基于树高和树冠因子的立木材积与地上生物量相容模型研究

【目的】无人机机载激光雷达能够准确地测定单木、林分乃至大尺度森林结构参数(树高和树冠因子)。为应用无人机激光雷达技术准确估测森林蓄积量、生物量和碳储量提供计量依据和技术支撑。【方法】以150株实测马尾松生物量样本数据为研究对象,采用非线性回归估计方法和度量误差联立方程组方法,分析立木材积和地上生物量与树高、树冠因子的相关性,并在此基础上研究建立基于树高和树冠因子的立木材积与地上生物量相容模型。【结果】单株材积和地上生物量与树高因子的相关性最为紧密,其次才是树冠因子;基于树高和冠幅因子的二元材积和地上生物量模型预估精度较高,达到92%以上,再考虑冠长因子的三元模型预估精度改进不大;基于树高和冠幅因子的二元立木材积与地上生物量相容模型估计效果更好,相对于一元相容模型系统而言,二元相容模型拟合效果有较大幅度提高,预估精度达到92%以上。【结论】采用度量误差联立方程组方法可以有效解决基于树高和树冠因子的立木材积与地上生物量相容问题,并且预估精度达到92%以上,所建二元立木材积与地上生物量相容模型可为应用激光雷达技术反演森林蓄积量和生物量提供计量依据。     

Modeling compatible single-tree aboveground biomass equations for masson pine (Pinus massoniana) in southern China

Because of global climate change,it is necessary to add forest biomass estimation to national forest resource monitoring.The biomass equations developed for forest biomass estimation should be compatible with volume equations.Based on the tree volume and aboveground biomass data of Masson pine(Pinus massoniana Lamb.) in southern China,we constructed one-,two-and three-variable aboveground biomass equations and biomass conversion functions compatible with tree volume equations by using error-in-variable simultaneous equations.The prediction precision of aboveground biomass estimates from one variable equation exceeded 95%.The regressions of aboveground biomass equations were improved slightly when tree height and crown width were used together with diameter on breast height,although the contributions to regressions were statistically insignificant.For the biomass conversion function on one variable,the conversion factor decreased with increasing diameter,but for the conversion function on two variables,the conversion factor increased with increasing diameter but decreased with increasing tree height.     

利用混合模型方法建立全国和区域相容性立木生物量方程

开展全国森林生物量监测和评估,建立适合较大区域范围的通用性立木生物量模型将成为必然趋势,而如何保证不同尺度范围森林生物量估计值的相容性,是必须面临的一个问题。以南方马尾松(Pinus massoniana)地上生物量数据为例,通过利用混合模型方法,同时建立全国和区域性立木生物量方程,为解决不同区域尺度范围内森林生物量估计的相容性问题提供有效途径。从模型反映的结果看,相同直径林木的地上生物量估计值随起源、地域的不同存在一定程度的差异,其差异大小可以通过混合模型中的随机效应来估计。该方法可推广应用于其它通用性模型(如材积方程)的建立。     

林分材积计算的标准木方法的误差分析及校正

在指出了森林林分材积计算的标准本方法偏低估计实际材积的系统误差的基础上，提出了两种校正方案。校正系数可以从在林分内选择标准木的采样样本的数据中方便地算出。模拟举例计算说明两种校正方案基本消除了原公式的系统偏差。校正后的公式为：其中：为林分材积估计值；ＶＢＫ和ＡＢＫ分别是第Ｋ株标准木的测量材积和胸高断面面积；ＡＴ是林分的总胸高断面面积：ｈＢ，和ｄＢ是抽样算得的具有平均胸高断面面积的树的高度和胸径；ｄＷ是抽样算得的以胸高断面面积为权重的加权平均胸径；ｂ是树高曲线在ｄ＝ｄＢ处的斜率。校正的第２方案具有与上式完全相同的形式，只是标准木的是具有平均胸径的树木。     

Allometric equations for accurate estimation of above-ground biomass in logged-over tropical rainforests in Sarawak, Malaysia

