Spatial Statistical Model for the Analysis of Poverty in Urban Areas

The paper analyses the concept of poverty through a multidimensional approach that uses multiple indicators to define a condition of poverty and allows to denote territorial areas and/or population subgroups characterized by situations of inequalities. The complexity of the poverty phenomenon thus poses the need to identify analytical techniques that allow poverty to be framed in a broader con-text, to improve knowledge of the problem and deal with it through specific economic and social in-terventions. The data analysed in this paper allowed the construction of three sets of indicators refer-ring to three areas of poverty: economic, social, and housing. Two methodologies were adopted to study the data. The first based on the Fuzzy approach that uses the technique of Fuzzy Sets to synthe-size and measure the incidence of relative poverty in the considered population starting from the sta-tistical information provided by a plurality of indicators. The second, based on a the DBSCAN meth-od for identifying dense areas.