Chapter
Apr 26, 2012

Spatial Data Management and Analysis in Sewer Systems' Condition Assessment: an Overview

Publication: Computing in Civil Engineering (2007)

Abstract

As a result of EPA consent orders to enforce sewer systems inspection, an unprecedented amount of data are being acquired and stored in municipal sewer authorities and departments. Also, new technologies have been developed to increase inspection efficiency, such as sonar and laser scanners, allowing more complete characterization of sewer attributes and allowing better inspection data acquisition. Furthermore, sewer systems data have been deposited in Geographical Information Systems allowing the manipulation and association of spatial and non-spatial attributes. This paper discusses the potential of applying spatial data mining tools for extracting relevant and non-trivial information from spatial databases. This application aims at providing better decision making support for inspecting and maintaining sewer pipelines. Initial analyses show that the lack of integration and consistency of these growing databases is the first limitation to be overcome in order to successfully adopt any data mining tool.

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Go to Computing in Civil Engineering (2007)
Computing in Civil Engineering (2007)
Pages: 391 - 398

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Published online: Apr 26, 2012

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D. Oliveira [email protected]
Ph.D. Candidate, Graduate Research Assistant, Department of Civil and Environmental Engineering, Carnegie Mellon University. E-mail: [email protected]
Ph.D. Candidate, Graduate Research Assistant, Department of Civil and Environmental Engineering, Carnegie Mellon University. E-mail: [email protected]
L. Soibelman [email protected]
Associate Professor, Department of Civil and Environmental Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA - 15213. E-mail: [email protected]
James H. Garrett, Jr. [email protected]
Ph.D. Candidate, Graduate Research Asst., Professor, Department of Civil and Environmental Engineering, Carnegie Mellon University; Department of Civil and Environmental Engineering, Carnegie Mellon University; 5000 Forbes Avenue, Pittsburgh, PA - 15213. E-mail: [email protected]

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