UAV Photogrammetry-Based 3D Road Distress Detection

The timely and proper rehabilitation of damaged roads is essential for road maintenance, and an effective method to detect road surface distress with high efficiency and low cost is urgently needed. Meanwhile, unmanned aerial vehicles (UAVs), with the advantages of high flexibility, low cost, and ea...

Full description

Saved in:
Bibliographic Details
Published inISPRS international journal of geo-information Vol. 8; no. 9; p. 409
Main Authors Tan, Yumin, Li, Yunxin
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 12.09.2019
Subjects
Accuracy
Algorithms
Automation
Cameras
Condition monitoring
Detection
digital surface model
Dimensions
Efficiency
Image reconstruction
Lasers
Low cost
Maneuverability
Manoeuvrability
Methods
Photogrammetry
point cloud
region growing algorithm
Rehabilitation
road distress detection
Road maintenance
Roads
Roads & highways
Software
Surveying
Three dimensional models
UAV
Unmanned aerial vehicles
Vehicles
Online AccessGet full text

Cover

More Information
Summary:The timely and proper rehabilitation of damaged roads is essential for road maintenance, and an effective method to detect road surface distress with high efficiency and low cost is urgently needed. Meanwhile, unmanned aerial vehicles (UAVs), with the advantages of high flexibility, low cost, and easy maneuverability, are a new fascinating choice for road condition monitoring. In this paper, road images from UAV oblique photogrammetry are used to reconstruct road three-dimensional (3D) models, from which road pavement distress is automatically detected and the corresponding dimensions are extracted using the developed algorithm. Compared with a field survey, the detection result presents a high precision with an error of around 1 cm in the height dimension for most cases, demonstrating the potential of the proposed method for future engineering practice.
ISSN:2220-9964
2220-9964
DOI:10.3390/ijgi8090409