Accuracy assessment and error analysis for diameter at breast height measurement of trees obtained using a novel backpack LiDAR system

Background: The LiBackpack is a recently developed backpack light detection and ranging(LiDAR) system that combines the flexibility of human walking with the nearby measurement in all directions to provide a novel and efficient approach to LiDAR remote sensing, especially useful for forest structure inventory. However, the measurement accuracy and error sources have not been systematically explored for this system.Method: In this study, we used the LiBackpack D-50 system to measure the diameter at breast height(DBH) for a Pinus sylvestris tree population in the Saihanba National Forest Park of China, and estimated the accuracy of LiBackpack measurements of DBH based on comparisons with manually measured DBH values in the field. We determined the optimal vertical slice thickness of the point cloud sample for achieving the most stable and accurate LiBackpack measurements of DBH for this tree species, and explored the effects of different factors on the measurement error.Result: 1) A vertical thickness of 30 cm for the point cloud sample slice provided the highest fitting accuracy(adjusted R2= 0.89, Root Mean Squared Error(RMSE) = 20.85 mm);2) the point cloud density had a significant negative, logarithmic relationship with measurement error of DBH and it explained 35.1% of the measurement error;3) the LiBackpack measurements of DBH were generally smaller than the manually measured values, and the corresponding measurement errors increased for larger trees;and 4) by considering the effect of the point cloud density correction, a transitional model can be fitted to approximate field measured DBH using LiBackpackscanned value with satisfactory accuracy(adjusted R2= 0.920;RMSE = 14.77 mm), and decrease the predicting error by 29.2%. Our study confirmed the reliability of the novel LiBackpack system in accurate forestry inventory, set up a useful transitional model between scanning data and the traditional manual-measured data specifically for P.sylvestris, and implied the applicable substitution of this new approach for more species, with necessary parameter calibration.

Alternative expressions for stand diameter in complex forests

Quadratic mean diameter is the most frequently reported descriptor of the diameter distribution of forests.As such,it is often used as an indicator of forest stand structure,developmental stage,and ecological and economic potential.However,quadratic mean diameter can be heavily influenced by the presence or absence of large numbers of small stems in lower canopy strata,and it is also sensitive to left-truncation of the diameter distribution,making its interpretation across inventories with different protocols challenging.Here,we examine three alternative expressions of stand diameter:the arithmetic and quadratic mean diameter of the thickest 100 trees per hectare,and the basal area-weighted mean diameter.Using data from the United States Forest Inventory and Analysis program for New York and New England,these alternative expressions showed closer correlation with multiple stand structural variables than did quadratic mean diameter,including merchantable cubic and board foot volume per hectare,aboveground live tree carbon per hectare,and total number of live and dead standing trees greater than 40 cm diameter at breast height per hectare(previously proposed as an index of old-growth structure).Arithmetic and quadratic mean diameter of the thickest 100 trees per hectare showed nearly identical performance,and the strongest correlations across the board.We develop closed-form expressions for these variables when the diameter distribution is a Weibull,and illustrate their behavior relative to quadratic mean diameter for that situation.While the reasons for prevalence of quadratic mean diameter as an indicator remain valid,we suggest that these alternative measures should be more widely reported and analyzed to give a more informative depiction of stand structure and development in complex forests.

Analysis on the Growth Condition of Cunninghamia lanceolata Plantation in Lingnan Forest Farm

[Objectives]This study was conducted to provide good basic research data for Cunninghamia lanceolata plantations in southern Anhui,so as to improve local ecological,economic and social benefits.[Methods]A 22-year-old near-mature C.lanceolata plantation in Lingnan Forest Farm,Xiuning County,Huangshan City,Anhui Province was investigated and analyzed by sample plot survey.[Results]The average DBH value of the C.lanceolata plantation at the lower slope was the largest,24.7%and 19.2%higher than those at the upper and middle slopes,respectively.The average single plant wood volume at the lower slope was 47.6%and 49.1%higher than those in the upper and middle slopes,respectively.However,the average tree heights at various slope positions showed little difference.Meanwhile,all the indexes showed the phenomenon of semi-shady slope>sunny slope>shady slope under different slope directions.Among them,the effect of slope position on DBH was extremely significant,but the effect of slope direction on DBH was not significant,and slope position,slope direction and the interaction of slope direction and slope position had no significant effects on the tree height of the C.lanceolata plantation.In addition,slope direction and slope position had extremely significant effects on single plant wood volume.From the overall growth situation of the C.lanceolata plantation in Lingnan Forest Farm,the slope position factor had greater effects on various indexes of forest growth than the slope direction factor,mainly manifested in that the lower slope was better than the middle slope,and the middle slope position was better than the upper slope,while although slope direction had some effect on the growth of the C.lanceolata plantation,the influence degree was not as significant as that of slope position.[Conclusions]This study provides some reference for the adjustment and optimization,development and renewal of C.lanceolata plantation structure in the later period in this area,as well as some data support for other theoretical research on economic forests.

