Effect of Model Height and Model Position on Forming Table on Mouthguard Thickness in Thermoforming Using Circular Frame

Effectiveness and safety of mouthguards are greatly affected by its thickness. The aim of this study was to clarify the effect of model height and model position on the forming table on the mouthguard thickness in thermoforming using a circular frame. Mouthguards were thermoformed using 4.0-mm-thick ethylene-vinyl-acetate sheets and a vacuum forming machine. The sheet was sandwiched between circular frames and fixed to the clamp of the forming machine. Working models were two types of hard gypsum models trimmed so that the height of the anterior part was 25 mm (Model A) and 30 mm (Model B). The model was placed with its anterior rim positioned 40 mm (P40), 30 mm (P30), 20 mm (P20), or 10 mm (P10) from the front of the forming table. Differences in the reduction rate of the thickness due to the model height and model positions were analyzed by two-way ANOVA and Bonferroni’s multiple comparison test. Differences depending on the model height were observed at P40 at the incisal edge and P30, P20, and P10 on the labial surface, and the reduction rate of the thickness was significantly smaller in Model A (P < 0.01). As the distance from the model anterior rim to the front of the forming table was smaller, the rate of the thickness of the incisal edge and the labial surface decreases became larger. The rate of decrease in the thickness of the cusp and buccal surface was the smallest at P20. This study indicated that the difference in the thickness of the single-layer mouthguard depending on the model position on the forming table is affected by the model height. However, that is only the anterior part of the mouthguard, and the difference in thickness reduction rate is less than 5%. Additionally, in order to perform stable forming, it is useful to increase the distance from the model to the frame, and it is important to position the part whose thickness is desired to be maintained in the center of the forming table.

Genetic variation of height growth rhythm between clones of Larix kaempferi × L. gmelini based on logistic models

Fifty-three larch interspecific hybrid clones（Larix kaempferi × L.gmelini） and their parent clones were used for growth curve analysis of height variations.The growth curves of the 55 clones were ＇S＇-shaped and 36 exhibited similar curves as the male parent.The coefficients of the logistic models were higher than 0.943,indicating that our results were effective in the simulation of the growth curves.ANOVA analysis showed significant differences in height of different clones （P／0.01）.Average date of maximum height growth was Day 173,and average duration of rapid growth lasted for 50 days.Annual average increase in height was 9.7cm d^（-1） and daily average increase was 0.2 cm.The ratio of GR to the total annual increase in height ranged from 51.2 to 68.8%,with the average being 59.8%.There was a positive correlation between k values and plant heights which benefited from the evaluation of early plant height.There was also a positive correlation between GR（growth stage）,GD（plant height） and annual increase in height.These results are informative to the evaluation of the elite clone selection and provide a theoretical basis for breeding and management.

Modeling of the height–diameter relationship using an allometric equation model:a case study of stands of Phyllostachys edulis

Understanding the relationship between tree height （H） and diameter at breast height （D） is vital to forest design, monitoring and biomass estimation. We developed an allometric equation model and tested its applicability for unevenly aged stands of moso bamboo forest at a regional scale. Field data were collected for 21 plots. Based on these data, we identified two strong power relationships： a corre- lation between the mean bamboo height （Hm） and the upper mean H （Hu）, and a correlation between the mean D （Din） and the upper mean D （Du）. Simulation results derived from the aUometric equation model were in good agreement with observed culms derived from the field data for the 21 stands, with a root-mean-square error and relative root-mean-square error of 1.40 m and 13.41%, respectively. These results demonstrate that the allometric equation model had a strong predictive power in the unevenly aged stands at a regional scale. In addition, the estimated average height-diameter （H-D） model for South Anhui Province was used to predict H for the same type of bamboo in Hunan Province based on the measured D, and the results were highly similar. The allometric equation model has multiple uses at the regional scale, including the evaluation of the variation in the H- D relationship among regions. The model describes the average H-D relationship without considering the effects caused by variation in site conditions, tree density and other factors.

