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Providing land value information from geographic data infrastructure by using fuzzy logic analysis approach

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  • Bovkir, Rabia
  • Aydinoglu, Arif Cagdas

Abstract

Effective management of land-related information aids in promoting sustainable land development in both urban and rural areas. Standardised and interoperable data is a key component of achieving successful land administration and applications. When different datasets are produced in an interoperable manner, various thematic applications can be performed easily and reliably. The concept of geographic data infrastructure (GDI) has emerged, with the purpose of developing geographic data standards and ensuring data interoperability. In this study, an extension model was designed using the Turkish national GDI for obtaining reliable land-related information produced by public institutions. In the model design, the thematic factors affecting the land and its value were considered in seven groups and evaluated separately. In this manner, standardised and reliable information regarding land produced by public institutions can be obtained by using a national GDI. Thereafter, a case study using fuzzy logic and geographical analysis techniques was performed to implement the model, as well as obtain thematic information and general value approximations supporting land administration. The resulting maps from the analysis reflected a close and logical tendency towards reality and the applied method was found to be effective for producing reliable and accurate land value maps. Using this model, the general trends and thematic value indexes regarding 23 criteria of land parcels can be determined and added to the parcel information for sharing through e-government services.

Suggested Citation

  • Bovkir, Rabia & Aydinoglu, Arif Cagdas, 2018. "Providing land value information from geographic data infrastructure by using fuzzy logic analysis approach," Land Use Policy, Elsevier, vol. 78(C), pages 46-60.
    • Handle: RePEc:eee:lauspo:v:78:y:2018:i:c:p:46-60
    DOI: 10.1016/j.landusepol.2018.06.040
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    References listed on IDEAS

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    1. Carlo Bagnoli & Halbert C. Smith, 1998. "The Theory of Fuzzy Logic and its Application to Real Estate Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 16(2), pages 169-200.
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    3. Marija Bogataj & Danijela Tuljak Suban & Samo Drobne, 2011. "Regression-fuzzy approach to land valuation," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(3), pages 253-265, September.
    4. Klaus Deininger & Harris Selod & Anthony Burns, 2012. "The Land Governance Assessment Framework : Identifying and Monitoring Good Practice in the Land Sector," World Bank Publications - Books, The World Bank Group, number 2376.
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    Cited by:

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    4. Thanh Le Huu Ngoc & Ngu Nguyen Huu, 2024. "Application of Hedonic Model to Determine Residential Land Valuation in Suburban Areas: The Case of Hue City, Vietnam," Real Estate Management and Valuation, Sciendo, vol. 32(2), pages 70-79.
    5. Falcone, Pasquale Marcello & De Rosa, Salvatore Paolo, 2020. "Use of fuzzy cognitive maps to develop policy strategies for the optimization of municipal waste management: A case study of the land of fires (Italy)," Land Use Policy, Elsevier, vol. 96(C).
    6. Sisman, S. & Aydinoglu, A.C., 2022. "A modelling approach with geographically weighted regression methods for determining geographic variation and influencing factors in housing price: A case in Istanbul," Land Use Policy, Elsevier, vol. 119(C).

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