Parameterization of height-diameter and crown radius-diameter relationships across the globe

The tree height-diameter at breast height(H-DBH)and crown radius-DBH(CR-DBH)relationships are key for forest carbon/biomass estimation,parameterization in vegetation models and vegetation-atmosphere interactions.Although the H-DBH relationship has been widely investigated on site or regional scales,and a few of studies have involved CR-DBH relationships based on plot-level data,few studies have quantitatively verifed the universality of these two relationships on a global scale.This study evaluated the ability of 29 functions to ft the H-DBH and CR-DBH relationships for six different plant functional types(PFTs)on a global scale,based on a global plant trait database.Results showed that most functions were able to capture the H-DBH relationship for tropical PFTs and boreal needleleaf trees relatively accurately,but slightly less for temperate PFTs and boreal broadleaf trees(BB).For boreal PFTs,the S-shaped Logistic function ftted the H-DBH relationship best,while for temperate PFTs the Chapman-Richards function performed well.For tropical needleleaf trees,the fractional function of DBH satisfactorily captured the H-DBH relationship,while for tropical broadleaf trees,the Weibull function and a composite function of fractions were the best choices.For CR-DBH,the ftting capabilities of all the functions were comparable for all PFTs except BB.The Logistic function performed best for two boreal PFTs and temperate broadleaf trees,but for temperate needleleaf trees and two tropical PFTs,some exponential functions demonstrated higher skill.This work provides valuable information for parameterization improvements in vegetation models and forest feld investigations.

Heartwood, sapwood and bark content of teak trees grown in Karnataka, India

We evaluated heartwood, sapwood and bark content in teak trees. A total of 27 sample plots were laid out in teak plantations raised by State Forest Department in Kamataka covering different age groups （11-36 years）, density （516-2061 trees/ha） and sites. From these planta- tions, a total of 130 trees were felled for estimating the yield and bark content in relation to diameter at breast height （DBH）, age and density. Bark content ranged from 22.2%-54.3%. Heartwood and sapwood con- tent were analyzed by sampling five trees each from two different planta- tions, one 30 years old at 553 trees.ha-1 and the other 32 years old at 911 trees.ha-1. The highest heartwood proportion of stem wood volume （over-bark） was 56.3% and the lowest was 37.1%.

Estimating Individual Tree Diameter and Stem Volume Using Airborne LiDAR in Saga Prefecture, Japan

Advancements in airborne LiDAR analysis technology have made it possible to quantify forest resource volumes based on individual trees, and such technology may soon replace field surveys. Unlike individual tree detection or tree height measurements, diameter at breast height (DBH) is difficult to determine directly from measured data and is instead estimated indirectly using the correlation between crown size and DBH. Indicators that represent crown size include crown area, surface area, length, and length ratio, and were utilized with tree height as explanatory variables in ten combinations to determine a regression formula. DBH and tree height calculated from the regression formula were applied to an equation to calculate stem volumes of individual trees. Airborne LiDAR measurements were taken using ALS50-II and ALS60 (Leica) at a density of 4 points/m2. An evaluation of the relationship between the regression formulae and DBH estimates indicated that a combination of crown area, tree height, and crown ratio for Japanese cedar, and a combination of crown area and tree height for Japanese cypress, yielded the highest coefficients of determination. The average error and RMSE were 6.9% and 2.38 cm respectively for Japanese cedar, while the corresponding values for Japanese cypress were 8.35% and 2.51 cm. Once the relationship was extended to the stem volumes of individual trees, the average error was 14.4% and RMSE was 0.10 m3 for Japanese cedar. The corresponding values for Japanese cypress were 18.9% and 0.10 m3. These results demonstrate the potential use of airborne LiDAR as a substitute for field surveys.