Modelling Orthometric Heights from a Combination of Ellipsoidal Heights and Gravimetric Geoid Model in Rivers State, Nigeria

Many applications in geodesy, hydrography and engineering require geoid-related heights. Spirit leveling which is the traditional means of obtaining geoid- or mean sea level-related heights is slow, time-consuming and costly. Global Navigation Satellite Systems (GNSS) offer faster and relatively cheaper way of obtaining geoid-related heights when geoidal undulation is applied to ellipsoidal heights. However, difficulties involved in determining acceptable geoid height have seriously hampered the application of GNSS for leveling in Rivers State, thus necessitating the need to develop an acceptable geoid model which will serve as a means of conversion of GNSS-delivered ellipsoidal heights to their orthometric heights equivalent. In pursuance of this objective, a detailed gravimetric geoid has been evaluated for Rivers State, Nigeria. The computation of the geoid was carried out by the traditional remove-restore procedure. The Earth Geopotential Model 2008 (EGM08) was applied as the reference field for both the remove and restore parts of the procedures;spherical Fast Fourier Transform (FFT) was employed for the evaluation of the Molodenskii’s integral formula for the height anomaly, (ζ) to yield the quasi-geoid;while the Residual Terrain Modelling (RTM) was done by prism integration. The classical gravimetric geoid over Rivers State was obtained from the rigorously evaluated quasi-geoid by adding the quasi-geoid to geoid (N?- ζ) correction it. The minimum and maximum geoid height values are 18.599 m and 20.114 m respectively with standard deviation of 0.345 m across the study area. Comparison of the gravimetric geoidal heights with the GPS/Leveling-derived geoidal heights of 13 stations across Rivers State, Nigeria showed that the absolute agreement with respect to the GPS/leveling datum is generally better than 7 cm root mean squares (r.m.s) error. Results also showed that combining both GPS heights and the computed Rivers State geoid model can give orthometric heights accurate to 3 cm post-fit using a 4-parameter empirical model. The geoid model can thus serve as a good alternative to traditional leveling when used with GPS leveling, particularly for third order leveling in the study area.

A new statistical model of wave heights based on the concept of wave breaking critical zone

When waves propagate from deep water to shallow water, wave heights and steepness increase and then waves roll back and break. This phenomenon is called surf. Currently, the present statistical calculation model of surf was derived mainly from the wave energy conservation equation and the linear wave dispersion relation, but it cannot reflect accurately the process which is a rapid increasing in wave height near the broken point. So, the concept of a surf breaking critical zone is presented. And the nearshore is divided as deep water zone, shallow water zone, surf breaking critical zone and after breaking zone. Besides, the calculation formula for the height of the surf breaking critical zone has founded based on flume experiments, thereby a new statistical calculation model on the surf has been established. Using the new model, the calculation error of wave height maximum is reduced from 17.62% to 6.43%.

Mixed-effects modeling for tree height prediction models of Oriental beech in the Hyrcanian forests

Height–diameter relationships are essential elements of forest assessment and modeling efforts.In this work,two linear and eighteen nonlinear height–diameter equations were evaluated to find a local model for Oriental beech（Fagus orientalis Lipsky） in the Hyrcanian Forest in Iran.The predictive performance of these models was first assessed by different evaluation criteria： adjusted R^2（R^2_（adj））,root mean square error（RMSE）,relative RMSE（%RMSE）,bias,and relative bias（%bias） criteria.The best model was selected for use as the base mixed-effects model.Random parameters for test plots were estimated with different tree selection options.Results show that the Chapman–Richards model had better predictive ability in terms of adj R^2（0.81）,RMSE（3.7 m）,%RMSE（12.9）,bias（0.8）,%Bias（2.79） than the other models.Furthermore,the calibration response,based on a selection of four trees from the sample plots,resulted in a reduction percentage for bias and RMSE of about 1.6–2.7%.Our results indicate that the calibrated model produced the most accurate results.

