<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
        <Journal>
            <PublisherName>Scienceline Publications</PublisherName>
            <JournalTitle>Journal of Civil Engineering and Urbanism</JournalTitle>
            <ISSN>2252-0430</ISSN>
            <Volume>10</Volume>
            <Issue>4</Issue>
            <PubDate PubStatus="epublish">
             <Year>2020</Year>
             <Month>July</Month>
            </PubDate>
        </Journal>
        <ArticleTitle>Spatio-Temporal Understanding and Representation of Transformative
Urban Mobility and Trip Patterns, A Review</ArticleTitle>
        <FirstPage>35</FirstPage>
        <LastPage>41</LastPage>
        <ELocationID EIdType="url">https://www.ojceu.com/main/attachments/article/77/JCEU%2010(4)%2035-41,%202020.pdf</ELocationID>
        <Language>EN</Language>
        <AuthorList>
			<Author>
                <FirstName>Arian</FirstName>
                <MiddleName> </MiddleName>
                <LastName>Behradfar</LastName>
                <Affiliation>Department of Geomatics and Spatial Information Engineering, College of Engineering, University of Tehran, Tehran 1439957131, Iran</Affiliation>
			</Author>
			<Author>
                <FirstName>Soheil</FirstName>
                <MiddleName> </MiddleName>
                <LastName>Mohammadi</LastName>
                <Affiliation>Department of Naval, Electrical, Electronic and Telecommunications Engineering, DITEN, University of Genoa, Genoa 16126, Italy</Affiliation>
			</Author>
			        </AuthorList>
            
        <Abstract>The rapid development in transport system monitoring provide planners and researchers with new opportunities to
understand the trends of mobility patterns in urban areas, known as transformation of urban mobility. It brings
businesses and cities together to implement system-level integrated initiatives to conducting urban mobility and
transport system toward a more efficient future. As a result, identification of the trip patterns and spatio-temporal
dependencies in urban areas requires a comprehensive understanding of high-dimensional human mobility
dynamics. These emerging trends need a framework to identify urban mobility patterns from a spatio-temporal
perspective that includes various visualized representation of mobility patterns and travel behaviour. The main
purpose of this study is to investigate different data sources and methods used in the literature to obtain the
proposed patterns in urban areas. The spatio-temporal models evaluated in this review can be used in a wide range
of mobility studies suggesting trip patterns and related variables are significantly affected by spatial and non-spatial
impacts.</Abstract>
        <KeywordsList>
                <Keyword>Transformation of urban mobility</Keyword>
                <Keyword>Mobility flows</Keyword>
		<Keyword>Trip patterns</Keyword>
		<Keyword>spatio-temporal dependencies</Keyword>
		<Keyword>spatialanalysis</Keyword>
	</KeywordsList>
 </Article>
</ArticleSet>
