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EN
Real estate is one of the most important aspect of our life and play significant role in global economy. Sooner or later, everyone has contact with properties that are place for life, work, investment, relax. That is why properties are part of many decision-making systems related to valuation, taxes, land planning and sustainable development of the areas. Analysis related to property market are based on many assumptions such as property homogeneity determination. The following paper presents proposal of utilization of automated solutions based on robust geo-estimation that enables high efficacy of property submarkets identification. The study is to propose the optimal solutions for initial part of the homogenous market analyses such as feature engineering, that enables unbiassed identification of the homogenous areas (zones). In this case the following methods based on robust geo-estimation/geoprocessing will be used: Gauss filter, geocoding and reverse geocoding, tessellation model and entropy theory.
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