Modelling the value of location in the prediction of residential property value

Abstract

The important of location to effect property value is widely acknowledged. However, traditional approaches in quantifying location influence on property value modelling are unsatisfactory. Value Residual Surface (VRS) has been suggested as an alternative to resolving the difficulty in the traditional modelling of location influence on property values in a particular area. This paper discusses the use of GIS generated VRS for delineating residential location value factors in the multiple regression analysis (MRA) model. A sample of 125 single and double-storey residential properties was used to construct regression model. Residuals generated from location-blind model were used to construct VRS to develop location adjustment factors. The results showed that using VRS integrative has allowed a clearer spatial visual picture of the location influence to be captured at all level in the study area. And, the location factors influence to property value can be modelled in a more effective way.