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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-XLIII-B4-2022-247-2022</article-id>
<title-group>
<article-title>A REVIEW OF URBAN HUMAN MOBILITY RESEARCH BASED ON CROWD-SOURCED DATA AND SPACE-TIME AND SEMANTIC ANALYSIS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kamel Basmenj</surname>
<given-names>S.</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>Li</surname>
<given-names>S.</given-names>

</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<ext-link>https://orcid.org/0000-0002-8244-5681</ext-link></contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Department of Civil Engineering, Ryerson University, 350 Victoria St., Toronto, Canada</addr-line>
</aff>
<pub-date pub-type="epub">
<day>01</day>
<month>06</month>
<year>2022</year>
</pub-date>
<volume>XLIII-B4-2022</volume>
<fpage>247</fpage>
<lpage>252</lpage>
<permissions>
<copyright-statement>Copyright: © 2022 S. Kamel Basmenj</copyright-statement>
<copyright-year>2022</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/isprs-archives-XLIII-B4-2022-247-2022.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLIII-B4-2022-247-2022.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLIII-B4-2022-247-2022.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLIII-B4-2022-247-2022.pdf</self-uri>
<abstract>
<p>Detecting urban human mobility patterns helps contributes to many urbanization issues, such as urban planning and traffic management. With the growing volume of crowd-sourced data, many studies have benefited from this data type to explore people’s daily movements and track their activities. There are several published review papers examing these studies on urban human mobility, with the focus on defining models and applications. However, the absence of a review of studies on urban human mobility that considered spatial, temporal, and semantic properties as well as crowd-sourced data together has limited the proliferation of semantic content in addressing mobility issues. In response, this paper provides a review on urban human mobility, including the data, models, and applications used in the selected articles. We defined particular inclusion and exclusion criteria to select the most relevant articles. We also included metadata analysis to overview the existing relevant literature. Finally, several research challenges and open issues are discussed.</p>
</abstract>
<counts><page-count count="6"/></counts>
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