Urban Regularity in PS point clouds

Man-made structures like urban areas are often characterized by geometrically simple and repeated forms. This leads to a preferred rectangular and regular alignment of objects like windows or balconies at facades of the majority of buildings in modern cities. In this paper we show how this regularity can be exploited for the challenging task of Synthetic Aperture Radar (SAR) scene description and demonstrate the applicability in a case study. We present a virtually parameter free method to segment a Persistent Scatterer point cloud which is based on spectral clustering theory. In a consecutive step we fit optimal lattices into the clustered PS sets to describe separate facades. This leads to an object based representation of the SAR data which allows for many new applications in the field of building monitoring and change detection in urban areas.