基于辐射传输模型探究机载高光谱激光雷达的植被垂直生化组分探测能力  

Exploring the Capability of Airborne Hyperspectral LiDAR Based on Radiative Transfer Models for Detecting the Vertical Distribution of Vegetation Biochemical Components

作　　者：郝一硕 牛沂芳 王力 毕恺艺 HAO Yi-shuo;NIU Yi-fang;WANG Li;BI Kai-yi(Key Laboratory of Remote Sensing and Digital Earth,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院空天信息创新研究院,遥感与数字地球重点实验室(中国科学院),北京100101 [2]中国科学院大学,北京100049

出　　处：《光谱学与光谱分析》2024年第7期2083-2092,共10页Spectroscopy and Spectral Analysis

基　　金：国家重点研发计划项目(2021YFB3901305);中国博士后科学基金项目(2022M723221);国家自然科学基金项目(U2244230)资助。

摘　　要：自然环境下的植被群落,由于各种群之间以及种群与环境间的竞争与选择,常呈现出一定的垂直结构,对于同一植株的不同生长阶段,在垂直方向也有着不同的生理生化参数。对这种三维立体分布特征进行探测,能够进行生态环境立体化定量评价,对森林碳储量估算和生物多样性保护等具有重要意义。传统的被动光学遥感以及激光雷达在植被生化参数垂直探测方面有较大的局限性,而高光谱激光雷达(Hyperspectral LiDAR,HSL)这一新型探测仪器的出现为探测植被生理生化参数垂直分布提供了新的手段。但由于受到硬件方面的限制,HSL在机载平台下对森林复杂立体场景的适用性尚未得到充分研究。故首先基于HSL原型样机在实验室开展小尺度的室内测量,以火炬花植株为目标,验证其对空间信息和光谱信息的一体化提取能力;随后进一步使用三维辐射传输模型构建具有垂直异质性特征的森林场景,模拟机载HSL设备实现森林的高光谱三维点云提取,结合植被指数和随机森林模型对场景中三种不同植被冠层的叶绿素浓度和类胡萝卜素浓度进行反演。结果表明:室内实验证实了HSL回波信息可以有效区分植株不同高度处光谱曲线的差异,火炬花上部红色叶片和下部绿色叶片的归一化植被指数分别小于和大于0.5;基于三维辐射传输模型成功构建了虚拟森林场景的机载HSL高光谱三维点云,在得到的24组植被指数中,有17组指数表现出良好的探测精度(平均绝对百分比误差MAPE<13%);植被叶绿素反演模型R^(2)达到0.93,上层、中层和下层的平均绝对误差MAE分别为6.26、3.40和2.81;类胡萝卜素反演模型R^(2)为0.91,上层、中层和下层的MAE分别为1.59、2.58和0.39。该研究显示出HSL设备是一种立体化提取植被光谱信息的有效手段,在探测森林等复杂植被场景的生化组分垂直分布方面具有巨大的应用潜力。In natural environments,vegetation communities often demonstrate vertical structure due to competition and natural selection among plant groups and between populations and their environment.Different growth stages of the same plant also exhibit various structural and biochemical parameters in the vertical dimension.Detecting these three-dimensional spatial distribution features enables quantitative assessment of ecological environments in three dimensions,crucial for estimating forest carbon reserves and biodiversity conservation.Traditional passive hyperspectral remote sensing and lidar techniques face significant limitations in vertical vegetation profiling.However,the emergence of Hyperspectral LiDAR(HSL),a new type of sensing instrument,offers a fresh approach to studying the vertical distribution of physiological and biochemical parameters in vegetation.Yet,due to hardware constraints,the suitability of HSL under unmanned aerial platforms for complex three-dimensional forest scenes remains insufficiently explored.This paper begins with laboratory experiments using a prototype HSL to conduct small-scale indoor measurements with torch flower plants as the target to verify its integrated capability in extracting spatial and spectral information.Subsequently,the three-dimensional radiative transfer model LESS was used to simulate forest scenes with vertical heterogeneity.The model simulated airborne HSL devices for extracting hyperspectral three-dimensional point clouds of forests.Vegetation indices and a random forest model are utilized to invert chlorophyll and carotenoid concentrations in forest canopy layers.The results show that in indoor experiments,the HSL echo information effectively discriminates the spectral differences at different heights of plant structures.The NDVI values in the upper red leaf area and lower green leaf area of torch flowers are respectively less than and greater than 0.5.The LESS model successfully constructed high-resolution hyperspectral three-dimensional point clouds of forest s

关 键 词：森林立体场景 机载高光谱激光雷达 三维辐射传输模型 植被生化组分 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]