方向自适应的星载光子计数激光测高植被冠层高度估算

星载光子计数激光测高系统具有较高的沿轨距离分辨率,能够探测得到植被冠层和地表的连续高程信息。然而星载植被点云的低点云密度和低信噪比,对植被相对冠层高度的估算方法提出了新的要求。本文提出了一种方向自适应的星载光子计数激光测高植被点云冠高估算方法。首先通过寻找点云高程统计直方图中代表冠层和地面位置的极值进行粗去噪,大致得到信号高程所在的范围,并估算出冠层,地面和噪声点云的平均密度以及地表坡度。随后对粗去噪后的点云进行方向自适应的密度聚类精去噪,其邻域的方向为地表坡度,与密度有关的阈值均根据估算出的点云密度自适应的做出调整。在滤波后,结合点云的密度和高程百分比分别找出地面与树冠顶端的初始点,并通过三角网方法(TIN)扩展初始点以进行分类,最终确定地表与树冠顶端的高程。采用ATLAS星载激光测高仪的植被点云对算法进行了验证,结果表明算法能够正确估算植被冠高,十分适用于坡度较大和叶面积指数较低的地区,其中冠顶与地面的高程和机载LIDAR数据高程的决定系数R~2分别为0.99与0.77,均方根误差RMSE为0.28 m与2.6 m。

An adaptive directional model for estimating vegetation canopy height using space-borne photon counting laser altimetry data

The space-borne photon counting laser altimetry can detect continuous elevations of vegetation canopy and earth surface for its high along-orbit resolution. However, the relatively low point cloud density and low signal-to-noise ratio (SNR) of space-borne vegetation point clouds put forward new requirements for estimating vegetation canopy heights. In this paper, an adaptive directional model for estimating vegetation canopy heights using space-borne vegetation point clouds was proposed to meet the new requirements. Firstly, the range of signal elevation was roughly obtained by searching two extremums that represent the crown and ground in the statistical histogram of point cloud elevation. The land slope and average densities of crown, ground and noise were estimated as well. Then, the roughly denoised point clouds were further fine denoised by adaptive directional density-based clustering where the direction of neighborhood is along the land surface, and the thresholds related to density are adjusted adaptively according to the estimated point cloud densities. After filtering, the elevations of ground and canopy were estimated respectively by applying triangular irregular networks (TIN) where the initial points of ground and canopy in TIN were found by the densities and elevation percentage of point clouds. Vegetation point clouds of ATLAS space-borne laser altimeter are used to validate the filtering method. The experimental results show that the adaptive directional model can correctly estimate vegetation canopy heights and is fit for areas with large slope and low leaf area index. The determination coefficients R² of canopy and ground elevation between processed ATLAS data and airborne LIDAR data are 0.99 and 0.77 respectively, and RMSE are 0.28 M and 2.6 m.