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高光谱激光雷达提取植被生化组分垂直分布
引用本文:高帅,牛铮,孙刚,覃驭楚,李旺,田海峰.高光谱激光雷达提取植被生化组分垂直分布[J].遥感学报,2018,22(5):737-744.
作者姓名:高帅  牛铮  孙刚  覃驭楚  李旺  田海峰
作者单位:中国科学院遥感与数字地球研究所遥感科学国家重点实验室;中国科学院大学
基金项目:国家重点研发计划项目(编号:2017YFA0603004);国家自然科学基金(编号:41730107);中国科学院百人计划项目(编号:Y6YR0700QM);高分项目(编号:30-Y20A34-9010-15/17)
摘    要:对地高光谱激光雷达可以获得观测对象含有高光谱属性的全波形激光雷达回波,为探测植被生化特征的立体分布提供了新的遥感探测手段。基于此仪器开展室内试验,提出了植被生化组分垂直分布提取方法。首先,针对仪器的特点,提出了高光谱激光雷达全波形数据处理的方法;其次,以火炬花为例开展了室内扫描,并对获取的高光谱激光雷达数据进行了处理,获得带有高光谱属性的激光雷达点云数据;最后,根据植被指数与生化组分的关系,提取了叶绿素和胡萝卜素的生化组分垂直分布结果。研究结果表明,在植被顶部生化组分含量较低,叶绿素a普遍低于0.5 mg/g,胡萝卜素低于0.2 mg/g,而在中部叶片处,生化组分含量明显较高,与红色(顶部)和绿色叶片(中部)在植被垂直方向的分布一致,这表明基于仪器开展植被生理生化参数垂直分布遥感反演具有极大的应用潜力。

关 键 词:高光谱激光雷达  生化组分  垂直分布  全波形  点云分布
收稿时间:2017/6/19 0:00:00

Vertical distribution inversion of biochemical parameters using hyperspectral LiDAR
GAO Shuai,NIU Zheng,SUN Gang,QIN Yuchu,LI Wang and TIAN Haifeng.Vertical distribution inversion of biochemical parameters using hyperspectral LiDAR[J].Journal of Remote Sensing,2018,22(5):737-744.
Authors:GAO Shuai  NIU Zheng  SUN Gang  QIN Yuchu  LI Wang and TIAN Haifeng
Institution:The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China,The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100049, China,The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China,The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China,The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China and The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:A hyperspectral Light Detection And Ranging (LiDAR) can obtain high spectral properties of the observed object and provides a new method for detecting a three dimesional distribution of vegetation structure and biochemical characteristics. In this study, a data process flow and a biochemical characteristics method were proposed.Laboratory experiments were conducted on the basis of this instrument, and a vertical distribution extraction method of vegetation biochemical components was provided. First, we proposed the hyperspectral LiDAR waveform data processing method in accordance with the characteristics of the instrument. Second, an indoor Kniphofia scanning experiment was utilized, and the LiDAR point cloud data with high spectral properties were obtained. Finally, chlorophyll and carotene vertical distributions were extracted on the basis of the relationship between the vegetation index and biochemical components.Results show that the biochemical content of a red leaf at the top of vegetation is low, which is generally lower than 0.5 mg/g, and carotene is less than 0.2 mg/g. However, the biochemical component content in the middle of the green leaves was evidently high.This study showed that the instrument has a considerable application prospect in the field of quantitative remote sensing.
Keywords:hyperspectral LiDAR  biochemical parameter  vertical distribution  full waveform  point cloud
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