Regionalisation as Spatial Data Mining Problem: A Comparative Study
Regionalisation, an important problem from sociogeography. It could be solved by a classification algorithm for grouping spatial objects. A typical task is to find spatially compact and dense regions of arbitrary shape with a homogeneous internal distribution of social variables. Grouping a set of homogeneous spatial units to compose a larger region can be useful for sampling procedures as well as many applications such as customer segmentation. It would be helpful to have specific purpose regions, depending on the kind of homogeneity one is interested in. In this paper, the authors perform comparative study on various regionalisation techniques available in literatures.