沥青路面老化状况遥感监测与评估模型建立及应用
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摘要
针对大范围公路路面健康状况快速监测与评估需求,基于地面光谱测量获取的路面光谱数据,对不同老化程度的沥青路面光谱特征进行了分析,通过求导和包络面去除等方法得出老化沥青路面和新沥青路面在400～680nm、860～970nm两个波段范围内存在显著光谱特征差异。然后基于这些特征波段构建了沥青路面老化乘积指数(Multiplication Aging Index,MAI)模型,并利用北京房山良乡地区的WorldView-2卫星影像来刻画沥青路面在道路使用中出现的老化状况。通过与地面实测光谱数据和路面状况描述进行对照,将实地测量得到的Munsell明度色卡值与本文提出的MAI指数进行了统计分析,结果表明:该MAI指数能较好地反映沥青路面的老化状况,可实现对研究区内14条沥青道路的老化状况进行遥感监测与评价,研究结果可为道路管理部门制定养护规划提供新的技术手段。
To meet the demands in monitoring the health conditions of road pavements over a relatively large area,by means of derivative and continuum removal approaches this study analyzes the spectral features of asphalt road pavements aging degrees based on the field measurements of pavement spectra.Distinct spectral features of new and aged asphalt road pavements were observed in the wavelength regions of400～680 nm and 860～970 nm.After that,a WorldView-2 image in Liangxiang area,Fangshan district,Beijing City were captured and the corresponding bands were used to create a Multiplication Aging Index(MAI)to reflect the aging conditions of asphalt road pavements.Comparison between the MAI and in-situ measurements of the spectra and aging conditions of the road pavements in the study area was performed,and statistical analysis was also conducted based on the Munsell brightness values collected in the field investigation.Through the contrast,the aging condition from MAI has good relevance to the in-situ measurements.Results indicate that the proposed MAI index can reflect the aging conditions well and is further used to monitor the pavement quality of the 14 road pavements in the study area.According to the evaluation,six roads in the study area need road maintenance.The research can offer a new technology for road management departments to make their road maintenance plans.
To meet the demands in monitoring the health conditions of road pavements over a relatively large area,by means of derivative and continuum removal approaches this study analyzes the spectral features of asphalt road pavements aging degrees based on the field measurements of pavement spectra.Distinct spectral features of new and aged asphalt road pavements were observed in the wavelength regions of400～680 nm and 860～970 nm.After that,a WorldView-2 image in Liangxiang area,Fangshan district,Beijing City were captured and the corresponding bands were used to create a Multiplication Aging Index(MAI)to reflect the aging conditions of asphalt road pavements.Comparison between the MAI and in-situ measurements of the spectra and aging conditions of the road pavements in the study area was performed,and statistical analysis was also conducted based on the Munsell brightness values collected in the field investigation.Through the contrast,the aging condition from MAI has good relevance to the in-situ measurements.Results indicate that the proposed MAI index can reflect the aging conditions well and is further used to monitor the pavement quality of the 14 road pavements in the study area.According to the evaluation,six roads in the study area need road maintenance.The research can offer a new technology for road management departments to make their road maintenance plans.
引文
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[16] Zhao Ying,Wang Huan,Fang Yuan.Remote Sensing Image Preprocessing based on WorldView-2[J].Geomatics&Spatial Information Technology,2014(6):165-167.[赵莹,王环,方圆.基于WorldView-2的遥感影像预处理[J].测绘与空间地理信息,2014(6):165-167.]
[17] Xu Jing,Hong Jinxiang,Liu Jiaping.Literature Review of Asphalt Aging Mechanism[J].Petroleum Asphalt,2011,25(4):1-7.[徐静,洪锦祥,刘加平.沥青老化机理综述[J].石油沥青,2011,25(4):1-7.]
[18] Dong Zhenzhong.Concepts and Comparison of Common Distresses of Asphalt Pavements[J].Science and Technology Innovation Herald,2015(7):238.[董振忠.沥青路面常见病害概念比较[J].科技创新导报,2015(7):238.]
[19] Shahi K,Shafri H Z M,Taherzadeh E,et al.A Novel Spectral Indexto Automatically Extract Road Networks from World View-2 SatelliteImagery[J].Egyptian Journal of Remote Sensing&Space Science,2015,32(1):27-33.
[20] Mohammadi M.Road Classification and Condition Determination Using Hyperspectral Imagery[J].International Society for Photogrammetry and Remote Sensing-International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2012,XXXIX-B7:141-146.
[2] Herold M,Roberts D,Smadi O,et al.Road Condition Mapping with Hyperspectral Remote Sensing[C]∥Proceedings of the AVIRIS Workshop,Pasadena,CA,USA,2004.