Fitting and evaluation of height-diameter models for Alnus japonica in La Trinidad, Benguet, Philippines

The study was conducted to develop height-diameter at breast height(HT-DBH) models for Alnus japonica in La Trinidad, Benguet,Philippines and evaluate their predictive capability.The six widely used nonlinear growth models that were selected in this study were the ChapmanRichards, Schnute, Modified logistic, Korf/Lundqvist,Weibull and Exponential. A total of 208 Alnus japonica trees were measured using standard diameter tape for DBH(1.3 m above the ground) and Vertex and transponder was used for the total height measurement. The performance of the developed models were evaluated using the fit statistics including coefficient of determination(R^2), root mean square error(RMSE), mean bias(ē), absolute mean difference(AMD), and Akaike Information Criterion(AIC). The lack-of-fit statistics was also performed for further evaluation of the performance of the models.Based on the evaluation criteria, all six models were able to determine the DBH-height relationships and fitted the data well. Using the rank analysis, the Weibull HT-DBH model had the best performance among the six commonly used nonlinear growth models. The results of this study will help forest managers especially in La Trinidad, Benguet to easily predict the total height using the Weibull model for Alnus japonica utilizing the DBH as the predicting variable.

A Hybrid Approach to Modeling and Control of Vehicle Height for Electronically Controlled Air Suspension

The control problems associated with vehicle height adjustment of electronically controlled air suspension （ECAS） still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical （MLD） modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller （HMPC） is tuned based on online mixed-integer quadratic optimization （MIQP）. Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology （MPT）, thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.

特高压电网不等高差短导线的受力性能

目前中国的特高压电网技术得到了快速发展。然而,工程中常由于忽视对导线受力性能的分析而酿成绝缘事故。根据导线两端挂线点的空间位置,其连接方式可分为等高差导线连接和不等高差导线连接。为此,本文提出了一种计算不等高差短导线端子在不同方向上受力性能的经验公式。通过改变挂线点之间的水平间隔距离、竖直高度差两个因素,开展了不同空间布局组合状态下的导线端子的受力特性分析,提出了可供设计参考的导线端部力学分析公式。结果表明经验公式具有良好的工程适用性。导线两端的受力特性不仅与环境荷载有关,与导线型号、两端竖直高度差、两端水平间隔距离等因素有关。

Incorporating shape constraints in generalized additive modelling of the height-diameter relationship for Norway spruce

Background： Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height （dbh） can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter （h-d） models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions. Methods： We develop unconstrained generalized additive models （GAM） and shape constrained generalized additive models （SCAM） for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany. Results： Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand, The definition of constraints leads only to marginal or minor decline in the model statistics like AIC An observed structured spatial trend in tree height is modelled via 2-dimensional surface fitting. Conclusions： We demonstrate that the SCAM approach allows optimal regression modelling flexibility similar to the standard GAM but with the additional possibility of defining specific constraints for the model effects. The longitudinal character of the model allows for tree height imputation for the current status of forests but also for future tree height prediction.

Derivation of a Formula for Mountain Height as a Function of Rank in Height

The relationship between mountain height and rank in height for a mountainous region is examined. A stochastic differential equation model is derived for the evolution of mountain elevations. The derivation is based on simple assumptions about tectonic and erosion processes in mountain elevation dynamics. At any given time, the model yields a CIR-type probability density for mountain heights. As data are often available for mountains of greatest elevation in a region, the tail of the CIR density is studied and compared with mountain height data for the highest mountains in the region. The tail density is proportional to the product of a power of height and an exponential function of height, i.e., hb-1exp(-ah) where h is mountain height and a and b are constants. The inverse distribution function of the tail probability density leads to a formula that relates rank in height to the corresponding mountain height. The formula provides, for example, a decreasing sequence of theoretical mountain heights for the region. The derived formula is tested against mountain height data sets for several mountainous regions in the British Isles, Continental Europe, Northern Africa, and North America. The derived formula provides an excellent fit to the mountain height data ranked by height.

