A temporal-contextual analysis of urban dynamics using location-based data

The dynamics of urban activities in Jerusalem were studied by analyzing a large-scale semantically rich movement dataset. The semantic enrichment process was based on coupling movement trajectories sampled by GPS loggers with contextual data derived from trajectory-based digital activity dairies. Although the utility of such procedures in generating trajectory-specific semantic data was noted before, their application stays limited. In this paper, we promote the utilization of these procedures by demonstrating that they are not only feasible but also important for mobility studies. We discuss the characteristics of the semantic enrichment process and the manner by which it was applied within the large-scale analysis of urban dynamics. This application uncovered a time- and context-dependent array of centers in Jerusalem, resulting in a semantically rich characterization of urban dynamics. Such characterization provides otherwise unobtainable insights crucial for urban analysis. Wider implications for movement studies may be derived, as this application demonstrates how diary-based enrichment approaches hold the potential to advance bridging the semantic gap in mobility research.

[1]  Jungyul Sohn.  Are commuting patterns a good indicator of urban spatial structure , 2005 .

[2]  Jürgen Symanzik,et al.  Extracting Semantics of Individual Places from Movement Data by Analyzing Temporal Patterns of Visits , 2013, COMP '13.

[3]  Vania Bogorny,et al.  Where Have You Been Today? Annotating Trajectories with DayTag , 2013, SSTD.

[4]  Felix Kling,et al.  When a city tells a story: urban topic analysis , 2012, SIGSPATIAL/GIS.

[5]  Masahisa Fujita,et al.  Multiple equilibria and structural transition of non-monocentric urban configurations , 1982 .

[6]  Randall Guensler,et al.  Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data , 2001 .

[7]  Carlo Ratti,et al.  Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis , 2006 .

[8]  Michael May,et al.  Semantic Annotation of GPS Trajectories , 2008 .

[9]  David I. Stern,et al.  Ethno-ideological segregation and metropolitan development , 1990 .

[10]  R. R. Hocking.  The analysis and selection of variables in linear regression , 1976 .

[11]  Renato Fileto,et al.  Analysis of Spatiotemporal Inconsistencies of Trajectories with Planned and Reported Tasks , 2014, GeoInfo.

[12]  David M. Mark,et al.  Extensions to Geographic Representations , 2005 .

[13]  G. Giuliano,et al.  SUBCENTERS IN THE LOS ANGELES REGION , 1991 .

[14]  Rodolphe Devillers,et al.  From Movement Data to Objects Behavior Using Semantic Trajectory and Semantic Events , 2014 .

[15]  John F. McDonald,et al.  Suburban Employment Centres: The Case of Chicago , 1994 .

[16]  Max J. Egenhofer,et al.  Modeling Moving Objects over Multiple Granularities , 2002, Annals of Mathematics and Artificial Intelligence.

[17]  Thomas Ertl,et al.  Semantic Enrichment of Movement Behavior with Foursquare–A Visual Analytics Approach , 2015, IEEE Transactions on Visualization and Computer Graphics.

[18]  Peter Vovsha,et al.  Global Positioning System–Assisted Prompted Recall Household Travel Survey to Support Development of Advanced Travel Model in Jerusalem, Israel , 2011 .

[19]  Daniel Villatoro,et al.  From Tweets to Semantic Trajectories: Mining Anomalous Urban Mobility Patterns , 2013, CitiSens.

[20]  M. Batty.  The Size, Scale, and Shape of Cities , 2008, Science.

[21]  Timothy F. Leslie,et al.  Identification and Differentiation of Urban Centers in Phoenix Through a Multi-Criteria Kernel-Density Approach , 2010 .

[22]  Chiara Renso,et al.  Annotating Trajectories by Fusing them with Social Media Users Posts , 2014, GeoInfo.

[23]  Stefano Spaccapietra,et al.  Semantic trajectories modeling and analysis , 2013, CSUR.

[24]  Dino Pedreschi,et al.  Unveiling the complexity of human mobility by querying and mining massive trajectory data , 2011, The VLDB Journal.

[25]  William Alonso,et al.  A THEORY OF THE URBAN LAND MARKET , 2005 .

[26]  Gillad Rosen,et al.  Whose Right to Jerusalem , 2014 .

