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    <responseDate>2026-10-13T11:37:51Z</responseDate>
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    <identifier>10.57760/sciencedb.35761</identifier>
    <datestamp>2026-01-28T10:19:54Z</datestamp>
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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:date>2026-01-28</dc:date>
  <dc:title>A set of historical road prediction path intersection data</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.35761</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset was constructed to support the validation of the historical road prediction model (LCGF) and contains spatial information on key historical transportation nodes within Datian County, Fujian Province. The data are primarily used to evaluate the alignment between the predicted ancient road network from the proposed model and actual historical path intersections. The spatial coverage encompasses the entire area of Datian County, with approximate geographic coordinates ranging from&amp;nbsp;25&amp;deg;29&amp;prime;N to 25&amp;deg;51&amp;prime;N and 117&amp;deg;29&amp;prime;E to 118&amp;deg;03&amp;prime;E. The coordinate system is&amp;nbsp;WGS 1984 UTM Zone 50N, which is suitable for regional-scale spatial analysis and modeling. The nodes are derived from historical records spanning the Ming and Qing dynasties to the Republican period, predominantly reflecting the transportation network status of the region from the&amp;nbsp;19th to the mid-20th century. The data consist of static spatial points and do not possess temporal sequence attributes. The point locations were cross-verified and georeferenced using satellite imagery (Esri World Imagery) and surveying and mapping maps from the Republican era (1:50,000 topographic maps produced by the Survey Bureau of the Ministry of National Defense in 1947). The planar coordinate accuracy is better than&amp;nbsp;30 meters&amp;nbsp;at identifiable ground feature locations, while points situated in topographically complex or significantly altered areas may exhibit higher spatial uncertainty.</dc:description>
  <dc:subject>Historical road prediction; cost functions; geometric fusion; spatial analysis</dc:subject>
  <dc:creator>Lin Wang</dc:creator>
  <dc:creator>Yongze Song</dc:creator>
  <dc:creator>Yihang Xu</dc:creator>
  <dc:creator>Weitao Hou</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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