Although allometric equations can be used to accurately estimate biomass and/or carbon stock in forest ecosystems, few have been developed for logged-over tropical rainforests in Southeast Asia. We developed allometric relationships between tree size variables (stem diameter at breast height (dbh) and tree height) and leaf, branch, stem and total above-ground biomass in two logged-over tropical rainforests with different soil conditions in Sarawak, Malaysia. The study sites were originally classified as mainly lowland dipterocarp forest and have been selectively logged in the past 20 years. In total, 30 individuals from 27 species were harvested to measure above-ground parts. The correlation coefficients for the allometric relationships obtained for total above-ground biomass as a function of dbh had high values (0.99), although the relationships for leaf biomass had a relatively low coefficient (0.83). We also found relatively high coefficients for allometric relationships between tree height and plant-part biomass, ranging from 0.82 to 0.97. Moreover, there were no differences for allometric equations of total above-ground biomass between study sites. A comparison of equations of above-ground biomass in various previously reported tropical rainforests and pan-tropic general equations imply that our allometric equations differ largely from the equations for tropical primary forests, early successional secondary forest, and even for the general models. Therefore, choosing the biomass estimation models for above-ground biomass in the logged-over forests of Southeast Asia requires careful consideration of their suitability.     

Stem mapping and estimating standing volume from stereoscopic hemispherical images

Sustainable forest management requires knowledge of forest structure and dynamics as well as an estimation of growing stock. The forest inventory provides the data for estimating stand variables. The measurement device MU2005-01738, patented by the Center for Forest Research (INIA-CIFOR), provides stereoscopic hemispherical images which can allow the 3D restoration of the stand around the sampling point. The aim of this study is to develop a methodology for forest stand mapping as well as tree diameter and height measurement along with volume estimation from the stereoscopic hemispherical images provided by the MU2005-01738. Using the MU2005-01738, Eucalyptus globulus Labill. plantations were sampled. Distance, diameter, height and volume were derived from the stereoscopic hemispherical images of 30 trees located at distances ranging from 0 to 15 m from the device. These variables were then compared with field measurements and the estimation errors analyzed. The (root-mean-squared error) RMSE was 0.23 m (8.95 %) for tree position and 1.51 cm (10.43 %) for diameter at breast height measurement at distances of less than 8 m. In the case of stem height and individual tree volume estimation, the RMSE was 2.59 m (23.05 %) and 0.025 m³ (17.94 %), respectively. The analysis of measurement errors indicated that the measurement precision decreases beyond 8 m from the device as well as for directions close to the baseline (the line between the optical centers of the two images), whereas the precision was highest for directions near to the line which is perpendicular to the base line. Future research should focus on improving measurement accuracy and possible applications in the field of forestry of the techniques presented in this study.     

基于无人机影像的森林生物量估测与制图

【目的】森林生物量的精确测定,对于全球气候变化和碳循环研究具有重要的意义。【方法】以东北林业大学城市林业示范基地为研究区域,首先利用无人机平台获取整个研究区域的高分辨率无人机影像;然后在研究区域四种人工林样地中分别选取20 m×20 m的4块建模样方和4块测试样方,通过每木检尺法实测建模样方内林木的树高和胸径数据,建立H-DBH(树高-胸径)估算模型,并结合已有的DBH-SB(胸径-树干生物量)模型得到测试样方的森林生物量数据;在处理后的数字冠层高度模型(DCHM)基础上利用局部最大值法提取树高与树冠中心点位置,建立一种结合无人机影像提取树高与H-SB(树高-树干生物量)经验模型的森林生物量制图方法。【结果】不同样方的H-DBH模型R2均大于0.70,测试样方的总地上生物量平均值为6915.85 kg,总的估测精度为87%。通过ArcGIS软件结合本研究提出的方法快速得到了整个研究区域的地上生物量分布图,估测总地上生物量为4396.18 t。【结论】研究结果可为快速准确的进行森林生物量的估测提供基础数据和技术参考。     

Integration of remote sensing-based bioenergy inventory data and optimal bucking for stand-level decision making

