An approach to produce a GIS database for road surface monitoring

Fendi, Karwan Ghazi; Adam, Sarhat Mustafa; Kokkas, Nikolaos; Smith, Martin John

Abstract

Road Surface Monitoring (RSM) is the process of detecting the distress on paved or unpaved road surfaces. The primary aim of this process is to detect any distress (such as road surface cracks) at early stages in order to apply maintenance on time. Early detection of road cracks can assist maintenance before the repair costs becomes too high. Local authorities should have an effective and easy to use monitoring process in place across the road network to meet their obligations. The process of adding geographical identification metadata to the photos is called “Geo-tagging”. The proposed method in this work entails capturing GPS information when the photo is taken for the road surface distress, then attaching the photo to a map. The location disclosure in the act of geo-tagging of a photo provides qualities to the digital map. In that respect, a specific richness of the GIS dataset arises when they disclose the road surface distress photos. This paper proposes a system for establishing a GIS database consisting of geo-tagged photos for local authorities to automate the process of recording and reporting road surface distresses. This system is easy to use, cost-effective, deployable, and can be used effectively by local authorities.

Citation

Fendi, K. G., Adam, S. M., Kokkas, N., & Smith, M. J. (in press). An approach to produce a GIS database for road surface monitoring. . https://doi.org/10.1016/j.apcbee.2014.01.042

• Conference Name: 2nd International Conference on Civil Engineering (ICCEN 2013)
• End Date: Dec 14, 2013
• Acceptance Date: Sep 14, 2013
• Online Publication Date: Sep 9, 2014
• Deposit Date: Jul 19, 2016
• Publicly Available Date: Jul 19, 2016
• Journal: APCBEE Procedia
• Print ISSN: 2212-6708
• Electronic ISSN: 22126708
• Peer Reviewed: Peer Reviewed
• Volume: 9
• DOI: https://doi.org/10.1016/j.apcbee.2014.01.042
• Keywords: Road Surface Monitoring, Gis Database, Geo-Tagging
• Public URL: https://nottingham-repository.worktribe.com/output/736753
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S2212670814000438
• Additional Information: Published in: APCBEE Procedia 9, 2014. ISSN: 2212-6708. pp. 235-240, doi:10.1016/j.apcbee.2014.01.042
• Contract Date: Jul 19, 2016