Comparison of terrestrial laser scanning and X-ray scanning in measuring Scots pine (Pinus sylvestris L.) branch structure

While X-ray scanning is increasingly used to measure the interior quality of logs, terrestrial laser scanning (TLS) could be used to collect information on external tree characteristics. As branches are one key indicator of wood quality, we compared TLS and X-ray scanning data in deriving whorl locations and each whorl’s maximum branch and knot diameters for 162 Scots pine (Pinus sylvestris L.) log sections. The mean number of identified whorls per tree was 37.25 and 22.93 using X-ray and TLS data, respectively. The lowest TLS-derived whorl in each sample tree was an average 5.56?m higher than that of the X-ray data. Whorl-to-whorl mean distances and the means of the maximum branch and knot diameters in a whorl measured for each sample tree using TLS and X-ray data had mean differences of ?0.12?m and ?6.5?mm, respectively. One of the most utilized wood quality indicators, tree-specific maximum knot diameter measured by X-ray, had no statistically significant difference to the tree-specific maximum branch diameter measured from the TLS point cloud. It appears challenging to directly derive comparative branch structure information using TLS and X-ray. However, some features that are extractable from TLS point clouds are potential wood quality indicators.     

运用机载LiDAR数据对橡胶林地上生物量估测的采样尺度效应分析

气候变化下,森林生物量遥感监测是当前研究的热点,机载LiDAR作为重要的遥感信息源,其采样大小对生物量估测精度有着一定的影响。以机载LiDAR数据为信息源,以44块30m×30m的方形橡胶林实测样地数据为基础,对机载激光雷达数据进行不同尺寸采样(共21个采样尺寸,边长从10m至30m,间隔为1m),提取不同采样尺寸下的激光雷达参数,并与橡胶林地上生物量建立PLSR模型,就机载激光雷达采样大小对橡胶林地上生物量估测精度的影响进行研究。研究表明:当采样尺寸小于18m时,估测精度随着采样尺寸的增大而增大;而当采样尺寸大于18m时,估测精度随着采样尺寸的增大而减小,进而趋于平缓。结果虽然呈现出一定的规律性,但是差异并不是很明显。当采样尺寸为18m时估测效果最佳,模型决定系数(R^2)为0.718,均方根误差(RMSE)为17.830 t/hm^2;交叉验证精度P和RMSEcv分别为82.741%和18.874t/hm^2。相较于实际样地(30m)尺寸下的估测结果,18m采样尺寸下的R^2提高了1.989%,RMSEcv降低了2.611%。因此,生物量的估测精度受机载激光雷达数据采样尺寸大小的影响,在生物量估测过程中需结合研究对象和研究区的实际情况对采样尺寸进行选择,从而提高生物量估测精度。     

Estimation of stem attributes using a combination of terrestrial and airborne laser scanning

Properties of individual trees can be estimated from airborne laser scanning (ALS) data provided that the scanning is dense enough and the positions of field-measured trees are available as training data. However, such detailed manual field measurements are laborious. This paper presents new methods to use terrestrial laser scanning (TLS) for automatic measurements of tree stems and to further link these ground measurements to ALS data analyzed at the single tree level. The methods have been validated in six 80 × 80 m field plots in spruce-dominated forest (lat. 58°N, long. 13°E). In a first step, individual tree stems were automatically detected from TLS data. The root mean square error (RMSE) for DBH was 38.0 mm (13.1 %), and the bias was 1.6 mm (0.5 %). In a second step, trees detected from the TLS data were automatically co-registered and linked with the corresponding trees detected from the ALS data. In a third step, tree level regression models were created for stem attributes derived from the TLS data using independent variables derived from trees detected from the ALS data. Leave-one-out cross-validation for one field plot at a time provided an RMSE for tree level ALS estimates trained with TLS data of 46.0 mm (15.4 %) for DBH, 9.4 dm (3.7 %) for tree height, and 197.4 dm³ (34.0 %) for stem volume, which was nearly as accurate as when data from manual field inventory were used for training.     

