Esnek kaplama denetiminde GCP'ler kullanarak İHA kullanımının değerlendirilmesi: Filistin'deki kentsel yollar üzerine bir vaka çalışması

Since rehabilitation plans are developed based on the results of pavement condition assessments, It's a crucial component of contemporary pavement management systems. These methods create challenges for road maintenance and repair programs due to seasonal limitations, low accuracy, visual errors, time consumption, and high costs. Existing pavements need to be properly evaluated, and this requires ongoing, efficient monitoring using acceptable tools in all weather and traffic conditions. unmanned aerial vehicles (UAVs) offer a novel and intriguing option for a wide range of activities, including dam monitoring, road Inspection, and building 3D ground models and orthophoto, due to their high level of accessibility, low cost, and safety. This research aims to use the mentioned technology to assess the severity and type of asphalt damage. To achieve the research objectives, ground control points were used in the image processing of vertical photogrammetric mapping to reconstruct 3D road models, which were processed and analyzed using the Agisoft Photoscan software. through the Agisoft Photoscan software tool, the patch area, rut depth, and crack type located on the road pavement were detected and their dimensions were extracted. Compared to field surveys, the results of the detection provide high accuracy with an error of about ± 3 mm in the rut's depth, ± 2.44 cm² in the patches and potholes areas, and an accuracy of up to 96% in identifying cracked areas and the type of cracks in most cases. In conclusion, this study demonstrated the ability of ground control points to enhance the accuracy of the image of a drone for road distress extraction, especially in conditions where photographing is difficult from a low altitude and in critical weather and traffic conditions.