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首页> 外文期刊>Journal of Forest Planning >Estimating Canopy Information in Cryptomeria japonica and Chamaecyparis obtusa Stands using Airborne LiDAR Data
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Estimating Canopy Information in Cryptomeria japonica and Chamaecyparis obtusa Stands using Airborne LiDAR Data

机译：使用机载LiDAR数据估算日本柳杉和Chamaecyparis obtusa林分的冠层信息

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Crown density control is one of the main activities in forest management. For the prediction of tree growth, it is important to consider the crown length, leaf biomass, and other canopy parameters as a photosynthetic organ. We estimated the lengths ofcanopies on the basis of a Digital Surface Model (DSM) and Digital Elevation Model (DEM) obtained from airborne Light Detection and Ranging (LiDAR) data and examined the accuracy of the estimates in even-aged stands. Cryptomeria japonica and Chamaecyparis obtusa stands were selected for analysis. The study site was the University Forest in Chiba, Japan, which is managed by the University of Tokyo and has stand densities between 350 and 4,000 trees ha~(-1). First, we calculated the DSM and DEM for the University Forest in Chiba for the analysis of canopy information. We established 12 circular sample plots in Cryptomeria japonica and Chamaecyparis obtusa stands and measured the crown length of the dominant trees in each plot Second, we estimated the crown length of the dominant trees in each plot using the DSM and DEM obtained from airborne LiDAR data. Finally, we compared crown lengths obtained from airborne LiDAR data with crown lengths obtained from ground surveys and checked the accuracy of this methodology. The crown lengths obtained from airborne LiDAR data were highly correlated with those obtained from ground surveys (coefficient of determination = 0.95; root mean square error (RMSE) = 0.67). Thus, airborne LiDAR accurately measured crown length, regardless of stand density.
机译：树冠密度控制是森林管理的主要活动之一。对于树木的生长预测，重要的是将树冠长度，叶片生物量和其他冠层参数视为光合作用器官。我们根据从机载光检测和测距（LiDAR）数据获得的数字表面模型（DSM）和数字高程模型（DEM）估算了顶棚的长度，并检查了在均匀老化摊位上估算的准确性。选择了日本柳杉和美洲扁Cha（Chamaecyparis obtusa）林进行分析。研究地点是日本千叶市的大学森林，由东京大学管理，林分密度在350至4,000公顷（-1）之间。首先，我们计算了千叶大学森林的DSM和DEM以分析冠层信息。我们在日本柳杉和Chamaecyparis obtusa林分中建立了12个圆形样本样地，并测量了每个样地中优势树的树冠长度。其次，我们使用从机载LiDAR数据获得的DSM和DEM估算了每个样地中优势树的树冠长度。最后，我们将机载LiDAR数据获得的树冠长度与地面调查获得的树冠长度进行了比较，并检验了该方法的准确性。从机载LiDAR数据获得的冠冠长度与从地面勘测获得的冠冠高度高度相关（确定系数= 0.95;均方根误差（RMSE）= 0.67）。因此，无论支架密度如何，机载LiDAR都能准确测量冠长。

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