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首页> 外文期刊>Journal of Forest Planning >Estimating Mean Height and Stand Volume in Broad Leaved Forest Stands using LiDAR
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Estimating Mean Height and Stand Volume in Broad Leaved Forest Stands using LiDAR

机译：利用LiDAR估算阔叶林林分的平均高度和林分体积

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摘要

Forest stand variables (mean height, stand volume, and mean diameter breast height (DBH), tree density) were estimated in evergreen and deciduous broad leaved forest stand using LiDAR. LiDAR data were acquired along 12km and 28km transects with 1 pulse per square meter and small foot print (20cm). We set plots in evergreen and deciduous broad leaved forest stands from small to large on the transect and measured forest stand variables (mean DBH: 3.441.2cm; mean H: 3.1-17.4m; V: 25.1-854m~3; N: 295-9,507ha~(-1); n=18). Laser pulses of digital canopy height model were extracted in each plot and LiDAR indexes were calculated: average, maximum, 90, 75, 50, 25 percentiles, standard deviation, and coefficient of variation. A linear regression analysis wasperformed between LiDAR indexes and forest stand variables. Mean height had the highest relationship with the LiDAR index 75 percentile (r~2=0.79); stand volume with the LiDAR index average 05=0.79), mean DBH with the LiDAR index 75 percentile (r~2=0.56), and tree density with LiDAR index 75 percentile (r~20.52) .These results showed that low density LiDAR was useful for forest stand variable and would be useful for update and modification of forest base map and forest register.
机译：使用LiDAR估算常绿和落叶阔叶林林分中的林分变量（平均高度，林分体积和平均直径胸高（DBH），树木密度）。 LiDAR数据沿12km和28km断面采集，每平方米1个脉冲，占地面积小（20cm）。我们在样带上从小到大在常绿和落叶阔叶林林中设置图并测量林分变量（平均DBH：3.441.2cm;平均H：3.1-17.4m; V：25.1-854m〜3; N：295 -9,507ha〜（-1）; n = 18）。在每个图中提取数字树冠高度模型的激光脉冲，并计算LiDAR指数：平均值，最大值，90、75、50、25个百分位数，标准偏差和变异系数。 LiDAR指标与林分变量之间进行了线性回归分析。平均高度与LiDAR指数为75个百分位数的关系最大（r〜2 = 0.79）;结果表明，低密度LiDAR的平均立木蓄积量（LiDAR指数平均值为05 = 0.79），LiDAR指数为75％（r〜2 = 0.56）的平均DBH和LiDAR指数为75％（r〜20.52）的树木密度。对林分变量有用，对更新和修改林底图和林名册很有用。

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