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-  2016 

基于机载LiDAR数据的玉米叶面积指数反演
A method of estimating maize LAI using airborne LiDAR data

Keywords: 玉米 激光雷达 点云分类 孔隙率 叶面积指数
maize LiDAR point cloud classification gap fraction LAI

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Abstract:

以机载LiDAR离散点云数据为数据源,基于植被冠层孔隙率与叶面积指数的关系,提出一种反演大田玉米叶面积指数的方法。对反演LAI和实测LAI进行对比分析,结果表明:基于Axelsson改进的不规则三角格网加密方法可以将地面点和非地面点分开,结合高分辨率影像能够提取出玉米冠层点云;基于孔隙率反演LAI,尼尔逊参数的选择对结果影响很大,利用扫描天顶角模拟尼尔逊参数,LAI反演结果接近于真实情况。利用机载LiDAR点云数据能精确地反演大田玉米LAI,该研究方法适用于中等高度的农作物,可以扩展到甜菜、甘蔗等其他中等高度农作物。
Based on the airborne LiDAR point cloud data and the correlation between canopy gap fraction and leaf area index of maize, a method of estimating field planting maize LAI (Leaf area index) is put forward.The results show that:Applying irregular triangular grid encryption method can classify the LiDAR point clouds and combining with high resolution imagery can extract the maize canopy point cloud data;Nilsson parameters have great influence on the results.The inversion result of LAI by Nilsson parameters simulated with scan zenith angle is close to the actual LAI;Estimating LAI with LiDAR data has high precision and the method in this paper is feasible.It can also be applied to medium height crops, e.g.beet and sugar cane.

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