Relationship between species diversity and tree size in natural forests around the Tropic of Cancer

Although numerous hypotheses have been proposed to explain the patterns of species diversity of forests at local and landscape levels,it is still difficult to predict the alpha diversity of species,especially in tropical and subtropical natural forests where trees of different sizes and shapes are highly mixed.Size might characterize species diversity,and the possible correlation between these variables may contribute to the development of easy-to-use growth indicators to predict diversity and to understand the status of trees within a stand.In this study,diameter classes were divided using the equal diameter class(EDC)and minimum measured diameter(MMD)methods,and five species diversity indices were calculated for each diameter class of 14 permanent plots in five national nature reserves surrounding the Tropic of Cancer(23.5°),southwest China.The results show that species richness,abundance,and spatial diversity indices decreased in a typical inverted J-shape pattern with increasing diameter class and MMD,and could be easily modeled by a negative exponential function.The ShannonWiener index showed a linear decrease while Pielou’s evenness index displayed a linear increase,with a small degree of instability.The results suggest that species diversity in subtropical forests is closely related to tree size,and the relationship is possibly independent of habitat.Measuring DBH of some trees in a stand could be informative regarding species diversity and contribute to the investigation and assessment of biodiversity.

Biomass Estimation Models for Cocoa (Theobroma cacao) Plantations in Ghana, West Africa

The role of cocoa systems for climate change mitigation and adaptation has increased substantially because of their capability to trap carbon dioxide from the atmosphere and deposited in the cocoa trees as carbon. Development of aboveground biomass (AGB) models for cocoa plantations is crucial for accurate estimation of carbon stocks in the cocoa systems, however, allometric models for estimating AGB for cocoa plantations remain a challenge for cocoa producing countries in Sub-Saharan Africa especially Ghana. The aim of this study is to develop allometric model that can be used for the estimation of AGB for cocoa plantations in Ghana, as well as West Africa. Destructive sampling was carried out on 110 cocoa trees obtained from the cocoa rehabilitation exercise for the development of the allometric models. Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R2), index of agreement (IA), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AICC) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as;AGB = 0.7217ρ(D2)0.921. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. This study is significant because it has provided a model to estimate AGB for the cocoa plantations in Ghana which is very important for the Ghana Cocoa-Forest REDD+ Programme and also can be used by other West African cocoa producing countries.

点云密度对无人机激光雷达森林参数估测精度的影响

[目的]点云密度是影响无人机激光雷达数据获取和预处理成本和效率的关键因素,探明点云密度对林分尺度无人机激光雷达森林参数估测精度的影响,有助于优化无人机激光雷达森林应用技术方案。[方法]以马尾松、桉树人工林为研究对象,采用百分比重采样方法,对密度为247点·m^(-2)的原始点云按40%、20%、8%、4%和2%的比例降低点云密度,得到1个全密度原始点云数据集和5个稀疏密度点云数据集;每个数据集独立进行点云分类、地面点滤波和数字高程模型生成、点云高度归一化等预处理并提取激光雷达变量;对于同一森林类型的同一个森林参数(林分蓄积量、断面积、平均高和平均直径)的估测,各个数据集都采用相同的乘幂模型结构式进行模型拟合,然后比较分析模型优度统计指标的差异,包括:决定系数(R^(2)),相对根方根误差(rRMSE)和平均预报误差(MPE);采用配对样本t检验方法对各个数据集的森林参数估测结果和激光变量的差异进行统计分析。[结果]当点云密度分别稀疏至100、50、…、5点·m^(-2)时,各个森林参数估测模型的精度保持基本一致;各个稀疏密度点云数据集的森林参数估测值的均值与原始点云数据集的估测值的均值不存在显著性差异(p≥0.05);各个稀疏密度点云数据集激光变量的均值和原始点云数据集激光变量的均值基本上不存在显著性差异(p>0.05)。[结论]在无人机激光雷达森林资源调查监测应用中,点云密度可低至5点·m^(-2)。然而,本试验结果仍需通过不同飞行高度获取不同密度点云数据予以验证。

滇西北高山松根径与胸径相关性模型比选研究

在滇西北调查高山松样木总株数862株,有效样木824株,系统抽取建模样木618株,检验样木206株。选用10种一元线性或非线性回归方程,拟合各胸径D与根径DR模型参数,并进行了适用性检验。结果表明,模型D=-2.710599+0.938673DR-0.000911DR^(2),离差平方和(SSR)值相对较小、总相对误差(RS)为0、相关系数(R^(2))0.987、预估精度99.44%,残差图以横轴为中心分布最为均匀随机,模型参数变动系数最大值为32.3%,说明模型稳定。检验样本实测值和估计值没有显著差异,该模型最优。