This paper tests the reliability of a biomass prediction procedure which combines aerial data collection, biometric models and optimisation for forest management planning. Tree stock information is obtained by predicting species-specific diameter and height distributions by a combination of field sampling, ALS data and aerial photographs. The subsequent steps in the chain are (1) assignment of the plots to forestry operation classes by means of remote sensing-based tree stock estimates, (2) estimation of the biomass components removed by simulating forestry operations, and (3) estimation of forest owners’ income flow from optimised bucking of the species-specific diameter distributions. The error effects caused by these steps are analysed, and the applicability of remote sensing–based data collection for biomass inventories and planning is assessed. The approach used for assigning the plots to operation classes resulted in moderate accuracies (75%). The reliability estimates indicated quite poor performance when predicting the biomass components removed in forest treatments, with RMSEs of 33.0–69.4% in the case of final cutting and 76.9–228.0% in the case of thinning. The relative RMSEs of the above-ground biomass estimates of the standing stock were about 19%. The relative bias for the biomasses removed was 10.0–88.6% and that for the standing stock biomasses 0.0%. When optimising bucking, the bucked assortments were larger and the incomes enhanced with this estimation method relative to the reference. This explains why the estimation of forest owner’s incomes in the energy wood thinning simulations led to suboptimal decisions and income losses.     

EU-wide maps of growing stock and above-ground biomass in forests based on remote sensing and field measurements

The overall objective of this study was to combine national forest inventory data and remotely sensed data to produce pan-European maps on growing stock and above-ground woody biomass for the two species groups “broadleaves” and “conifers”. An automatic up-scaling approach making use of satellite remote sensing data and field measurement data was applied for EU-wide mapping of growing stock and above-ground biomass in forests. The approach is based on sampling and allows the direct combination of data with different measurement units such as forest inventory plot data and satellite remote sensing data. For the classification, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used. Comprehensive field measurement data from national forest inventories for 98,979 locations from 16 countries were used for which tree species and growing stock estimates were available. The classification results were evaluated by comparison with regional estimates derived independently from the classification from national forest inventories. The validation at the regional level shows a high correlation between the classification results and the field based estimates with correlation coefficient r = 0.96 for coniferous, r = 0.94 for broadleaved and r = 0.97 for total growing stock per hectare. The mean absolute error of the estimations is 25 m³/ha for coniferous, 20 m³/ha for broadleaved and 25 m³/ha for total growing stock per hectare. Biomass conversion and expansion factors were applied to convert the growing stock classification results to carbon stock in above-ground biomass. As results of the classification, coniferous and broadleaved growing stock as well as carbon stock of the above-ground biomass is mapped on a wall-to-wall basis with a spatial resolution of 500 m × 500 m per grid cell. The mapped area is 5 million km², of which 2 million km² are forests, and covers the whole European Union, the EFTA countries, the Balkans, Belarus, the Ukraine, Moldova, Armenia, Azerbaijan, Georgia and Turkey.     

Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume

Carbon accounting, forest health monitoring and sustainable management of the subtropical dry forests of Puerto Rico and other Caribbean Islands require an accurate assessment of forest aboveground biomass (AGB) and stem volume. One means of improving assessment accuracy is the development of predictive equations derived from locally collected data. Forest inventory and analysis (FIA) measured tree diameter and height, and then destructively sampled 30 trees from 6 species at an upland deciduous dry forest site near Ponce, Puerto Rico. This data was used to develop best parsimonious equations fit with ordinary least squares procedures and additive models fit with nonlinear seemingly unrelated regressions that estimate subtropical dry forest leaf, woody, and total AGB for Bucida buceras and mixed dry forest species. We also fit equations for estimating inside and outside bark total and merchantable stem volume using both diameter at breast height (d.b.h.) and total height, and diameter at breast height alone for B. buceras and Bursera simaruba. Model fits for total and woody biomass were generally good, while leaf biomass showed more variation, possibly due to seasonal leaf loss at the time of sampling. While the distribution of total AGB into components appeared to remain relatively constant across diameter classes, AGB variability increased and B. simaruba and B. buceras allocated more carbon into branch biomass than the other species. When comparing our observed and predicted values to other published dry forest AGB equations, the equation developed in Mexico and recommended for areas with rainfall >900 mm/year gave estimates substantially lower than our observed values, while equations developed using dry forest data from forest in Australia, India and Mexico were lower than our observed values for trees with d.b.h. <25 cm and slightly higher for trees with d.b.h. >30 cm. Although our ability to accurately estimate merchantable stem volume and live tree AGB for subtropical dry forests in Puerto Rico and other Caribbean islands has been improved, much work remains to be done to sample a wider range of species and tree sizes.     

