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作 者:徐乔 余绍淮[1] 余飞[1] XU Qiao;YU Shao-huai;YU Fei(CCCC Second Highway Consultants Co.Ltd.,Wuhan 430056,China)
机构地区:[1]中交第二公路勘察设计研究院有限公司,武汉市430056
出 处:《公路》2023年第12期344-354,共11页Highway
基 金:湖北省重点研发计划项目,项目编号2021BAA185;武汉市重点研发计划项目,项目编号2022012202015071;中交二公院科技研发项目,项目编号KJFZ-2020-012。
摘 要:定期开展高速公路路域植被参数监测工作,对指导路域生态环境保护具有十分重要的意义,而传统地面实测方法难以对大范围植被参数进行快速长时间的监测。为此,利用卫星遥感技术,采用一种基于时序Sentinel-2影像的高速公路路域典型植被参数监测与分析方法,以京港澳高速湖北北段路域为研究区,利用长时间序列的Sentinel-2影像,采用PROSAIL辐射传输模型与人工神经网络相结合的方法快速获取路线区域的多种植被参数,并结合时间序列信息熵与变异系数对植被参数的趋势性及稳定性进行分析,从而实现对路域植被变化状况的准确评价。实验结果表明,基于时序Sentinl-2影像的路域典型植被参数提取与分析技术,可快速获取路域植被的生长变化状况,有效节约人力物力,为高速公路植被保护与绿化养护提供科学依据。Regular monitoring of vegetation parameters in the expressway area is of great significance to guide the ecological environment protection of the road area.However,it’s difficult for the traditional ground measurement method to extract and monitor vegetation parameters in a large range for a long time quickly.To this end,a monitoring and analysis method of typical vegetation parameters in highway road area using time-series Sentinel-2images is adopted based on satellite remote sensing technology.Taking the northern section of the Beijing-Hong Kong-Macao Expressway in Hubei as the research area,the PROSAIL radiation transfer model combined with the artificial neural network method is used to quickly obtain various vegetation parameters in the route area based on the long-term Sentinel-2images.Then the time series information entropy and variation coefficient is utilized to analyze the trend and stability of the vegetation parameters,and an accurate evaluation of the vegetation changes in the road area is finally realized.The experimental results show that the extraction and analysis technology of typical road vegetation parameters based on time series Sentinl-2images can quickly obtain the growth and change status of road vegetation,effectively save manpower and material resources,and provide a scientific basis for highway vegetation protection and greening maintenance.
关 键 词:Sentinel-2影像 路域植被参数 高速公路 时间序列信息熵 变异系数 状态监测
分 类 号:U418.9[交通运输工程—道路与铁道工程] TP75[自动化与计算机技术—检测技术与自动化装置]
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