Clustering spatially correlated functional data

In this paper we discuss and compare two clustering strategies: a hierarchical clustering and a dynamic clustering method for spatially correlated functional data. Both the approaches aim to obtain clusters which are internally homogeneous in terms of their spatial correlation structure. With this scope they incorporate the spatial information into the clustering process by considering, in a different manner, a measure of spatial association ables to emphasize the average spatial dependence among curves: the trace-variogram function.