Abstract
Estimating the value of real estate has applications in fields as diverse as taxation, buying and renting properties, expropriation and urban regeneration. Determining the most objective, accurate and acceptable value for real estate by considering spatial criteria is therefore important. One stochastic method used to determine real estate values is ‘nominal valuation’. In this approach, criteria that may affect land value are subjected to various spatial analyses, and pixel-based value maps can be produced using GIS. Land value maps are in raster data format and need to be compared with the actual market values. Pixel-resolution analyses are required that depend on the selected grid dimensions. First of all, nominal value maps were produced using a nominal valuation model, using criteria for proximity, visibility and terrain. These were weighted in order to produce a nominal asset value-based map according to the ‘Best Worst Method’. Changes in the unit land values were examined for maps at various resolutions; a resolution of 10 metres emerged as the ideal pixel size for valuation maps.
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