In this paper we describe work on the automatic recognition of island structures. In an initial phase several test persons were asked to mark groups of islands that they perceived on test maps. Based on these experimental results the island structures were categorized with respect to size and shape, and their construction described using principles from Gestalt theory. Based on those descriptions of island structures we will present an algorithm for the detection of large groups of islands based on a Minimal Span- ning Tree (MST). Therefore, we apply split and merge operations on the MST. For the automated characterization of the shape and orientation of island groups we propose to use principal compo- nents obtained from a PCA. The results of the algorithm are then visually compared with the island groups previously marked by test persons and shortcomings of the approach are discussed.