BackgroundForest stand density in tropical rainforests is crucial functional and structural variable of forest ecosystems in which above ground biomass can be derived. Currently, there is a growing demand for airborne and terrestrial LIDAR in measuring forest trees parameters for accurate assessment of forest biomass/carbon stock to meet the requirements of UN-REDD + program. Although several studies have been conducted on above ground biomass/carbon stock in tropical rainforest using forest inventory parameters derived from airborne and terrestrial LIDAR, no research was conducted on how the estimation of above ground biomass/carbon stock using airborne and terrestrial LIDAR derived parameters is affected by forest stand density in a tropical rainforest. Therefore, this study aims to analyze and investigate the strength of the relationship between forest stand density and its above ground biomass estimated using airborne and terrestrial LIDAR derived trees parameters. Purposive sampling approach was adopted for the selection of the unit of analysis. Results are based on data collected from 32 sample plots measured and scanned in the field. Airborne LIDAR was used to derive upper canopy trees height, while terrestrial LIDAR was used to derive the height of lower canopy trees and DBH of all lower and upper canopy trees. The DBH measured in the field was used to compute forest stand density and to validate the DBH manually extracted from TLS point cloud data. The DBH manually derived from TLS point cloud data was used to estimate AGB of the sampled plots for both upper and lower canopy trees.ResultsDescriptive statistics, linear regression and correlation analysis were used to answer the research questions of this study. Out of 1033 trees measured and scanned in the field, 855 trees (82.7%) were extracted from TLS point cloud data and 178 trees (17.3%) were missed due to occlusion. The Pearson correlation coefficient (r) between a total number of trees measured and scanned in the field and the total number of trees extracted from TLS point cloud data was 0.95. R2 of 0.89 was found to explain the relationship between number of missed trees per plot against a number of trees measured in the field per plot. The strength of the effect of forest stand density on AGB is explained by R2 which is 0.91.ConclusionsBased on the findings, forest stand density have significant effect on above ground biomass at 1% significance level. Since there is a strong relationship between forest stand density and AGB and the measurement of forest stand density from the ground is fast, forest stand density could be recommended as a proxy to estimate above ground biomass.

中文翻译：

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林分密度对使用马来西亚热带雨林的空中和陆地 LIDAR 衍生树木参数估算地上生物量/碳库的影响

背景热带雨林中的林分密度是森林生态系统的关键功能和结构变量，可以从中获得地上生物量。目前，在测量林木参数以准确评估森林生物量/碳储量以满足 UN-REDD+ 计划要求方面，对机载和地面 LIDAR 的需求不断增长。尽管已经使用从空中和陆地 LIDAR 导出的森林资源清查参数对热带雨林的地上生物量/碳库进行了几项研究，但没有研究如何使用空中和陆地 LIDAR 导出的参数估计地上生物量/碳库受热带雨林林分密度的影响。所以，本研究旨在分析和调查使用机载和地面 LIDAR 衍生的树木参数估计的林分密度与其地上生物量之间关系的强度。分析单位的选择采用有目的的抽样方法。结果基于从现场测量和扫描的 32 个样地收集的数据。机载 LIDAR 用于推导上部冠层树的高度，而地面 LIDAR 用于推导下部冠层树的高度和所有上下冠层树的 DBH。在现场测量的 DBH 用于计算林分密度并验证从 TLS 点云数据中手动提取的 DBH。从 TLS 点云数据手动导出的 DBH 用于估计上部和下部冠层树的采样地块的 AGB。结果描述性统计、线性回归和相关分析被用来回答本研究的研究问题。在现场测量和扫描的 1033 棵树中，从 TLS 点云数据中提取了 855 棵树（82.7%），由于遮挡而遗漏了 178 棵树（17.3%）。在现场测量和扫描的树木总数与从 TLS 点云数据中提取的树木总数之间的 Pearson 相关系数 (r) 为 0.95。发现 0.89 的 R2 可以解释每个地块缺失的树木数量与在每个地块的田间测量的树木数量之间的关系。林分密度对 AGB 的影响强度由 R2 解释为 0.91。结论根据研究结果，林分密度对地上生物量有显着影响，显着性水平为 1%。