Application of Classification Models and Spatial Clustering Analysis to a Sewage Collection System of a Mid-Sized City
Improving asset management of infrastructure systems has been an ongoing issue in the United States. Oliveira et al. (2010, 2011) developed several approaches to better understand the nature and location of pipe breaks in a drinking water distribution system. In this paper, we applied these two approaches to another infrastructure system..the pipe network of a sewage collection system. We first applied several classification approaches to analyze factors associated with higher density regions of deteriorating pipes in the sewage collection system. Relevant attributes that cause poorly conditioned sewer pipes could be found using this approach. We then applied the network version of a density-based clustering algorithm created by Oliveira et al. (2010), used to detect clustered regions of pipe breaks in water distribution systems, to detect hierarchically clustered regions in one of the high density regions of pipe deterioration in the same pipe network. This latter approach was found to provide useful information and additional insight about the local attributes that might be related to the high-density of pipe deterioration.