• DocumentCode
    2708871
  • Title

    The effects of land´s proximity to river on spatial pattern of land prices in Tokyo metropolitan area using GIS: An analytical assessment

  • Author

    Eshliki, Sajad Alipour ; Angherabi, Bahram Abedini

  • Author_Institution
    Sch. of Archit. & Environ. Design, Iran Univ. of Sci. & Technol., Tehran, Iran
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper investigates the effects of land´s proximity to river at a distance of 200 meters on land prices in Tokyo metropolitan Area (TMA) using Geographic Information System (GIS). Line Density Function was employed to estimate the effects of distance and Geographically Weighted Regression (GWR) was applied for assessing the effects of land´s proximity to river. The result of GWR demonstrated that there have been different effects of land´s proximity to river in areas near Tokyo Bay and suburbs. In the first area, the proximity to river has positive effects on land prices, whereas in the second area, the proximity to river created negative impacts on land prices. It is also worth mentioning that in the first area, the error of measurement of the employed model for estimating the land price is more than its second counterpart signifying that other important factors in Tokyo Bay play roles in land prices.
  • Keywords
    geographic information systems; oceanographic regions; rivers; Geographic Information System; Tokyo Bay; Tokyo metropolitan Area; geographically weighted regression; land prices; land value assessment; line density function; randomization effect; river; spatial pattern; Cities and towns; Correlation; Data models; Estimation; Proximity effect; Rivers; Roads; Geographically Weighted Regression; Tokyo Metropolitan Area; land value assessment; proximity effect; randomization effect;
  • 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.2011.5980846
  • Filename
    5980846