A multi-layer approach for the analysis of neighbourhood relations of polygons in remotely acquired images

In this letter we present a novel approach to extract topological features of polygonal networks, based on a multi-layer strategy; the motivation for this new development was the need to analyse the small-scale polygonal patterns observed on remotely sensed, high spatial resolution images of the surface of Mars. The major improvement of the algorithm consists of the distribution of polygons by layers in such a way that adjacent polygons cannot coexist on any given layer; this is followed by a global analysis of each layer to extract topological features. This novel approach can be indistinctively applied to any kind of tri and tetravalent network (presenting respectively three and four polygons at each vertex); its computational performance is extremely favourable when compared with previous approaches to this problem. The experimental dataset used to evaluate the algorithm consisted of 47 segmented polygonal networks seen on the surface of Mars and presenting very distinct visual appearances.