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Spatial Analytics and Data Visualization

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Handbook of e-Tourism

Abstract

Along with the growing availability of geospatial data generated with information and communications technologies, spatial analytics and data visualization have prevailed in e-tourism research. This chapter systematically reviews the application of spatial analytics and data visualization in tourism. Specifically, the chapter discusses various exploratory analytics, such as spatial network analysis, spatial clustering, point pattern analysis, ESDA, and sequence analysis, and explanatory analytics, such as spatial interaction model, spatial econometrics, and geographically weighted regression. Some popular geovisualization methods are discussed with examples of their e-tourism applications. Lastly, the chapter discusses several major challenges of spatial analytics and geovisualization, including tourist identification, temporal angle in addition to the spatial analysis, computation burden, and web-based GIS applications.

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Author information

Authors and Affiliations

  1. Department of Tourism and Hospitality Management, Temple University, Philadelphia, PA, USA

    Yang Yang

Authors
  1. Yang Yang
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Corresponding author

Correspondence to Yang Yang .

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Editors and Affiliations

  1. The Howard Feiertag Department of Hospitality and Tourism Management, Pamplin College of Business, Virginia Tech, Blacksburg, VA, USA

    Zheng Xiang

  2. Department of Economics, Geography, Law and Tourism, The European Tourism Research Institute, Mid-Sweden University, Östersund, Jämtland, Sweden

    Matthias Fuchs

  3. Annenberg School for Communication and Journalism, University of Southern California, Los Angeles, CA, USA

    Ulrike Gretzel

  4. Institute for Digital Transformation, Ravensburg-Weingarten University of Applied Sciences, Weingarten, Germany

    Wolfram Höpken

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Yang, Y. (2022). Spatial Analytics and Data Visualization. In: Xiang, Z., Fuchs, M., Gretzel, U., Höpken, W. (eds) Handbook of e-Tourism. Springer, Cham. https://doi.org/10.1007/978-3-030-48652-5_34

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