Selection of the area to be established for unmanned aerial vehicles to detect damage on roads with remote sensing techniques using GİS and multi-criteria decision making methods

Road maintenance is an essential to keeping roads safe for drivers and pedestrians. Regular inspections and maintenance work preserve road quality, reduce the need for emergency repairs, and help to identify and resolve problems before they become safety hazards. Traditional road surface evaluation methods are expensive, time-consuming, and labor-intensive, making them limited in scope. Remote sensing techniques offer non-contact methods to quickly and effectively examine large areas, enabling frequent and comprehensive evaluations of transportation infrastructure. This study aims to detect road damage using unmanned aerial vehicles (UAVs) and transmit the data to a central hub via ground data terminals. Determining the optimal locations for these ground data terminals, which are critical for UAV communication, involves using multi-criteria decision analysis (MCDM) methods. Five criteria were evaluated using the Analytic Hierarchy Process (AHP): elevation, slope, aspect, proximity to settlements, and proximity to main roads. In a sample study area, site selection was conducted based on the defined criteria, and a suitability map was created using ArcMap software that incorporated all the criteria. This map illustrates the most suitable locations for the terminals on a single map. Integrating Geographic Information Systems (GIS) and remote sensing with MCDM ensures that ground data terminals are optimally placed, thereby optimizing data collection and transmission processes. This study underscores the importance of integrating UAVs and remote sensing techniques to enhance road maintenance efficiency and safety. The combination of GIS and MCDA methods enables faster, more efficient, and safer assessments of transportation infrastructure.