Uncertainty estimation of biomass expansion factors for Norway spruce in the Czech Republic

Nation wide estimates of the changes in forest biomass are needed for the greenhouse gas (GHG) reporting under the Climate Convention. The bases for national GHG reporting concerning forest sector are the national forest inventory (NFI) programmes. Since these programmes were mostly established for monitoring of timber resources, one of the current challenges for the NFIs is the development of methodology, such as biomass expansion factors (BEFs). The methodology for carbon stock change estimation should be transparent and verifiable, but this demand is not currently met due to the fact that the source data and uncertainty in the applied BEFs are not known. Here we developed BEFs with uncertainty estimation applicable to stand wise inventory of Norway spruce forests in the Czech Republic. BEFs were constructed, based on tree wise data from permanent research plots, by applying biomass and volume models to tree-level data. These BEFs were age-dependent and their uncertainty was sensitive to the dependencies among errors. Most of the uncertainty in the BEFs was due to uncertainty in the biomass and volume models applied.     

Biomass, basic density and biomass expansion factor functions for European beech (Fagus sylvatica L.) in Denmark

The objective of this study was to analyse the within-tree allocation of biomass and to develop biomass functions for above- and below-ground components of European beech in Denmark. Separate functions were developed for stem, branches, below-ground stump and root system, total above-ground biomass and total tree biomass. For each of these components or aggregate components, models were also developed for the average basic density of wood and bark. To enhance the versatility of the models, a function for estimating the biomass expansion factor (BEF) was also developed. The functions were based on 66 trees measured for total biomass. Model performance was evaluated based on 74 trees measured only for above-ground biomass. The trees were sampled in 18 different forest stands covering a wide range of tree sizes and stand treatments. Models were estimated using a linear mixed-effects procedure to account for within-stand correlations. The functions for biomass and BEFs included only diameter at breast height and total tree height for individual trees as predictor variables. Inclusion of additional variables reflecting site quality or stand density did not improve model performance. The functions for basic density included individual tree diameter, tree height and quadratic mean diameter as predictor variables, indicating an effect of stand density on the basic density of wood and bark.     

利用度量误差模型和分段建模方法建立云南云杉相容性立木材积和地上生物量模型

以云南云杉实测立木材积和地上生物量数据为例,利用度量误差模型方法和分段建模方法建立相容性的一元和二元立木材积和地上生物量模型。结果表明,无论常规模型还是分段模型二元立木材积模型的相关统计指标得到了大幅度的改进,而二元地上生物量模型的相关指标与一元模型相比差异不大;常规二元立木材积模型在小径阶下存在明显的偏差,分段模型从整体上能够有效地解决系统偏差问题;所建的分段一元立木材积模型和地上生物量模型的平均预估精度分别到了90％和95％,同时分段二元立木材积模型和地上生物量模型的平均预估精度均到了97％。     

一个新的通用性相对生长生物量模型

针对West等(1997;1999)提出的理论生物量模型与经验模型存在显著差异的问题,对应用最广的一元生物量模型M=aDb的2个参数进行专题研究。首先,基于几何学的观点推导出参数b的理论值为7/3(≈2.33),与大量已有研究结果的对比表明,该理论参数值能够很好地描述地上生物量与胸径之间的平均相对生长关系;然后,利用包含1441株样木的5组立木生物量数据对新提出的通用性理论模型进行验证;最后,分析参数a与木材密度ρ之间的相关性,并建立二者之间的线性回归模型。新的模型既简单明了,又能反映不同树种之间的生物量差异,可为建立用于区域性和国家级森林生物量估计的通用性生物量模型提供可行途径。     

