annals.copernicus.org/articles/XII-4-W1-2026/343/2026/isprs-annals-XII-4-W1-2026-343-2026.html</self-uri>
<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/XII-4-W1-2026/343/2026/isprs-annals-XII-4-W1-2026-343-2026.pdf">The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/XII-4-W1-2026/343/2026/isprs-annals-XII-4-W1-2026-343-2026.pdf</self-uri>
<abstract>
<p>This study developed a spatially constrained clustering (SCC) framework for identifying urban heat-risk zones by integrating environmental heat hazard, population exposure, socio-demographic vulnerability, and mitigation indicators. Heat risk was conceptualized as a multidimensional framework, and SCC was applied to derive geographically contiguous zones in Sofia, Bulgaria. The results revealed a dominant urban&amp;ndash;peripheral gradient in heat risk, with the urban core characterized by the co-occurrence of elevated thermal stress, high population density, and reduced mitigation capacity. While the SCC approach successfully identified spatially coherent and interpretable risk zones, the findings also suggest that additional variables and higher-resolution data are required to capture more detailed intra-urban differences. Overall, the proposed framework demonstrates the potential of integrating multidimensional geospatial data with the SCC approach to support urban heat-risk assessment and inform climate adaptation strategies.</p>
</abstract>
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