基于地基雷达数据构建红松人工林树高、枝下高及接触高模型

采用地面激光雷达(Terrestrial Laser Scanning,TLS)扫描10块人工红松林所得到的数据,与实地调查数据相结合,构建红松树高曲线模型、枝下高预估模型与接触高预估模型,并建立联立方程组。首先,从所选择的5种树高曲线模型中,选择出拟合效果较好的2个模型作为联立方程组的备选模型。然后再从5个枝下高基础模型中选出1个拟合效果好,并且适用程度高的模型作为基础模型,运用再参数化和最优子集回归的方法将林分因子(林分平均胸径、林分断面积、高径比、优势木平均胸径和优势木平均高)代入基础模型,选择拟合效果较好的模型作为枝下高备选模型。相同的方法选择拟合效果好的接触高备选模型。最后将树高曲线模型、枝下高备选模型与接触高备选模型分别两两联立,建立联立方程组。通过似不相关回归(Seemingly Unrelated Regression Estimation,SVR或SURE),根据拟合优度与检验结果选择最优秀的方程组,并对联立方程组进行评价。最终得到结果最优联立方程组预估树高时,决定系数R^(2)=0.896,均方根误差RMSE=0.612 m;当方程组预估枝下高时,R^(2)=0.575,RMSE=0.850 m;当方程预估接触高时,R^(2)=0.719,RMSE=0.791 m,而且各种检验指标都较好。综合来看,方程组对树高、枝下高与接触高拟合精度与检验效果较好,可以解决树高、枝下高与接触高的内在相关性问题,为进一步研究红松树冠结构与动态变化提供基础。

含竞争指标的广义可加混合效应树高-胸径模型

广义可加混合效应模型(GAMM)兼具参数模型与非参数模型的优点,同时适于处理多层次分组数据。通过运用广义可加混合效应模型模拟胸径及树高之间关系,加入竞争因子作为辅助变量,并与传统非线性混合效应模型进行比较,能够为建立树高曲线及提高模型精度提供新方法。根据吉林省汪清林业局金沟岭林场2块100 m×100 m次生混交林样地中的实测单木数据,按照7∶3比例随机划分建模与验证数据。随机效应设定为林木分级,辅助变量选择大于对象木胸高断面积之和(B_(AL))或简单竞争指数(Hegyi指数,H_(EG)),根据随机效应的设定位置共构建15个广义可加混合效应模型,对照模型以Logistic及Richard方程为基础模型,共构建6个非线性混合效应树高-胸径模型。结果表明:所有广义可加混合效应模型均能较好地描述自变量与树高之间的关系,决定系数(R^(2))为0.8897~0.8998,相对均方根误差(R_(RMSE))为17.87%~18.74%,平均绝对误差(M_(AE))为1.7881~1.8745 m,赤池信息量(A_(IC))为4120.42~4162.23,均优于相同自变量下的非线性混合模型,R^(2)平均提高0.005,相对均方根误差、平均绝对误差、赤池信息量分别平均降低0.46%、0.0587 m、41.49。对于验证数据的预测可以看出,模型5具有最小的预测相对均方根误差,为20.28%,同时具有最小的预测平均绝对误差,为2.1038 m。但部分广义可加混合效应模型的预测表现略差于非线性混合模型。综合考虑参数与非参数估计显著性、模型估计精度及预测能力,所有模型中的最优模型为模型5,即以B_(AL)为辅助变量,考虑唯一全局平滑函数并以具有相同扭曲程度的分组水平平滑函数为基础添加随机效应。竞争因子选择B AL作为辅助变量能够提升树高模型的精度,而选择Hegyi指数为辅助变量的促进效果不明显。研究建立的广义可加混合效应树高胸径模型相较于传统非线性混合效应模型具有更高的估计精度及预测效果,B AL适宜作为树高模型的辅助变量来反映林木竞争状况的影响。

