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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-XLIX-B3-2026-1411-2026</article-id>
<title-group>
<article-title>Characterizing Wildland-Urban Interface Fire Typology and Climate Associations Across California, USA</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Su</surname>
<given-names>Huiyi</given-names>
<ext-link>https://orcid.org/0000-0002-0903-443X</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>Cao</surname>
<given-names>Pingting</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>Wu</surname>
<given-names>Ximei</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>Liang</surname>
<given-names>Lu</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xu</surname>
<given-names>Qingqing</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ju</surname>
<given-names>Yang</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Diao</surname>
<given-names>Jiaojiao</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ma</surname>
<given-names>Qin</given-names>
<ext-link>https://orcid.org/0000-0002-6995-6663</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>School of Geography, Nanjing Normal University, Nanjing, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>State Key Laboratory of Climate System Prediction and Risk Management, Nanjing, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Department of Landscape Architecture and Environmental Planning, University of California, Berkeley, USA</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Sierra Nevada Research Institute, University of California, Merced, USA</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>School of Geography and Ocean Science, Nanjing University, Nanjing, China</addr-line>
</aff>
<aff id="aff6">
<label>6</label>
<addr-line>Department of Integrative Biology, University of Guelph, Ontario, Canada</addr-line>
</aff>
<pub-date pub-type="epub">
<day>31</day>
<month>07</month>
<year>2026</year>
</pub-date>
<volume>XLIX-B3-2026</volume>
<fpage>1411</fpage>
<lpage>1417</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Huiyi Su 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-archives.copernicus.org/articles/XLIX-B3-2026/1411/2026/isprs-archives-XLIX-B3-2026-1411-2026.html">This article is available from https://isprs-archives.copernicus.org/articles/XLIX-B3-2026/1411/2026/isprs-archives-XLIX-B3-2026-1411-2026.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLIX-B3-2026/1411/2026/isprs-archives-XLIX-B3-2026-1411-2026.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIX-B3-2026/1411/2026/isprs-archives-XLIX-B3-2026-1411-2026.pdf</self-uri>
<abstract>
<p>California experiences some of the most intense wildfire activity globally, with substantial human casualties and economic losses that show accelerating trends. Existing research predominantly quantifies the relative contributions of anthropogenic factors and climate forcing to WUI fires at the aggregate level, yet overlooks the heterogeneity in fire initiation and propagation mechanisms arising from differences in ignition locations and dominant spread areas. Using multi-source data from California (2002&amp;ndash;2023), we classified WUI fires into four behavioral modes based on whether ignition sites and primary spread areas were located in the WUI: I-I (WUI ignition, WUI spread), I-W (WUI ignition, wildland spread), W-I (wildland ignition, WUI spread), and W-W (wildland ignition, wildland spread). We systematically analyzed size characteristics, inter-annual trends, fuel composition, and climate sensitivity across modes. Results revealed: (1) WUI fires accounted for 96.6% of total burned area from large fires, although only 12.2% of burned area fell within the WUI; both total and mean burned area increased significantly over the two-decade period. (2) Naturally-ignited WUI fires showed significantly delayed ignition dates, whereas human-caused fires occurred significantly earlier, with peaks in fire frequency during Independence Day, Labor Day, and Thanksgiving. (3) I-I fires were predominantly driven by anthropogenic factors with the highest proportion of shrubland fuel and the smallest mean size; W-W and I-W fires exhibited significant climate sensitivity, with I-W showing a higher rate of increase than W-W over the two decades. These findings reveal differentiated driving mechanisms of anthropogenic and climatic factors across WUI fire behavioral types, providing scientific evidence for stratified fire management strategies.</p>
</abstract>
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