Comparative evaluation of UAV photogrammetry and mobile laser scanner for flexible pavement failure detection in developing countries

Abstract

Flexible pavements constitute a critical infrastructure that, throughout its life cycle, faces degradation caused by climatic variables and traffic loads. This deterioration affects their mechanical properties, leading to cracks and failures that reduce their functionality and longevity. It is therefore imperative that advanced analytical methodologies are applied to identify the appropriate level of intervention to ensure their optimal serviceability. Recently, technological innovations have emerged that allow the detailed assessment of flexible pavements in an efficient manner, covering large areas in a short time. This research focuses on whether drone photogrammetry (UAV) or mobile laser scanning (MLS) is more appropriate for the diagnosis of surface imperfections in flexible pavements in the context of developing countries, as well as the impacts that its adoption could have on road assessment. The qualitative study is based on a literature review and uses the Choosing by Advantages (CBA) method to evaluate and compare the decisive qualities in the selection of technologies. The results indicate that the mobile laser scanner provides accurate topographic and geometric characterisation at the millimetre level. However, drone photogrammetry, standing out for its high flexibility, low cost and ease of operation, presents itself as the most viable solution for continuous road condition monitoring.