GIS Research Infrastructure for Spatial Analysis of Real Estate Markets

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Abstract
This article outlines the type of research infrastructure needed to complement existing commercial Geographic Information System (GIS) environments to perform state-of-the-art spatial analysis of real estate markets. The emphasis is on the relevance of a spatial data analytic perspective and on the operational setting in which this can be implemented. These ideas are part of an overall framework that distinguishes four spatial analysis functions: selection, manipulation, exploration, and confirmation. The relevance of spatial econometrics and spatial statistics for empirical analysis of real estate markets is illustrated with respect to three specific examples: efficient survey design, pattern recognition, and the estimation of hedonic models. Particular attention is paid to the linkages between the spatial data analytic functions and the more traditional GIS analysis functions, both conceptually and in existing software environments.