Using spatial interpolation models to predict residential property market prices
Property valuation is considered to be an important research field for significant production factors such as investors and businesses. In its simplest form, valuation is the determination of the property transaction price on a specific date. Up to now, a wide range of valuation methods exists, according to the properties potential usage or the aim of the evaluation process. Given the spatial nature of the residential properties valuation problem, Geographic Information Systems are recognised as the most appropriate computer-based tool in order to provide price estimations and to support financial decisions. The paper at hand proposes a methodological framework that allows both private and public sector organizations to obtain property price estimations in sufficient time.
Given that comparative evaluation approach is considered the most preferable approach in property investment, a GIS-based approach is developed, aiming to obtain prices’ spatial distributions from a set of known estimations. As a result, various interpolation methods are implemented and compared in order to select the most suitable for the city of Xanthi, situated in north-eastern Greece.