Surface Defect Detection of Nanjing City Wall Based on UAV Oblique Photogrammetry and TLS

Abstract

Ancient architecture, with its long history, has a high cultural value, artistic achievement, and scientific value. The Nanjing City Wall was constructed in the mid-to-late 14th century, and it ranks first among the world’s city walls in terms of both length and size, whether historically or in the contemporary era. However, these sites are subject to long-term degradation and are sensitive to disturbances from the surrounding landscape, resulting in the potential deterioration of the architecture. Therefore, it is urgent to detect the defects and repair and protect Nanjing City Wall. In this paper, a novel method is proposed to detect the surface defects of the city walls by using the unmanned aerial vehicle (UAV) oblique photogrammetry and terrestrial laser scanning (TLS) data. On the one hand, the UAV oblique photogrammetry was used to collect the image data of the city wall, and a three-dimensional (3D) model of the wall was created using the oblique images. With this model, 43 cracks with lengths greater than 30 cm and 15 shedding surfaces with an area greater than 300 cm2 on the wall can be effectively detected. On the other hand, the point cloud data obtained by TLS were firstly preprocessed, and then, the KNN algorithm was used to construct a local neighborhood for each sampling point, and the neighborhood was fitted using the least squares method. Next, five features of the point cloud were calculated, and the results were visualized. Based on the visualization results, surface defects of the wall were identified, and 18 cracks with lengths greater than 30 cm and 5 shedding surfaces with an area greater than 300 cm2 on the wall were detected. To verify the accuracy of these two techniques in measuring cracks, the coordinates of some cracks were surveyed using a prism-free total station, and the lengths were calculated. The root mean square error (RMSE) of crack lengths based on the UAV oblique photogrammetry model and TLS point cloud model were calculated to be 0.73 cm and 0.34 cm, respectively. The results of the study showed that both techniques were able to detect the defects on the wall surface, and the measurement accuracy could meet the accuracy requirements of the surface defect detection of the city wall. Considering their low cost and high efficiency, these two techniques provide help for the mapping and conservation of historical buildings, which is of great significance for the conservation and repair of ancient buildings.