CLASSIFICATION OF THE CONDITION OF URBAN FLEXIBLE PAVEMENTS FROM IMAGES

Abstract

Flexible pavement evaluations, in a simplified way, are usually carried out manually by professionals on site. Thus, with the objective of analyzing different ways of surveying, this research seeks to verify the feasibility of using images of urban roads, obtained with a drone, to classify the condition of the surface. To assist in decision-making regarding maintenance and rehabilitation, a classification index was used, which identifies the quality of the pavement surface. It was possible to observe that the final condition of the pavement evaluated from the images registered a better classification in relation to the result of the survey by walking on the road, making the intervention measures and other observations different between the methods.