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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-W2-2026-137-2026</article-id>
<title-group>
<article-title>Future Urban Heat Risk Assessment in Sydney: Integrating Satellite-Derived UTCI with Population Projections</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Nishino</surname>
<given-names>Akihiko</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>Zlatanova</surname>
<given-names>Sisi</given-names>
<ext-link>https://orcid.org/0000-0002-8766-0487</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>Kohtake</surname>
<given-names>Naohiko</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Built Environment, University of New South Wales, Sydney, NSW 2052, Australia</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Graduate School of System Design and Management, Keio University, Yokohama, Kanagawa, Japan</addr-line>
</aff>
<pub-date pub-type="epub">
<day>28</day>
<month>09</month>
<year>2026</year>
</pub-date>
<volume>XII-4/W2-2026</volume>
<fpage>137</fpage>
<lpage>144</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Akihiko Nishino 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-W2-2026/137/2026/isprs-annals-XII-4-W2-2026-137-2026.html">This article is available from https://isprs-annals.copernicus.org/articles/XII-4-W2-2026/137/2026/isprs-annals-XII-4-W2-2026-137-2026.html</self-uri>
<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/XII-4-W2-2026/137/2026/isprs-annals-XII-4-W2-2026-137-2026.pdf">The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/XII-4-W2-2026/137/2026/isprs-annals-XII-4-W2-2026-137-2026.pdf</self-uri>
<abstract>
<p>Urban heat stress poses an intensifying public health challenge in Australian cities, with Sydney facing increasingly severe summer thermal conditions. We present a reproducible framework for metropolitan-scale future heat risk assessment that integrates satellite-derived Universal Thermal Climate Index (UTCI) with demographic projections to 2031. We define the UTCI-Population Index (UPI), a composite indicator that quantifies population-weighted heat exposure at Travel Zone resolution across Sydney. We implemented two complementary satellite-based approaches: (1) trend-based extrapolation of the GloUTCI-M global UTCI dataset within Google Earth Engine to predict 2031 summer UTCI at 1 km resolution, and (2) a high-resolution spatial downscaling that combines ERA5-HEAT physically consistent UTCI at 28 km with Landsat 8/9 land surface temperature at 30 m, further refined by 3D solar radiation modelling and nine-station BOM bias correction to produce a pedestrian-level UTCI surface. The resulting UPI maps highlight priority zones where high projected thermal stress coincides with large future resident populations, supporting targeted heat adaptation planning. Approach 1 enables long-term metropolitan-scale future projection, while Approach 2 provides more than 30-fold higher spatial resolution for precinct-level intervention design. The two approaches are designed for future integration, with Approach 2&amp;rsquo;s downscaling pipeline applicable to Approach 1&amp;rsquo;s projected UTCI to yield pedestrian-scale 2031 projections; Approach 2 currently serves as a proof-of-concept and does not constitute a direct 2031 high-resolution forecast. The framework is scalable to other Australian and international cities facing growing heat risks under climate change.</p>
</abstract>
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