Automatic Zonation of Urban Areas Based on the Similarity of H/V Spectral Ratios

Abstract

Abstract In this article we propose an automatic procedure that performs thezonation of urban areas based on a set of horizontal-to-vertical ( H/V ) spectral ratiosfrom ambient noise recordings collected at many measurement points. The techniquesearches for the connected areas where the similarity among the spectral ratios ismaximized. The problem is posed as one of the optimal partitioning of the Delaunaytriangulation of the available measurement points. The technique explores and triesto partition some random variations of a Euclidean minimum spanning tree of thetriangulation. The optimization is performed using a genetic algorithm.Thetechniqueis applied to the zonation of the town of Vittorio Veneto in northeastern Italy and toa synthetic data set that tries to simulate the effects of some typical geological con-ditions.Introduction Seismic microzonation concerns the identification andmapping at local or site scales of areas having different po-tentials of hazardous earthquake effects, such as ground-shaking intensity, liquefaction, or landslide potential (Akiand Lee, 2003). It is commonly performed by experts takinginto account geophysical and geological information of dif-ferent natures. For ground-shaking intensity, a useful sup-port comes from the computation of horizontal-to-vertical(