Małgorzata Renigier-Biłozor, Artur Janowski, Marek Walacik, Aneta Chmielewska
Effective comprehension of highly complex and spatially heterogenous property market requires its’ appropriate recognition. One of the most critical steps in property analyses and valuation procedures is the identification of the sub-markets as the fundamental comparable units. The biggest challenge in this case is to define the criteria of the basis indicating the similarity (homogeneity) of property markets area. The objective of the study was to propose methodology (called “HO-MAR”) that enables objective identification of the homogenous (similar/comparable) areas (zones) that could indicate location of similar groups of property transactions (representative properties) used either in individual valuations or AVMs. The authors propose utilization of automated solutions based on robust geo-estimation that enables high efficacy of property submarkets identification. Robust geo-estimation is guaranteed by merging semi-automated data mining methods (e.g. entropy theory, rough set theory, fuzzy logic) and geoprocessing activities (Gauss filter, geocoding and reverse geocoding, tessellation model with mutual spatial overlapping) concerning spatial relation database application.
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