• DocumentCode
    2709082
  • Title

    Spatial differential features of inbound tourists in Jiangsu, China

  • Author

    Lu, Shaojing ; Zhang, Jie ; Zhang, Honglei

  • Author_Institution
    Dept. of Land Resources & Tourism Sci., Nanjing Univ., Nanjing, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The spatial differential features of tourists are the fundamental of tourism spatial structure research. Though many literatures on this issue have offered some efficient approaches, spatial view has not been paid sufficient attention to in the statistical model for spatial correlation. To explore the variation and mechanism of tourist spatial difference, exploratory spatial data analysis (ESDA) has been employed, taking the data of inbound tourist arrivals of all the cities in Jiangsu province from 2001 to 2009. Box-Cox transform has been taken to normalizing the data before ESDA. The Global and Local spatial autocorrelation analysis has been employed to examine the spatial aggregation characteristics and measure tourist distribution differences and significance between cities. Detailed discussions are then made referring to the spatial aggregation and diffusion effect. Finally, the conclusions are obtained.
  • Keywords
    geographic information systems; statistical analysis; transforms; travel industry; Box-Cox transform; GIS; Jiangsu province; exploratory spatial data analysis; global spatial autocorrelation analysis; inbound tourist arrival; local spatial autocorrelation analysis; spatial correlation; spatial differential feature; statistical model; tourism spatial structure research; Aggregates; Cities and towns; Correlation; Economics; Indexes; Transforms; EDSA; GIS; inbound tourist; spatial autocorrelation analysis; spatial difference features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5980861
  • Filename
    5980861