红松半同胞家系生长性状变异及优良家系和单株的筛选

在辽宁省本溪满族自治县清河城实验林场国家红松良种基地,以2007年营建的15年生红松半同胞子代测定林为研究对象,选择参试家系171个(其中包括当地生产苗作为对照),造林株行距2 m×3 m,设计为10株小区,9次重复;2022年11月份,测定试验林所有存活木的树高、胸径,以树高、胸径、单株材积等生长性状为评价指标,计算各指标的变异系数、家系遗传力、遗传增益、现实增益;采用多目标决策法、隶属函数法筛选优良家系和优良单株。结果表明:参试家系各测定指标差异均达极显著水平(P<0.01),各指标变异系数变化范围为9.69%~35.01%、家系各指标遗传力变化范围为0.64~0.78、家系单株遗传力变化范围为0.14~0.45,说明参试家系具有较大的性状变异和较高的遗传力。利用隶属函数法筛选出优良家系17个,入选家系的胸径均值5.69 cm、树高均值12.92 m、单株材积均值0.04 m^(3),分别是当地生产苗(对照)胸径的1.14倍、树高的1.13倍、单株材积的1.44倍;17个优良家系的现实遗传增益,胸径为3.21%、树高为4.54%、单株材积为9.37%。在优良家系的基础上筛选出50株优良单株,入选单株胸径平均值为6.6 cm、树高平均值为15.1 m、单株材积平均值为0.0573 m^(3)。

河南栾川老君山麻栎林群落结构与多样性动态研究

在河南老君山国家级自然保护区的麻栎林设置样地,分别于2018年、2023年进行了群落结构特征及其多样性调查.结果表明:5 a间,麻栎林的乔木密度下降,种类组成由52科86属110种减少至41科72属102种,常见种数量由70增加至79,物种丰富度指数增加,但各层次优势种、建群种相对稳定,群落具有一定相似性;胸径级与树高级的个体分布均表现出倒“J”形;多样性指数以灌木层的最大,灌木层与草本层均表现为增加,而乔木层表现为下降.研究表明,5 a间,群落结构特征与多样性发生了一定程度的变化,但总体上表现出较好的稳定性.

Radarsat SAR的森林生物物理参数信号响应及其蓄积量估测

利用地面实测数据,系统探讨了RadarsatSAR数据在森林蓄积量估测方面的应用潜力和森林生物物理参数信号响应。结果表明:RadarsatSAR后向散射系数与森林蓄积量、树高及胸径之间的关系可以用对数模型模拟;树种对后向散射系数具有一定影响;利用后向散射系数估测森林蓄积量,其精度基本符合林场大面积总体估测的精度要求,但小班水平应用效果不理想。

径级差异驱动辽东栎根系菌根真菌群落嵌套分布格局

嵌套理论反映局域集合群落物种的扩散迁移特征,菌根真菌作为维管束植物重要的共生对象,明晰其迁移扩散特征有助于提升生境破碎背景下微生物资源的保护和利用,为生物多样性保护政策的制定提供依据。本文选取东灵山辽东栎林10个海拔高度不同的山体半阳坡组成研究系统,测定坡面辽东栎根系外生菌根真菌群落并调查坡面植物属性,使用坡面植物属性表征树岛特征,使用真菌菌门属性特征表征菌根真菌扩散能力,使用重叠嵌套指数(NODF)和零模型检验确定菌根真菌群落嵌套水平及嵌套显著性,探究了基于辽东栎树岛的菌根真菌群落是否呈嵌套分布及驱动因素。结果表明:①辽东栎树岛的菌根真菌群落呈显著嵌套分布格局(P<0.05),重叠嵌套指数(57.35)高于完全随机零模型和列限定零模型(物种多度限定)。②锤舌菌纲、伞菌纲和座囊菌纲等真菌菌纲分别占群落相对多度的41.46%、29.31%和16.37%,多度较高的锤舌菌纲的生态位宽度显著高于其他菌纲(P<0.05),即其树岛分布范围最广。③调整树岛属性顺序后,基于土壤温度、生境异质性集合群落的NODF值显著高于完全随机零模型(P<0.05),表明土壤温度、生境异质性主要通过驱动种群多度方式来影响菌根真菌群落分布;基于胸径集群群落的NODF值显著高于列限定零模型(P<0.05),表明植株径级差异可显著影响菌根真菌的迁移扩散路径。研究发现,菌根真菌迁移扩散过程受辽东栎径级的影响,粗径级植株可通过能源供给招募更多菌根真菌成为菌根真菌群落中的迁移扩散源,驱动形成较高的嵌套性水平和群落稳定性,因此森林经营中应适当加强对粗径级林木的保护利用。