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。

基于混合效应和分位数回归的温带针阔混交林树高与胸径关系研究

【目的】基于非线性回归和广义模型构建不同分位数回归和混合效应的树高预测方程,并对比分析非线性模型、不同分位点(τ=0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9)模型、广义模型及非线性混合效应模型的拟合效果和预测精度,为研究林分生长和收获提供理论依据。【方法】本研究以吉林蛟河地区针阔混交林的主要树种(红松、色木槭、紫椴和水曲柳)为研究对象,基于21.12 hm2样地数据,首先在11个广泛使用的树高方程基础模型中选定基础模型;其次探究林分变量对树高的影响并构建含林分变量的广义模型;最后在基础模型和广义模型的基础上,构建分位数模型,同时考虑样方效应对树高的影响,构建混合效应模型。【结果】(1)各树种均以Richards模型拟合精度更高,且具有生物学意义,选定为基础模型;考虑林分变量与树高的相关性以及模型收敛性,加入优势木高建立的广义模型能显著提高拟合效果。(2)各树种均为中位数τ=0.5时模型拟合效果最佳,且与非线性回归预测精度相近,红松、色木槭、紫椴和水曲柳最高R^(2)值分别为0.811、0.809、0.724和0.617,广义中位数回归预测能力得到进一步提高,R^(2)值分别为0.891、0.874、0.858和0.627。(3)混合效应模型相对其他模型能显著提高预测精度,其中基础混合模型略优于广义混合模型,4个树种R^(2)值达到0.937、0.919、0.906和0.643,表明包含样方效应的混合模型能得到更准确更稳定的预测结果。【结论】与传统方法建立的基础模型和广义模型以及两者的中位数回归模型相较,基于非线性混合效应构建的树高-胸径模型预测精度更高,其中基于基础混合效应构建的吉林蛟河地区混交林树高-胸径模型更具优越性和稳定性。

基于深度神经网络的杉木树高-胸径模型研建

利用深度神经网络(DNN)模型建立杉木的树高-胸径模型,寻求一种更加高效的杉木树高预测方法。以贵州省清镇市国有林场49块样地中杉木的胸径、树高数据为研究对象,分成不同比例的训练集和测试集,训练集占比分别为20%,30%,40%,50%,60%,70%,80%;对应的测试集占比分别为80%,70%,60%,50%,40%,30%,20%。利用DNN构建树高-胸径模型,并将其与11个传统基础模型进行比较,通过R^(2)、RMSE和MAE对比选出预测效果最好的模型,并根据最优模型添加林木胸径与优势木平均胸径比(DDH),以提高模型的预测精度。利用DNN模型建立的树高-胸径模型在训练集占比为20%的情况下,加入DDH因子后其预测精度R^(2)达到0.89。利用DNN构建杉木树高-胸径模型对杉木树高进行预测,在使用较小数据量的前提下加入DDH因子能够提高对杉木树高的预测效果。

大采高工作面柔模沿空留墙掘巷技术

柔模混凝土沿空留巷技术已应用多年,在中厚煤层和薄煤层开采下均取得了较好的支护效果,但在厚煤层大采高工作面,因巷道高、巷旁支护压力大、混凝土早期强度低易受压损坏难以有效支撑顶板。大采高工作面矿压显现剧烈,巷旁维护难度大,故此提出一种新型的预浇墙柔模混凝土沿空留墙掘巷新技术,即在上工作面回采前,刷煤扩帮后提前预浇柔模混凝土墙体,提高煤帮整体支撑力的同时,解决柔模混凝土墙短期无法有效承载顶板来压的难题;待回采一定距离后,再沿墙滞后掘进下工作面回采巷道,且掘进方向与上工作面回采方向一致,缓解接续紧张,最终实现无煤柱开采。以王庄煤业3503工作面回采留设预浇墙为工程背景,建立了沿空留墙掘巷围岩结构力学模型,理论计算得出墙体力学支护参数,并通过现场应用验证了该技术的可实施性。结果表明:理论计算分析确定了墙体高宽比为5 m×1.5 m,混凝土强度C30即可满足留墙支护要求;沿墙掘进巷道总体变形量小,顶底板和两帮最大移近量仅为260 mm和125 mm,墙体最大受压18 MPa,小于墙体自身承载力;下工作面临近巷道掘进115 m后即趋于稳定。该技术应用全阶段效果良好,满足巷道使用要求,有效解决了大采高工作面沿空留巷重大技术难题,也可为相似工况无煤柱开采提供技术借鉴。

