In this paper, we introduce a new spatially constrained clustering problem called the max-p-regions problem. It involves the clustering of a set of geographic areas into the maximum number of homogeneous regions such that the value of a spatially extensive regional attribute is above a predefined threshold value.We formulate the max-p-regions problem as a mixed integer programming (MIP) problem, and propose a heuristic solution.