PL EN


2013 | 21 | 2 | 72-82
Article title

Spatio-Temporal Analysis of the Real Estate Market Using Geographic Information Systems

Title variants
Languages of publication
EN
Abstracts
EN
The paper proposes the use of geographic information system tools for the analysis of spatial and temporal aspects of the real estate market. In particular, it focuses on the graphical presentation of the spatial distribution of price and its variability over time. The possibility of presenting an image of the spatial distribution of prices in the form of a 3D model is studied. A topographic surface is proposed as an alternative to traditional methods of spatial interpolation. Visual verification and numerical comparison have shown its superiority over other previously used methods. The best method of presenting four-dimensional data - the variation in time of the spatial distribution of house prices - was sought. The possibility of taking time into account as one of the attributes of the analyzed and presented objects, available in advanced GIS software, was used for this purpose. The undertaken activities were based on formal guidelines for the registration of time set out in the ISO 19100 series of standards dedicated to geographic information. Potential sources of data for this kind of analysis were identified and their availability was examined. The paper also presents how to build a spatial database on the basis of the available information, which is a starting material for further analysis. The carried out research demonstrated the benefits of the spatial approach to trends of changes in real estate prices, which can be used, among others, for mass appraisal.
Publisher
Year
Volume
21
Issue
2
Pages
72-82
Physical description
Dates
published
2013-06-01
online
2013-07-11
Contributors
  • AGH University of Science and Technology Department of Geomatics, geo-staszic@wp.pl
References
  • ANDRIENKO N., ANDRIENKO G., GATALSKY P., 2003, Exploratory spatio-temporal visualization: an analyticalreview, Journal of Visual Languages & Computing, 14(6), 503-541.[WoS]
  • CAYO M.R., TALBOT T.O., 2003., Positional error in automated geocoding of residential addresses, International journal of health geographics, 2(1):10.[Crossref][PubMed]
  • CHARIF O., OMRANI H., KLEIN O., SCHNEIDER M., TRIGANO P., 2010, A method and a tool for geocoding andrecord linkage, CEPS/INSTEAD Working Paper Series 2010-17.
  • CICHOCIŃSKI P., 2007, Zastosowanie metod kartograficznych i geostatystycznych do wstępnej analizy rynkunieruchomości, Studia i Materiały Towarzystwa Naukowego Nieruchomości, vol. 15, nr. 3-4, s. 155-166.
  • CICHOCIŃSKI P., 2011, Porównanie metod interpolacji przestrzennej w odniesieniu do wartości nieruchomości, Studia i Materiały Towarzystwa Naukowego Nieruchomości, vol. 19, nr 3, s. 120-132.
  • DENG J. S., WANG K., HONG Y., QI J. G., 2009, Spatio-temporal dynamics and evolution of land use change andlandscape pattern in response to rapid urbanization, Landscape and Urban Planning, 92(3), 187-198.[Crossref][WoS]
  • ESRI, 2011. ArcGIS Desktop 10 Help.
  • GŁÓWNY GEODETA KRAJU, 1998, Instrukcja techniczna K-1. Mapa zasadnicza, Główny Urząd Geodezji i Kartografii.
  • HILL M. J., DONALD G. E., 2003, Estimating spatio-temporal patterns of agricultural productivity infragmented landscapes using AVHRR NDVI time series, Remote Sensing of Environment, 84(3), 367-384.[Crossref]
  • HOPFER A., CELLMER R., 1997, Rynek Nieruchomości, ART Olsztyn.
  • KARIMI H.A., DURCIK M., RASDORF W., 2004, Evaluation of uncertainties associated with geocodingtechniques, Computer-Aided Civil and Infrastructure Engineering 19, pp.170-185.[Crossref]
  • KRAAK M.-J., MACEACHREN A.M., 1994, Visualization of spatial data's temporal component, Proceedings, Spatial Data Handling, Advances in GIS Research, Edinburgh, Scotland, 5-9, September, 1994, IGU
  • PEUQUET D.J., 2001, Making space for time: Issues in space-time data representation, GeoInformatica, 5(1), 11-32.[Crossref]
  • PN-EN ISO 19108:2010, Informacja geograficzna -- Schemat czasowy.
  • REKOWSKI M., 1995, Wprowadzenie do mikroekonomii, Polsoft.
  • ROZPORZĄDZENIE MINISTRA ADMINISTRACJI I CYFRYZACJI z 9 stycznia 2012 r. w sprawie ewidencjimiejscowości, ulic i adresów, Dz. U. z 2012 r., poz 125.
  • TOBLER W., 1970, A Computer Movie Simulating Urban Growth in the Detroit Region, Economic Geography, 46, 2 (1970), pp. 234-240.[Crossref]
  • Ustawa z 4 marca 2010 r. o infrastrukturze informacji przestrzennej, Dz. U. nr 76, poz. 489.
  • VIEIRA V.M., HOWARD G.J., GALLAGHER L.G., TONY FLETCHER T., 2010, Geocoding rural addresses ina community contaminated by PFOA: a comparison of methods, Environmental Health, 9:18.[Crossref][WoS]
  • YAO X., 2003, Research issues in spatio-temporal data mining, In White paper submitted to the University Consortium for Geographic Information Science (UCGIS) workshop on Geospatial Visualization and Knowledge Discovery, Lansdowne, Virginia, Nov (pp. 18-20).
  • ZANDBERGEN P.A., 2007, Influence of geocoding quality on environmental exposure assessment of childrenliving near high traffic roads, BMC Public Health 2007, 7:37.[PubMed][Crossref][WoS]
  • ZANDBERGEN P.A., 2008, A comparison of address point, parcel and street geocoding techniques, Computers, Environment and Urban Systems 32 (2008) 214-232.[WoS]
  • ZANDBERGEN P.A., 2011, Influence of street reference data on geocoding quality, Geocarto International vol. 26, no. 1, February 2011, 35-47.
  • ZIMMERMAN D.L., Li J., 2010, The effects of local street network characteristics on the positional accuracy ofautomated geocoding for geographic health studies, International Journal of Health Geographics 2010, 9:10.[Crossref][PubMed][WoS]
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.doi-10_2478_remav-2013-0019
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