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Progress on road pavement condition detection based on remote sensing monitoring

  • role： First author第一作者
  • Affiliation：

    Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China

  • Email：yfpan@pku.edu.cn
  • Introduction：潘一凡(1989—　)，男，博士研究生，研究方向为高光谱遥感、机器学习及LiDAR应用。E-mail：yfpan@pku.edu.cn
PAN Yifan1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China

  • Email：xfzhang@pku.edu.cn
  • Introduction：张显峰(1967—　)，男，副教授，研究方向为生态遥感、高光谱遥感应用。E-mail：xfzhang@pku.edu.cn
ZHANG Xianfeng1*,  
  • Affiliation：

    Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

TONG Qingxi12,  
  • Affiliation：

    Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China

SUN Min1,  
  • Affiliation：

    Remote Sening Center for Transportation, China Transport Telecommunications & Information Center, Beijing 100011, China

LUO Lun3

résumé

Roads are greatly essential in a transportation system. The quality of road pavements has a crucial impact on the driving safety, comfort, and the cost of the roads. Therefore, timely monitoring the pavement conditions to guarantee the secure operation of the traffic system is significant. Currently, time-consuming field investigations and manual measurements are the conventional and main methods to detect and evaluate the pavement conditions. However, many of these methods are destructive to the road surface. Many forms of remote sensing data without destructive effect on pavement were introduced with the support of computer technology and remote sensing to detect pavement conditions, such as digital images, LiDAR, and Radar. This paper reviewed the current research status and problems in pavement condition detection based on remote sensing technologies. Remote sensing, as a non-intrusive method, has the advantages of wide spatial coverage and objective and repeatable data with high temporal resolution that can be analyzed by computer conveniently. Generally, the methods can be divided into four types, namely, the multi-/hyper-remote sensing, the thermal remote sensing, the microwave remote sensing, and three dimensional reconstructionbased on the categories of the sensors used in pavement monitoring. The multi-/hyper- remote sensing primarily utilizes the reflective spectral information of the pavement, which contains three specific methods, namely, image processing method, the method based on the variation of pavement brightness, and spectral modeling. The thermal remote sensing is based on the radiation characteristics of pavement, which contains two methods based on the variation of pavement temperature and emissivity information. A microwave device called Ground Penetrating Radar (GPR) has been widely used to detect the pavement defects by road departments. The three dimensional information of the road surface can be acquired using photogrammetry and LiDAR systems to measure the elevation information of the deteriorated pavement. An experiment using the Multiple Endmember Spectral Mixing Analysis (MESMA) and WorldView-2 satellite image was conducted to evaluate the potential of remote sensing in aging pavement monitoring. Results show that all methods are greatly potential in pavement condition monitoring. However, these methods still have some limitations in terms of complexity, accuracy, and robustness. High resolution remote sensing technologies, such as sub-meter satellite data and low-altitude UAV systems, can achieve large-range and rapid detection of the road pavement conditions in question. The results of the case study in Liangxiang area of Beijing show that the road pavement aging conditions could be detected appropriately and mapped with higher accordance with the practical pavement conditions. Therefore, some ground remote sensing methods have been applied successfully in pavement condition detection, such as the Pavement Management Systems (PMS), GPR, and so on. However, spaceborne and airborne remote sensing methods still encounter problems (poor robustness and low accuracy etc.)on pavement condition detection. For instance, the applicability of pavement spectral analysis and airborne or satellite data in pavement condition detection applications still require additional future works. Finally, a case study using satellite multispectral data to monitor asphalt pavement aging conditions is presented to demonstrate the usefulness of remote sensing technology in road pavement monitoring and assessment.

mots-clés

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