Progress on road pavement condition detection based on remote sensing monitoring
- Vol. 21, Issue 5, Pages: 796-811(2017)
Published: 2017-9 ,
Accepted: 17 May 2017
DOI: 10.11834/jrs.20176381
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Published: 2017-9 ,
Accepted: 17 May 2017
扫 描 看 全 文
潘一凡, 张显峰, 童庆禧, 孙敏, 罗伦. 2017. 公路路面质量遥感监测研究进展. 遥感学报, 21(5): 796–811
Pan Y F, Zhang X F, Tong Q X, Sun M and Luo L. 2017. Progress on road pavement condition detection based on remote sensing monitoring. Journal of Remote Sensing, 21(5): 796–811
公路路面质量的好坏对行车安全性、舒适性、经济性有重要的影响,因此路面状况的监测对于公路交通的健康发展具有重要意义。遥感技术作为一种新兴的数据采集手段,具有图像覆盖范围大、时效性强、信息客观现实、可重复使用、便于计算机分析等优势,为解决大范围的路面监测问题提供了强有力的支持。本文综述了现有基于遥感技术的道路路面状况监测方法,对其中存在的问题进行了分析和探讨。遥感技术在路面状况监测中具有广泛的应用前景,部分技术已经成熟并在公路养护作业中广泛使用,例如路面监测管理系统、探地雷达等;但是仍有部分技术还存在着鲁棒性差、精度较低等问题,还需要进一步的研究探索,如路面光谱分析、基于机载和星载的路面状况遥感监测应用的适用性等。本文最后给出了一种基于多端元混合像元分解模型的沥青路面老化状况监测与评估方法的研究实例。实验结果证明该方法可有效区分沥青公路路面混合像元中不同老化状况的沥青路面,为大范围路面老化状况监测提供了一种技术途径。
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.
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