凉水保护区红松与主要伴生树种的空间关系

空间关系是影响森林生长与群落演替的重要因素,种间关系是其重要组成部分,研究空间关系有利于了解森林群落的生长更新、功能作用与演替进程。利用移动窗口法对凉水自然保护区10.4 hm^(2)样地不同径级的红松与主要伴生树种做空间相关性研究,并进行多尺度比较,得到不同尺度下不同径级红松与主要伴生树种个体的空间关系特征。研究结果表明:(1)红松与伴生树种的相互关系复杂多样,多种相互关系并存,表现出阔叶红松林群落结构的复杂性与稳定性。大径级红松压制同径级伴生树种,二者呈极显著负相关,但其对小径级伴生树种有庇荫作用,二者呈极显著正相关。(2)红松与主要伴生树种的相互关系在不同尺度、径级上均有极显著差异。尺度越大,红松与主要伴生树种的相关系数变化速率越小;伴生树种的径级越大,红松与主要伴生树种的相关系数变化速率越大。(3)红松与伴生树种的相关性具有尺度特征,主要表现在大尺度(≥60 m)范围上,在小尺度(<60 m)上相关性较弱。红松与伴生树种在相同径级与不同径级的结合方式上表现出不同的空间关系。同径级的红松与伴生树的种间关系多表现为负相关,不同径级的红松与伴生树种种间关系多表现为正相关。(4)以种间关系确定样方最小面积,凉水保护区临界样地面积为60 m×60 m。该研究集中于不同尺度下不同径级的红松与伴生树种的种间关系,解释优势种红松与伴生树种在森林的空间关系以及群落结构特征,为东北地区阔叶红松林的森林管理提供参考意见。

县级森林蓄积量连续监测方法及应用系统设计

森林蓄积量反映森林资源质量状况,精准估测森林蓄积量对提高森林资源管理水平和生态环境保护建设具有重要意义,也是我国实现2060年前碳中和方案的迫切需求。本研究提出一种县级森林蓄积量连续监测方法,通过采用抽样调查和样地实测相结合,样地模型更新和遥感变化更新相结合的方式,以智能样地代替人工样地调查,实现森林蓄积量调查同时部署、实时自动连续监测。同时,研发了应用系统和云平台,以期为森林蓄积量高效准确估测提供方法依据。

立地环境和林分结构驱动的辽东栎林生长与模拟

【目的】定量研究宁夏六盘山区辽东栎(Quercus mongolica)林的树高和胸径生长对气候、地形、土壤、林分结构等多种因子变化的响应规律,在此基础上构建多因子耦合模型,准确模拟和预测气候等因子对森林生长的影响。【方法】依据宁夏六盘山区环境梯度,2021—2022年对79块辽东栎天然次生林样地进行每木调查,利用上外包线法确定林分平均树高和平均胸径对立地环境和林分结构等因子的响应关系和函数类型,通过连乘构建多因子耦合模型框架并基于实测数据拟合模型参数,用于模拟气候变化对辽东栎林生长的影响。【结果】同时影响六盘山区辽东栎林平均树高和平均胸径生长的主要因子是林龄、林分密度、年均降水量、年均气温、土壤厚度。平均树高和平均胸径随林龄增大呈缓慢−快速−缓慢的生长变化,随林分密度增大呈先稳定后加速下降的变化,随土壤厚度和年均降水量增大呈先快速增加后渐趋平稳的变化,随年均气温升高呈先快速上升后快速下降的单峰变化趋势。根据林分平均树高和平均胸径对各单因子的响应函数构建了二者的多因子耦合模型,预测精度较高(R2>0.70)。对年均气温升高1.5℃的情景模拟结果表明,整个六盘山区的辽东栎林平均树高和平均胸径生长速率都会降低,其降低幅度在气候冷湿的六盘山区南部分别为10%和7%,在气候暖湿的六盘山区中部分别为15%和12%,在气候暖干的六盘山区北部分别为18%和13%。【结论】宁夏六盘山区辽东栎次生林的平均树高和平均胸径生长同时受气候、林分结构、立地环境等多因子的影响,建立反映多个主要因子(年均降水量、年均气温、林龄、林分密度、土壤厚度)影响的耦合生长模型可以准确预测气候变化和密度调控对树高和胸径生长的影响。未来的气温升高将会降低平均树高和平均胸径的生长,但降低幅度存在区域差异,表现为气温越高的区域降低幅度越大,需要分区采取不同的森林管理应对措施。研究结果可为预测气候变化影响和确定森林管理措施提供理论与技术支持。

