多波段激光雷达植被光谱分析

发布时间：2018-04-25 11:00

本文选题：多波段激光雷达 + 光谱指数　；参考：《光谱学与光谱分析》2017年06期

【摘要】：多波段激光雷达是获取光谱的一种新型手段。与传统的光谱仪仅能获取二维层面上的光谱不同,它基于超连续谱激光光源,利用激光的穿透性和高集中性,依靠光栅分光系统能够获得植被垂直方向上的光谱信息,从而得到植被在三维层面上的光谱分布。利用32波段激光雷达,首先在暗室条件下,将多波段激光雷达获取的光谱与ASD光谱仪获取的光谱进行了比较,发现在458~865nm内,两者有相同的形状特征,能准确的表示出植被的反射特征,然后通过对光谱指数与叶绿素含量的相关性分析发现,基于两者的光谱指数与叶绿素含量均有较好的拟合关系,其中,基于多波段激光雷达光谱的优化比值植被指数(MSR)与叶绿素含量存在极显著相关关系,决定系数R2达到0.780 2,均方根误差(RMSE)仅为0.508 1。最后,利用多波段激光雷达,实现了垂直方向上的光谱获取,通过多次扫描的方式,得到了植被光谱的三维点云分布,并利用MSR与叶绿素含量之间的最优拟合方程,反演得到了叶绿素含量的三维分布图。
[Abstract]:Multi-band lidar is a new method to obtain spectrum. Different from the traditional spectrometer, it can only obtain the spectrum on the two-dimensional level. It is based on the supercontinuum laser light source. It can obtain the spectral information in the vertical direction of the vegetation by using the penetration and high concentration of the laser, and depending on the grating spectroscopic system. Thus, the spectral distribution of vegetation on three-dimensional plane is obtained. Using 32-band lidar, the spectrum obtained by multi-band lidar is compared with that obtained by ASD spectrometer in the dark room. It is found that in 458~865nm, the two have the same shape characteristics. Can accurately express the reflection characteristics of vegetation, and through the correlation analysis of spectral index and chlorophyll content, it is found that the spectral index and chlorophyll content based on both have a good fitting relationship, among them, The optimized ratio vegetation index (MSRs) based on multiband lidar spectrum was significantly correlated with chlorophyll content, the coefficient of determination (R2) was 0.780 2, and the root mean square error (RMSE) was only 0.508 1. Finally, using multi-band lidar, the vertical spectral acquisition is realized. The three-dimensional point cloud distribution of vegetation spectrum is obtained by multiple scanning, and the optimal fitting equation between MSR and chlorophyll content is used. The three dimensional distribution map of chlorophyll content was obtained by inversion.
【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】：国家重点基础研究发展规划项目(2013CB733405) 国家高技术研究发展计划(863计划)(2014AA06A511) 青年科学基金项目(41301389)资助
【分类号】：Q948;TN958.98

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