GIS-based automated management of highway surface crack inspection system

Hung-Chi Chung; Masanobu Shinozuka; Tony Soeller; Roberto Girardello

doi:10.1117/12.539229

14 July 2004 GIS-based automated management of highway surface crack inspection system

Hung-Chi Chung, Masanobu Shinozuka, Tony Soeller, Roberto Girardello

Author Affiliations +

Proceedings Volume 5395, Nondestructive Detection and Measurement for Homeland Security II; (2004) https://doi.org/10.1117/12.539229
Event: NDE for Health Monitoring and Diagnostics, 2004, San Diego, CA, United States

Abstract

An automated in-situ road surface distress surveying and management system, AMPIS, has been developed on the basis of video images within the framework of GIS software. Video image processing techniques are introduced to acquire, process and analyze the road surface images obtained from a moving vehicle. ArcGIS platform is used to integrate the routines of image processing and spatial analysis in handling the full-scale metropolitan highway surface distress detection and data fusion/management. This makes it possible to present user-friendly interfaces in GIS and to provide efficient visualizations of surveyed results not only for the use of transportation engineers to manage road surveying documentations, data acquisition, analysis and management, but also for financial officials to plan maintenance and repair programs and further evaluate the socio-economic impacts of highway degradation and deterioration. A review performed in this study on fundamental principle of Pavement Management System (PMS) and its implementation indicates that the proposed approach of using GIS concept and its tools for PMS application will reshape PMS into a new information technology-based system that can provide convenient and efficient pavement inspection and management.

Citation Download Citation

Hung-Chi Chung, Masanobu Shinozuka, Tony Soeller, and Roberto Girardello "GIS-based automated management of highway surface crack inspection system", Proc. SPIE 5395, Nondestructive Detection and Measurement for Homeland Security II, (14 July 2004); https://doi.org/10.1117/12.539229

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