Abstract
Regionalization is one of the major issues faced by spatial data mining while representing social and economic geography. The purpose of this paper is to develop a system that applies data mining techniques to study air quality distribution of Chennai, a metro city in India using vehicular networking and map the distribution to geographic locations for effective policy making. Three different hybrid clustering methods are analyzed for grouping sites into non-overlapping, contiguous and homogeneous regions. This paper also validates homogeneity of the regions formed and suggests future lines of research for improving these methods.
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