Cluster analysis applied to engineering geological mapping

Cluster analysis of morphometric variable is reported in this paper to support characterization of rock masses and deposits. The first technique is related to fast mechanical characterization of bedrock and the second one on the mapping of the depth of superficial deposits. In order to extrapolate site-specific information to the whole study area two techniques are applied to morphometric space: supervised and unsupervised classifications through the algorithms maximum likelihood and ISODATA, respectively. The analysis of morphometric space with these techniques has provided significant results in order to discriminate bedrocks with different mechanical characteristics and the depth of superficial deposits.