| 公路路面光谱特征分析与沥青路面老化遥感监测方法初探 |
| |
| 引用本文： | 金续,张显峰,罗伦,潘一凡,阳柯.公路路面光谱特征分析与沥青路面老化遥感监测方法初探[J].地球信息科学,2017,19(5):672-681. |
| |
| 作者姓名： | 金续 张显峰 罗伦 潘一凡 阳柯 |
| |
| 作者单位： | 1. 北京大学遥感与地理信息系统研究所,北京 1008712. 中国交通通信信息中心,北京 100011 |
| |
| 基金项目： | 国家自然科学基金面上基金项目“基于高光谱与无人机LiDAR的路面健康状况监测方法研究”（41571331）;高分项项目“公路交通领域军民融合应用示范”（GFZX0404080102） |
| |
| 摘 要： | 随着道路交通的快速发展,道路养护工作正变得日益繁重,如何快速获取道路路面健康状况信息,为公路养护部门提供技术支撑,已成为交通部门的迫切需求。本文通过地面光谱测量手段获取了公路路面的光谱反射数据,基于对不同谱段光谱反射吸收特征的分析,探索了沥青路面老化过程中的光谱响应变化规律。在此基础上,通过比值、归一化等数学运算构建了能反映沥青路面健康状况的光谱指数模型,并基于北京南六环良乡地区2013年9月21日的Worldview-2高分辨率遥感数据,对所构建的沥青路面健康光谱指数模型进行了有效性验证与分析。通过比较不同指数反映沥青路面老化状况的差异,筛选出几个适合沥青道路健康状况检测的光谱指数,并以地面观测数据对检测结果的精度进行了验证。结果表明：利用遥感手段可快速实现大范围道路路面健康状况的监测与评价,拓展了遥感技术的应用领域,同时为公路养护部门提供了新的技术手段。
|
| 关 键 词： | 沥青路面 健康光谱指数 Worldview-2 光谱特征 沥青老化 |
| 收稿时间： | 2016-08-30 |
Spectral Analysis of Road Pavements and Monitoring of the Aging Conditions of Asphalt Pavement from Worldview-2 Imagery |
| |
| JIN Xu,ZHANG Xian feng,LUO Lun,PAN Yifan,YANG Ke.Spectral Analysis of Road Pavements and Monitoring of the Aging Conditions of Asphalt Pavement from Worldview-2 Imagery[J].Geo-information Science,2017,19(5):672-681. |
| |
| Authors: | JIN Xu ZHANG Xian feng LUO Lun PAN Yifan YANG Ke |
| |
| Institution: | 1. Institute of Remote Sensing and GIS, Peking University, Beijing, 100871, China2. China Transport Telecommunications & Information Center, Beijing 100011, China |
| |
| Abstract: | The rapid development of highway transport networks has increased much work load to road maintenance departments in China, and consequently it is currently a pressing demand to develop new technical support to rapidly and accurately collect the health conditions of road pavements. In contrast to the conventional methods, previous research indicated that remote sensing might offer a new approach for the monitoring of pavement conditions of highway roads. This paper first tends to examine the spectral responses and features of the road pavements with different aging conditions and pavement materials based on field measurements of the pavement spectral reflectance. In addition, this study also tries to construct effective road pavement condition index from satellite remote sensing data for the monitoring of pavement health conditions. One of the findings shows that the slope of the spectral curves in the wavelength region of 400~900 nm grows bigger from negative to positive with the gradual aging of the asphalt pavements based on the field measurements of the pavement spectra. After that, several spectral index models were built up to monitor and evaluate the road pavement aging conditions by means of simple arithmetical calculation such as ratio and normalization. To demonstrate the applicability of the proposed indices to satellite remotely sensed data, a Worldview-2 image acquired on September 21, 2013 in the Liangxiang area near the sixth Ring Road south, Beijing City was used to analyze the road pavement health conditions, and to verify these models using the Munsell Scale Card values that were collected together with the spectral measurements and used to indicate the pavement aging conditions in our study. The image was first preprocessed in RSI ENVI software package, such as radiometric and geometric corrections, and subset. The four proposed indices were calculated from the Worldview-2 image in the study area and evaluated using the in-situ measurements of the pavement health conditions by visually comparing the performance of the proposed spectral indices in characterizing the asphalt pavement aging conditions. Furthermore, correlation analysis between spectral pavement condition indices and the Munsell Scale Card values shows that the logarithmic health index can achieve the biggest determinant coefficient （R2=0.72,n=23） and may be applicable in the monitoring of road pavement conditions. The case study indicates that road pavements with different materials and aging conditions have distinct spectral response in visible and near-infrared wavelength, and satellite remote sensing can be employed in the rapid mapping and assessment of large-range asphalt road pavement conditions. Thus, the study extends remote sensing applications and offers a new technique for the road maintenance departments. Future work may explore spectral mixture analysis in asphalt condition mapping from low-altitude unmanned aviation vehicle （UAV） hyperspectral imagery. |
| |
| Keywords: | asphalt pavement spectral index high-resolution remote sensing spectral signatures asphalt aging |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《地球信息科学》浏览原始摘要信息 |
| 点击此处可从《地球信息科学》下载免费的PDF全文 |
|
