IDEAS home Printed from
   My bibliography  Save this paper

Experimental spatial modelling of commercial property stock using GIS


  • Paul Greenhalgh
  • Kevin Muldoon-Smith
  • Adejimi Adebayo
  • Josephine Ellis


This novel research project draws upon the experience of a small number of experimental research projects in seeking to extend some of the frontiers to the spatial modelling of commercial real estate markets. In so doing, it explores new ways of capturing, integrating, representing, illustrating and modelling commercial real estate data with other spatial variables.There is tacit understanding of the relationship between the distribution of commercial properties, and spatial factors such as proximity to footfall, transport and other infrastructure. However, there has been surprisingly little research that has been able to illustrate these tangled market relationships using spatial analyses, underpinned by empirical quantitative data. This research project has developed a methodology to visualise the distribution of rateable value, used as a proxy for the attractiveness of commercial property, across a pilot study area, in this case, the City of York, in North Yorkshire, England.The project has experimented with the use of grid squares to analyse geo-spatial relations of commercial real estate variables (such as, rental value, stock, vacancy, availability) with other spatial variables (such as, infrastructural facilities, transportation nodes). The project has confirmed that grid squares are more effective at representing data that are unevenly distributed across urban space at city level, than other artificial delineations, such as area postcodes, political boundaries or streets. The grid square approach can be further enhanced using 3D extrusions which facilitate simultaneous representation of an additional data characteristic, for example total stock combined with average rental value by location. Finally, modelling was conducted using hexagonal rather than grid squares, which revealed that hexagonal tiles are potentially more accurate, due to the proximity of data to the centroid of the tile (effectively losing the corners) and more efficacious at representing linear spatial patterns of of commercial property market data due to hexagons having 50% more directions of alignment than square tiles.

Suggested Citation

  • Paul Greenhalgh & Kevin Muldoon-Smith & Adejimi Adebayo & Josephine Ellis, 2018. "Experimental spatial modelling of commercial property stock using GIS," ERES eres2018_61, European Real Estate Society (ERES).
  • Handle: RePEc:arz:wpaper:eres2018_61

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    business rates; Commercial; Rateable value; retail property; Spatial Analysis;
    All these keywords.

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arz:wpaper:eres2018_61. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Architexturez Imprints (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.