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<front>
<journal-meta>
<journal-id journal-id-type="publisher">AGILE-GISS</journal-id>
<journal-title-group>
<journal-title>AGILE: GIScience Series</journal-title>
<abbrev-journal-title abbrev-type="publisher">AGILE-GISS</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">AGILE GIScience Ser.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2700-8150</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/agile-giss-7-33-2026</article-id>
<title-group>
<article-title>Measuring Urban Green Space Vitality through Multi-Source Visual and Textual Data: Integrating Social Media and Street- Level Imagery in London</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>Fangyuan</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>Wang</surname>
<given-names>Rui</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>Li</surname>
<given-names>Yijing</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>Shabrina</surname>
<given-names>Zahratu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Department of Geography, King’s College London, London, United Kingdom</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Department of Informatics, King’s College London, London, United Kingdom</addr-line>
</aff>
<pub-date pub-type="epub">
<day>10</day>
<month>06</month>
<year>2026</year>
</pub-date>
<volume>7</volume>
<elocation-id>33</elocation-id>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Fangyuan Li 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://agile-giss.copernicus.org/articles/7/33/2026/agile-giss-7-33-2026.html">This article is available from https://agile-giss.copernicus.org/articles/7/33/2026/agile-giss-7-33-2026.html</self-uri>
<self-uri xlink:href="https://agile-giss.copernicus.org/articles/7/33/2026/agile-giss-7-33-2026.pdf">The full text article is available as a PDF file from https://agile-giss.copernicus.org/articles/7/33/2026/agile-giss-7-33-2026.pdf</self-uri>
<abstract>
<p>Urban green space (UGS) vitality reflects actual public engagement rather than mere spatial provision. However, limited research has examined how micro-scale environmental characteristics shape participation intensity. This study investigates the relationship between street-level environmental features and green space vitality using cross-platform social media data in London. Geotagged Flickr and Instagram posts were used as proxies for usage intensity. Environmental attributes were extracted from Google Street View imagery through semantic segmentation, including vegetation coverage, walkability, spatial enclosure, and facility elements. Ordinary Least Squares models were applied to assess associations between environmental variables and social media density. Results indicate that structural and facility-related features show stronger relationships with participation intensity than simple vegetation measures.</p>
</abstract>
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