Abstract
This paper considers the urban processes that real estate (RE) experts use in assessing the value of a certain property, based on characteristics of that property and its environment. The main objective is to illustrate the confluence of RE decisional processes and spatial analysis and to show how these techniques can be put to work together. This paper describes a software package specifically designed for supporting spatial analysis of urban data collections. This software can serve as a reference architecture for developing applications that support decisional processes in real estate. Based on geographical features, the computational environment supports appraisal of a wide range of real estate types and can also create analytical maps for use in developing plans and strategies. A case study demonstrates how the computational environment can improve the quality of the diagnosis of urban real estate in a region that has been selected for a prototype implementation.
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Argiolas, M., Dessì, N. (2011). Engineering Spatial Analysis in Real Estate Applications. In: Yin, H., Wang, W., Rayward-Smith, V. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2011. IDEAL 2011. Lecture Notes in Computer Science, vol 6936. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23878-9_40
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DOI: https://doi.org/10.1007/978-3-642-23878-9_40
Publisher Name: Springer, Berlin, Heidelberg
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