Suchergebnisse

Provides an outline of research seeking to apply to computer assisted mass appraisal (CAMA) model capable of use within a geographic information system (GIS). The end product will be a working GIS/valuation integrated model. The model, in an operational context, can be utilized for property taxation purposes, to facilitate the rating and revaluation of residential properties in Northern Ireland. As the value of land and property is a function of economic, legal, physical and locational factors, consequently access to comprehensive, reliable and up‐to‐date transaction evidence is a prerequisite to property valuation. Valuation techniques depend on the collection and analysis of relevant data. Historically, the application of these techniques took place within a non‐spatial environment. Ultimately, market data support any estimate of value. Data searches and collection can prove both time consuming and expensive in relation to the fee earning potential of a valuation report. GIS can facilitate, in a spatial and aspatial context, the storage, manipulation and analysis of data, in a fraction of the time previously required. Current techniques for the mass appraisal of property, and for the prediction of residential property values, can be enhanced by utilizing the data handling capacity of GIS. Integration of a mass appraisal model within a GIS will add value to the valuation process.

The aim of this paper is to attempt to measure the effect of location on residential house prices and to endeavour to integrate spatial and aspatial data in terms of developing a hybrid predictive model. The research methodology investigates the traditional hedonic approach to modelling location using multiple regression techniques. Alternative approaches are considered which specifically model the spatial distribution of house prices with the objective of developing location adjustment factors. These approaches are based on the development of surface response techniques such as inverse distance weighting and universal kriging. The results generated from the surfaces created are then calibrated within MRA.