基于CMA-TRAMS模式地形高度偏差的地面气温误差订正方法研究

采用一元线性方法建立南海台风模式CMA-TRAMS地形高度偏差和地面气温预报误差的回归关系,分别开展不分级、高度偏差分级和地面气温误差分级的三种订正方法的研究,并进行订正效果评估。结果表明,模式地面气温预报误差与地形高度偏差总体呈负的线性相关关系,地面气温预报绝对误差随地形高度偏差绝对值增大而增大(对模式地形高度偏低站点尤为明显),但不同时刻地面气温预报误差特征表现不同,模式对地形高度偏高(即模式地形高于测站高度)和地形高度偏差小于50m的站点,06时地面气温(世界时,下同)预报总体偏低,对地形高度偏低大于50m的站点(即模式地形低于测站高度),06时地面气温预报总体偏高;而无论站点地形高度偏差如何,模式对18时地面气温预报总体偏高。三种订正方法中地面气温误差分级法能有效地减小地面气温预报误差,该方法订正后的分析场准确率可达96%~99%,12~48小时时效预报场准确率总体可提升至90%以上,该方法具有回归关系稳定、效果显著、适用性广、简单易行等特点。

基于遥感的森林碳储量显式计算模型

面向国家“双碳”目标和国际碳交易市场需求,陆地生态系统的固碳现状和未来固碳潜力亟须研究。森林是陆地生态系统中重要的碳库,目前基于地面观测的清查方法工作量大且抽样统计结果难以评价,基于卫星遥感反演的方法缺乏理论解释且普适性差。本文从单木级森林碳储量模型出发,提出一种基于遥感的森林碳储量显式计算模型。首先使用图像分辨率、森林郁闭度和森林高度3个关键变量构建森林碳储量显式计算模型,并对模型变量和参数进行误差分析;然后利用单木的生长特性,仿真不同饱和度的森林场景,从理论上解算不同树种的模型参数,并检验模型参数的精度与稳定性;最后验证模型在不同空间尺度、饱和度森林场景下的精度、稳健性和适用性。本文提出的森林碳储量模型解决了现有卫星遥感反演缺乏理论解释性和适用性差的难题,可实现大范围森林碳储量高分辨率制图和全球森林碳汇动态监测。

青冈栎次生林林分形高模型构建

探索林分形高模型的构建与评价方法,可为湖南省青冈栎林分蓄积量的精准测定提供理论依据。以芦头林场和青羊湖林场的青冈栎次生林为研究对象,基于35个样地的1055株单木实测数据,建立青冈栎次生林一元、二元林分形高模型。由孔兹干曲线推导出青冈栎树高曲线以计算林分条件平均高,基于林分形高与林分平均胸径、林分条件平均高的一元、二元相关关系,选取6个一元模型和8个二元模型,以决定系数(R^(2))、均方根误差(RMSE)、解释方差(EA)、平均绝对误差(MAE)和模型预估精度(P_(1))作为评价指标。经过评估和比较,选定一元林分形高模型为f(D)=2.8707×D^(0.2618)、f(H)=2.0224+0.3395×H和二元林分形高模型为f(D,H)=0.5906×exp(-0.0083×D)×H、f(D,H)=(0.7102-0.0701×logD)H和f(D,H)=2.4799×(D^(2)×H)^(0.1092)。通过留一交叉验证和配对T检验对模型进行检验,结果显示一元、二元林分形高模型均具有较高的精度和较强的适用性,进一步验证了以林分平均胸径和林分条件平均高构建林分形高模型的方法合理可行,可为其它类型的林分形高模型构建和林分形高表的编制提供示范和参考。