New indices to balanceα-diversity against tree size inequality

The number and composition of species in a community can be quantified withα-diversity indices,including species richness(R),Simpson’s index(D),and the Shannon-Wiener index(H΄).In forest communities,there are large variations in tree size among species and individu-als of the same species,which result in differences in eco-logical processes and ecosystem functions.However,tree size inequality(TSI)has been largely neglected in studies using the available diversity indices.The TSI in the diameter at breast height(DBH)data for each of 99920 m×20 m forest census quadrats was quantified using the Gini index(GI),a measure of the inequality of size distribution.The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat.We also examined the relationships ofα-diversity indices with the GI using correlation tests.The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions,with most root-mean-square errors(990 out of 999 quadrats)being<0.0030.There were significant positive correlations between each of threeα-diversity indices(i.e.,R,D,and H’)and the GI.Nevertheless,the total abundance of trees in each quadrat did not significantly influence the GI.This means that the TSI increased with increasing spe-cies diversity.Thus,two new indices are proposed that can balanceα-diversity against the extent of TSI in the com-munity:(1−GI)×D,and(1−GI)×H’.These new indices were significantly correlated with the original D and H΄,and did not increase the extent of variation within each group of indices.This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities,especially in the face of cumulative species loss under global climate change.

基于机载激光雷达和机器学习的林分平均胸径遥感估测

为探究不同模型对林分平均胸径的预测精度,使用贵州省桂花国有林场马厂工区同步获取的机载激光雷达点云数据和地面实测样地数据,通过提取样地水平的点云特征变量,采用方差膨胀因子分析和皮尔逊相关性检验进行自变量选择,建立机器学习模型估测样地平均胸径。结果表明:1)点云特征变量,如平均冠层高度和高度偏态与林分平均胸径有很强的相关性。2)机器学习模型(随机森林、支持向量机、最近邻算法)优于多元线性回归模型,其中,随机森林的拟合效果最好。随机森林的决定系数(R^(2))为0.71,均方根误差(RMSE)为2.50。3)通过柳杉纯林、针叶混交林、针阔混交林、马尾松纯林4种森林类型的林分平均胸径预测值与实际值差值,进一步证实随机森林模型精度最高,拟合效果最好。利用机载激光雷达点云数据提取点云特征变量,并构建基于机器学习算法的林分平均胸径估测模型是可行的,该方法的精度能满足森林资源调查的应用需求,可作为辅助林业调查工作的技术手段。

不同来源尾巨桉苗木造林生长的比较研究

为明确不同来源良种尾巨桉(Eucalyptus urophylla×E.grandis)无性系DH32-29苗木造林后幼龄阶段(1-3 a)的生长差异,为优质苗木的选择和提质增产增效提供理论依据,本研究以来源清楚的尾巨桉无性系DH32-29苗木(BG)和来源不清的尾巨桉无性系DH32-29苗木(NBG)造林林分为研究对象,比较研究广西西北部、中部及南部3个区域不同苗木造林林分的胸径、树高、生物量、碳储量及生产力的差异性。结果表明:林龄为2、3 a时,尾巨桉BG林分的平均胸径、单株生物量、单株碳储量及单株生产力均显著高于NBG林分(P<0.05);BG林分乔木层生物量、碳储量及生产力整体高于NBG林分,在林龄为1 a时差异较小,林龄为2 a生时差异增大,但未达显著水平(P>0.05),林龄为3 a生时差异达极显著水平(P<0.01)。因此,采用来源清楚的优质苗木造林增产效果更明显。