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Spatial Modeling and Geovisualization of Rental Prices for Real Estate Portals

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Computational Science and Its Applications -- ICCSA 2016 (ICCSA 2016)

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Abstract

From a geoinformation science perspective real estate portals apply non-spatial methods to analyse and visualise rental price data. Their approach shows considerable shortcomings. Portal operators neglect real estate agents’ mantra that exactly three things are important in real estates: location, location and location [16]. Although real estate portals record the spatial reference of their listed apartments, geocoded address data is used insufficiently for analyses and visualisation, and in many cases the data is just used to “pin” map the listings. To date geoinformation science, spatial statistics and geovisualization play a minor role for real estate portals in analysing and visualising their housing data. This contribution discusses the analytical and geovisual status quo of real estate portals and addresses the most serious deficits of the employed non-spatial methods. Alternative analysing approaches from geostatistics, machine learning and geovisualization demonstrate potentials to optimise real estate portals´ analysing and visualisation capacities.

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Notes

  1. 1.

    Alexa.com measures the number of website visitors [1]. According to Alexa.com, the two most visited real estate portals in the UK and the US are Zillow.com and Trulia.com; Immobilienscout 24.de and Immowelt.de are the most visited portals in the German speaking countries.

  2. 2.

    Zillow’s “neighborhood polygons have been licensed under a Creative Commons license and can be downloaded for free via the portal’s website.

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Author information

Authors and Affiliations

  1. Department of Geography, University of Potsdam, Karl-Liebknecht-Strasse 24/25, 14476, Potsdam, Germany

    Harald Schernthanner, Hartmut Asche, Julia Gonschorek & Lasse Scheele

Authors
  1. Harald Schernthanner
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  2. Hartmut Asche
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  3. Julia Gonschorek
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  4. Lasse Scheele
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Corresponding author

Correspondence to Harald Schernthanner .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  5. Polytechnic University, Bari, Italy

    Carmelo M. Torre

  6. Monash University, Clayton, Victoria, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  9. Beijing University of Posts and Telecommunications, Beijing, China

    Shangguang Wang

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Schernthanner, H., Asche, H., Gonschorek, J., Scheele, L. (2016). Spatial Modeling and Geovisualization of Rental Prices for Real Estate Portals. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9788. Springer, Cham. https://doi.org/10.1007/978-3-319-42111-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-42111-7_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42110-0

  • Online ISBN: 978-3-319-42111-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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