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Remote sensing technology is increasingly recognized as a valuable post-earthquake damage assessment tool. Recent studies performed by research teams in the United States, Japan, and Europe have demonstrated that building damage sustained in urban environments can be identified through analysis of optical imagery and synthetic aperture radar (SAR) data. Damage detection using automated change detection algorithms will soon facilitate the scaling and prioritization of relief efforts, as well as the monitoring of the recovery operations. This paper introduces the use of an edge dissimilarity algorithm to quantify the extent of building damage.

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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 providing a convenient and efficient pavement inspection and management.