[3] Herold M,Roberts D,Noronha V,et al.Imaging Spectrometry and Asphalt Road Surveys[J].Transportation Research Part C Emerging Technologie,2008,16(2):153-166.
[4] Mei A,Salvatori R,Fiore N,et al.Integration of Fieldand Laboratory Spectral Data with Multi-resolution Remote Sensed Imagery for Asphalt Surface Differentiation[J].Remote Sensing,2014,6(4):2765-2781.
[5] Emery W J,Yerasi A,Longbotham N,et al.Assessing Paved Road Surface Condition with High-resolution Satellite Imagery[C]∥International Geoscience and Remote Sensing Symposium,Canada,2014.
[6] Longbotham N,Chaapel C,Bleiler L,et al.Very High Resolution Multiangle Urban Classification Analysis[J].IEEE Transactions on Geoscience and Remote Sensing,2012,50(99):1-16.
[7] Herold M,Roberts D.Spectral Characteristics of Asphalt Road Aging and Deterioration:Implications for Remote-sensing Applications[J].Applied Optics,2005,44(20):4327-34.
[8] Manzo C,Mei A,Salvatori R,et al.Spectral Modelling Used to Identify the Aggregates Index of Asphalted Surfaces and Sensitivity Analysis[J].Construction&Building Materials,2014,61(3):147-155.
[9] Levinson R,Berdahl P,Akbari H,et al.Methods of Creating Solar-reflective Nonwhite Surfaces and Their Application to Residential Roofing Materials[J].Solar Energy Materials and Solar Cells,2007,91(4):304-314.
[10] Liu Ye.Road Condition Mapping with Hyperspectral Remote Sensing[D].Chengdu:Southwest Jiaotong University,2008.[刘烨.超光谱遥感路面状况检测的应用研究[D].成都:西南交通大学,2008.]
[11] Jin Xu,Zhang Xianfeng,Luo Lun,et al.Spectral Analysis of Road Pavements and Monitoring of the Aging Conditions of Asphalt Pavement from Worldview-2Imagery[J].Journal of Geo-information Science,2017,19(5):672-681.[金续,张显峰,罗伦,等.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].地球信息科学学报,2017,19(5):672-681.]
[12] Pan Yifan,Zhang Xianfeng,Tong Qingxi,et al.Progress on Road Pavement Condition Detection based on Remote Sensing Monitoring[J].Journal of Remote Sensing,2017,21(5):796-811.[潘一凡,张显峰,童庆禧,等.公路路面质量遥感监测研究进展[J].遥感学报,2017,21(5):796-811.]
[13] Tong Qingxi,Zhang Bing,Zheng Lanfen.Hyperspectral Applications:Principles,Technologies and Applications[M].Beijing:High Education Press,2006.[童庆禧,张兵,郑兰芬.高光谱应用—原理、技术与应用[M].北京:高等教育出版社,2006.]
[14] Satellite Imaging Corp.WorldView-2Data Sheet[EB/OL]:https:∥www.satimagingcorp.com/satellite-sensors/worldview-2/,2009-10-08.
[15] Hao Lina.A Remote Sensing Study on Mine Environmental Effects:A Case of the Key Ore concentrating Area in Hubei Province[D].Beijing:China University of Geosciences,2013.[郝利娜.矿山环境效应遥感研究[D].北京:中国地质大学,2013.]
[16] Zhao Ying,Wang Huan,Fang Yuan.Remote Sensing Image Preprocessing based on WorldView-2[J].Geomatics&Spatial Information Technology,2014(6):165-167.[赵莹,王环,方圆.基于WorldView-2的遥感影像预处理[J].测绘与空间地理信息,2014(6):165-167.]
[17] Xu Jing,Hong Jinxiang,Liu Jiaping.Literature Review of Asphalt Aging Mechanism[J].Petroleum Asphalt,2011,25(4):1-7.[徐静,洪锦祥,刘加平.沥青老化机理综述[J].石油沥青,2011,25(4):1-7.]
[18] Dong Zhenzhong.Concepts and Comparison of Common Distresses of Asphalt Pavements[J].Science and Technology Innovation Herald,2015(7):238.[董振忠.沥青路面常见病害概念比较[J].科技创新导报,2015(7):238.]
[19] Shahi K,Shafri H Z M,Taherzadeh E,et al.A Novel Spectral Indexto Automatically Extract Road Networks from World View-2 SatelliteImagery[J].Egyptian Journal of Remote Sensing&Space Science,2015,32(1):27-33.
[20] Mohammadi M.Road Classification and Condition Determination Using Hyperspectral Imagery[J].International Society for Photogrammetry and Remote Sensing-International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2012,XXXIX-B7:141-146.