[27]  Fabio Porto,et al.  A conceptual view on trajectories , 2008, Data Knowl. Eng..

[28]  Johanna Zmud,et al.  Household Travel Surveys with GPS , 2009 .

[29]  Tovi Fenster,et al.  A tale of two cities: Jerusalem and Tel Aviv in an age of globalization , 2005 .

[30]  Scott A. Bollens,et al.  Urban Planning amidst Ethnic Conflict: Jerusalem and Johannesburg , 1998 .

[31]  Shlomo Hasson.  Territories and identities in Jerusalem , 2001 .

[32]  Isabelle Thomas,et al.  Measuring urban polycentrism: a European case study and its implications , 2007 .

[33]  Francesco Chiodelli,et al.  Re-shaping Jerusalem: The transformation of Jerusalem’s metropolitan area by the Israeli barrier , 2013 .

[34]  Miriam Baglioni,et al.  How you move reveals who you are: understanding human behavior by analyzing trajectory data , 2012, Knowledge and Information Systems.

[35]  Henri L. F. de Groot,et al.  The consumer city , 2015 .

[36]  Gerben de Vries,et al.  Combining ship trajectories and semantics with the simple event model (SEM) , 2009, EiMM '09.

[37]  Ruojing W. Scholz,et al.  Detection of dynamic activity patterns at a collective level from large-volume trajectory data , 2014, Int. J. Geogr. Inf. Sci..

[38]  Noam Shoval,et al.  Tracking tourists in the digital age , 2007 .

[39]  A. Galton.  Space, Time, and the Representation of Geographical Reality , 2001 .

[40]  M. Barthelemy,et al.  From mobile phone data to the spatial structure of cities , 2014, Scientific Reports.

[41]  Chiara Renso,et al.  Inferring human activities from GPS tracks , 2013, UrbComp '13.

[42]  Davy Janssens,et al.  The Annotation of Global Positioning System (GPS) Data with Activity Purposes Using Multiple Machine Learning Algorithms , 2014 .

[43]  Allen G. Noble,et al.  Problems of reunified Jerusalem , 1988 .

[44]  M. Frankena,et al.  A bias in estimating urban population density functions. , 1978, Journal of urban economics.

[45]  Antti Vasanen.  Functional Polycentricity: Examining Metropolitan Spatial Structure through the Connectivity of Urban Sub-centres , 2012 .

[46]  Shih-Lung Shaw,et al.  Handling Disaggregate Spatiotemporal Travel Data in GIS , 2000, GeoInformatica.

[47]  J. Jacobs.  The Death and Life of Great American Cities , 1962 .

[48]  Carlo Ratti,et al.  Eigenplaces: Analysing Cities Using the Space–Time Structure of the Mobile Phone Network , 2009 .

[49]  Sungho Kim,et al.  An analysis on movement patterns between zones using smart card data in subway networks , 2014, Int. J. Geogr. Inf. Sci..

[50]  P. Katz.  The New Urbanism: Toward an Architecture of Community , 1993 .

[51]  M. Goodchild,et al.  National Center for Geographic Information and Analysis a Research Agenda for Geographic Information and Analysis , 2022 .

[52]  Haim Yacobi,et al.  Planning a bi-national capital: should Jerusalem remain united? , 2002 .

[53]  C. R. Marmolejo Duarte,et al.  Urban Structure and Polycentrism: Towards a Redefinition of the Sub-centre Concept , 2009 .

[54]  J. Mcdonald.  The identification of urban employment subcenters , 1987 .

[55]  Paolo Veneri,et al.  The Identification of Sub-centres in Two Italian Metropolitan Areas: a Functional Approach , 2013 .

[56]  J. Jacobs,et al.  Living Room: Rematerialising Home , 2008 .

[57]  Stefano Spaccapietra,et al.  Semantic trajectories: Mobility data computation and annotation , 2013, TIST.

[58]  Zbigniew Smoreda,et al.  Discovering urban and country dynamics from mobile phone data with spatial correlation patterns , 2015 .

[59]  Kees Maat,et al.  Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands , 2009 .

[60]  Stefano Spaccapietra,et al.  Trajectories and Their Representations , 2013, Mobility Data.