机载小光斑LIDAR的森林参数评估

使用小光斑机载激光雷达遥感得到森林结构参数是一个突破性技术。由于这个技术应用于树冠测量国内还相对比较新,所以需要大量的试验来整合实测数据和激光雷达遥感数据,并在后续分析和处理过程中获取森林应用急需的结构参数。随着数据存储能力和处理速度的提高,现在已经可以通过数字化采样来存储整个反射波形,而不仅仅是由系统提取出来的三维坐标(即离散点云)。通过对波形进行分析,可以更加详细地了解物体的纵向结构,比如表面倾斜、粗糙度、反射率。本文采用改进的EM算法分解原始波形数据,并得到植被高度、林冠下地形、冠层体积、地表反射率、植被反射率、森林郁闭度来描述森林的水平和垂直结构特性。

Use of Small - Footprint Scanning Airborne Lidar to Estimate Forest Stand Characteristics

Small-Footprint Airborne Lidar(light detection and ranging) remote sensing is a breakthrough technology for deriving forest canopy structural characteristics.Because the technique is relatively new in terms of canopy measurement in China,there is a tremendous need for experiments that integrate field work,lidar remote sensing and subsequent analyses for retrieving the full complement of structural measures critical for forestry applications.Data storage capacity and high processing speed available today has made it possible to digitally sample and store the entire reflected waveform,instead of only extracting the discrete coordinates which form the so-called point clouds.Return waveforms can give more detailed insights into the vertical structure of surface objects,surface slope,roughness and reflectivity than the conventional echoes.In this paper,an improved Expectation Maximum(EM) algorithm is adopted to decompose raw waveform data.Derived forest biophysical parameters,such as vegetation height,subcanopy topography,crown volume,ground reflectivity,vegetation reflectivity and canopy closure,are able to describe the horizontal and vertical forest canopy structure.