Objective Site Characterization Using Clustering of Piezocone Data

Abstract

Cluster analysis is a statistical method for grouping similar mathematical data sets and is used herein for delineating geostratigraphy from piezocone penetration test data. In terms of site characterization, clustering is an improvement over other statistical methods because no preliminary estimation of the inherent groups within the analyzed data is needed, and no overlapping is permitted between identified clusters. Clustering can accommodate single or multivariables and no data filtering is required. Its application to defining stratigraphic interfaces is illustrated using five case studies with layered profiles. Clustering is able to detect major changes within the stratigraphy not apparent by visually examining the trends of piezocone data or by available cone soil classification methods.