中国西南地区栎类和桦木立木地上及地下生物量模型研建

依据中国西南地区栎类和桦木的立木材积及生物量实测数据,采用度量误差模型的方法,建立栎类和桦木材积相容的地上生物量及地下生物量模型。结果表明,在地上生物量模型中,增加树高因子,立木材积模型的相关统计指标有较大幅度的改进,栎类和桦木二元材积模型的平均预估精度分别达到了97.86%和97.08%,而二元地上生物量模型的相关统计指标并没明显的改进;两树种一元与二元地下生物量模型的相关统计指标差异并不明显,平均预估精度均达到了90%以上。     

An indicator of tree migration in forests of the eastern United States

Changes in tree species distributions are a potential impact of climate change on forest ecosystems. The examination of tree species shifts in forests of the eastern United States largely has been limited to simulation activities due to a lack of consistent, long-term forest inventory datasets. The goal of this study was to compare current geographic distributions of tree seedlings (trees with a diameter at breast height ≤2.5 cm) with biomass (trees with a diameter at breast height > 2.5 cm) for sets of northern, southern, and general tree species in the eastern United States using a spatially balanced, region-wide forest inventory. Compared to mean latitude of tree biomass, mean latitude of seedlings was significantly farther north (>20 km) for the northern study species, while southern species had no shift, and general species demonstrated southern expansion. Density of seedlings relative to tree biomass of northern tree species was nearly 10 times higher in northern latitudes compared to southern latitudes. For forest inventory plots between 44° and 47° north latitude where southern tree species were identified, their biomass averaged 0.46 tonnes/ha while their seedling counts averaged 2600 ha⁻¹. It is hypothesized that as northern and southern tree species together move northward due to greater regeneration success at higher latitudes, general species may fill their vacated niches in southern locations. The results of this study suggest that the process of northward tree migration in the eastern United States is currently underway with rates approaching 100 km/century for many species.     

贺兰山灰榆疏林单株生物量回归模型的研究

对贺兰山东麓天然灰榆疏林林分进行了调查研究。实测灰榆单株的地上和地下生物量,应用相关分析方法,探讨灰榆单株各器官生物量与树高(H)、胸径(D)、1/2树高处直径(D1/2)和胸径平方乘树高(D2H)的相关关系,结果表明:1)贺兰山东麓天然灰榆疏林单株各器官生物量分配比率为树干>树根>树枝>树皮>树叶。2)各器官生物量拟合的预测模型中,树干、树枝和树叶的生物量预测模型拟合效果较好,而且具有一定的实用价值;树枝和树皮的生物量预测模型拟合效果一般;任一自变量与单株生物量拟合的预测方程适用性均较好。     

Variations in the biomass of Eucalyptus plantations at a regional scale in Southern China

We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method(BEF) versus estimates obtained from a local biomass model,based on large-scale empirical field inventory sampling data.The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method.Relative to the local model,BEF overestimated accumulative biomass by 22.12%.The predominant sources of the total deviation (70.94%) were stand-structure variables.Stand age and diameter at breast height are the major factors.Compared with biotic variables,abiotic variables had a smaller overall contribution (29.06%),with elevation and soil depth being the most important among the examined abiotic factors.Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data.To minimize deviations,stand age and elevation should be included in regional forest-biomass estimation.     

Variations in the biomass of <Emphasis Type="Italic">Eucalyptus</Emphasis> plantations at a regional scale in Southern China

We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method (BEF) versus estimates obtained from a local biomass model, based on large-scale empirical field inventory sampling data. The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method. Relative to the local model, BEF overestimated accumulative biomass by 22.12%. The predominant sources of the total deviation (70.94%) were stand-structure variables. Stand age and diameter at breast height are the major factors. Compared with biotic variables, abiotic variables had a smaller overall contribution (29.06%), with elevation and soil depth being the most important among the examined abiotic factors. Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data. To minimize deviations, stand age and elevation should be included in regional forest-biomass estimation.     

手杖式测树仪立木树高量测研究

[目的]树高是森林经营决策中最重要的一个参量,常用于估计森林生长、年龄、材积、生物量和碳储量等立木参数,其精度对立木质量的评价及森林生长的预测分析影响重大.为解决传统的树高量测仪器移动不便,测量周期长,人力耗损大等问题.[方法]以近景摄影测量为基础,构建了一种以登山杖绑定安卓智能手机为测量平台的便携、快捷的树高测量装备...