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    <identifier>10.57760/sciencedb.34328</identifier>
    <datestamp>2025-12-29T18:22:06Z</datestamp>
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  <dc:date>2025-12-29</dc:date>
  <dc:title>Accessibility calculation data, along with pre- and post-carbon emission calculations and driving force analysis.</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.34328</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This study developed an &amp;quot;Entry to Emission Reduction&amp;quot; (E2A) model to evaluate how increasing entry density as a land saving strategy can coordinate the relationship between accessibility and reduced transportation emissions. The E2A model first optimizes the entrance location, quantifies accessibility changes and the resulting traffic emissions, and then uses interpretable machine learning methods to identify key morphological driving factors.&amp;nbsp;</dc:description>
  <dc:subject>Accessibility; Urban greenspace; traffic carbon emissions; urban decarbonization; urban planning</dc:subject>
  <dc:creator>Xincheng</dc:creator>
  <dc:creator>HuangQiyue</dc:creator>
  <dc:creator>YangXinyue</dc:creator>
  <dc:creator>Xizhi</dc:creator>
  <dc:creator>Yongze</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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