PAVEMENT MAINTENANCE STRATEGY SELECTION WITH THE APPLICATION OF GEOGRAPHICAL INFORMATION SYSTEM AS A SUPPORT TOOL: A CASE STUDY WOLAITA SODO CITY

Abstract

As a practical tool, the Geographical information system integrates data collection, management, analysis, and output presentation in Pavement Maintenance System. Urban Pavement maintenance is one of the most crucial parts of the complete road system and has to be given the attention it deserves. There is no multi-criteria decision-making process, such as the analytic hierarchy process, to prioritize road sections for maintenance activities; There are many GIS techniques to improve maintenance and rehabilitation activities, such as dynamic segmentation and weighted overlay analysis, but not applied in pavement management activities. After the problems were identified, goals were formulated to fill the gap and increase the benefit gained from using GIS software. The objective of research is pavement maintenance strategy selection with application of GIS as a support tool of Wolaita Sodo city. The research tries to fill the gap of City problems identified during the interview and the questionnaire response. Spatial data was collected from the field using GPS and then correlated in GIS with the road condition index using the join tool. In the city’s, 16 route sections were selected using the purposive sampling method and the questionnaires were distributed to engineers, to obtain factors that influence the prioritization of pavement segment for maintenance work. Result of PCI analysis from paver system and weight of each criterion obtained using AHP approach calculated by IDRISI software for maintenance prioritization. From weight overlay analysis result the 16 route section were ranked into three category’s R-1,R-2,R-4 and R-12 high priority(Poor); R-7,R9 and R-16 have medium priority (Fair) and R-3,R-5,R-6,R-10,R-11,R-13,R-14 and R-15 have low priority (Good pavement condition). Hence by considering multi criteria’s to prioritize the road sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches. Finally the conclusion drawn that the developed Statistical Analysis of Paver Pavement Life Prediction model and Maintenance Priority Index works sufficiently and yields adequate output for providing accurate decisions. Lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.