不同估算树冠生物量方法的比较——以长白落叶松林为例

以长白落叶松人工林为研究对象,应用平均标准木法及枝解析木法调查树冠生物量,并采用标准枝法与枝条模型估算法对估测的树冠生物量进行了比较研究。分析了枝长与枝基径,枝条生物量与枝基径、枝长等各因子的相关关系,建立一级枝长模型及枝条生物量模型。通过对枝条生物量估测模型的比较,结果表明:枝基径与枝条生物量、叶生物量有很高的相关性,幂函数拟合的精度较高,参数估计较稳定;虽然二次多项式模型拟合的相关系数较大,但因参数变动较大,预测不稳定。在树冠生物量模型研究中,基于胸径建立异速生物量模型,相关系数R2值达0.906以上;通过对估测树冠生物量模型的比较,枝条模型估测法优于标准枝法,同时对模型进行F检验,F值达极显著水平,所选枝条生物量模型对长白落叶松树冠生物量的估测具一定参考价值。     

基于异速生长和理论生长方程的广东省木荷生物量动态预测

【目的】将异速生长方程与理论生长方程相结合,预测广东省木荷生物量动态,为广东省木荷林碳汇计量提供模型和方法,为其他树种碳汇计量提供可借鉴的方法学支持。【方法】基于实测样木生物量调查数据,包括40株树干解析资料,构建由胸径和年龄的理论生长方程以及地上生物量和胸径的异速生长方程组成的模型系,利用非线性度量误差联立方程组,在胸径生长速度分级情况下拟合模型参数;基于3期森林资源连续清查固定样地样木数据,对广东省木荷生物量动态进行预测。采用决定系数( R 2)和均方根误差(RMSE)评价模型拟合效果,通过生物量存量估计误差和增量估计误差判断模型预测效果。【结果】在胸径生长速度分级情况下,理论生长方程中年龄对胸径的解释率达0.95以上,比不分级提高0.166 3,均方根误差下降到1.97 cm,降低2.16 cm以上,预测胸径对地上生物量的解释率提高到近0.82;接近独立异速生物量模型中实测胸径对地上生物量的解释率达0.88以上,比不分级提高近0.30,均方根误差下降到51 kg左右,下降30 kg以上。在胸径生长速度不分级情况下,各期生物量存量估计误差变动幅度在-46.31%~77.45%之间,而分级情况下下降到-16.13%~7.06%;在尺度上,分级与不分级均呈相同规律,即单木误差小于林分误差、林分误差小于区域误差。不分级时,单木水平和区域尺度间的误差不大于10%,而分级时小于8%。不同间隔期生物量增量估计误差,不分级时估计值普遍偏大,在32.57%~115.45%之间,而分级时下降到-6.57%~15.77%之间,在单木尺度上不超过±10%;随着尺度增大,增量估计误差不断增加,不分级时单木水平和区域尺度间的误差介于10%~15%之间,分级时稳定在8%左右。【结论】对于理论生长方程和异速生长方程组成的模型系,分级可极大提高模型精度,减小预测估计误差;生长速度不分级时,仅利用胸径或年龄数据,分级时,则可利用2期胸径数据或1期胸径和年龄数据,就可预测未来生物量动态,简单方便,在森林资源连续清查和碳汇造林的碳汇量计量中具有极大应用价值,区域尺度上的估计误差也可基本满足精度要求。     

Crown area allometries for estimation of aboveground tree biomass in agricultural landscapes of western Kenya

Classical allometries determine biomass from measurements of diameter at breast height or volume. Neither of these measurements is currently possible to be derived directly from remote sensing. As biomass estimates at larger scales require remotely sensed data, new allometric relations are required using crown area and/or tree height as predictor of biomass, which can both be derived from remote sensing. Allometric equations were developed from 72 trees semi-randomly selected for destructive sampling in three 100?km² sentry sites in western Kenya. The equations developed fit the data well with about 85?% of the observed variation in aboveground biomass explained by crown area. Addition of height and wood density as second predictor variables improved model fit by 6 and 2?% and lowered the relative error by 7 and 2?%, respectively. The equation with crown area in combination with height and wood density estimated representative aboveground biomass carbon to be about 20.8?±?0.02?t?C?ha^?1; which is about 19?% more than the amount estimated using an allometry with diameter at breast height as predictor. These results form the basis for a new generation of allometries using crown area as a predictor of aboveground biomass in agricultural landscapes. Biomass predictions using crown area should be supported by height and wood density and the application of crown area equations for remote sensing based up-scaling should consider crown interactions with competing or coexisting neighboring trees.     

Allometric equations for biomass estimations in Cameroon and pan moist tropical equations including biomass data from Africa

Moist tropical forests in Africa and elsewhere store large amounts of carbon and need accurate allometric regressions for their estimation. In Africa the absence of species-specific or mixed-species allometric equations has lead to broad use of pan moist tropical equations to estimate tree biomass. This lack of information has raised many discussions on the accuracy of these data, since equations were derived from biomass collected outside Africa.     

A method for 3D reconstruction of tree crown volume from photographs: assessment with 3D-digitized plants

We developed a method for reconstructing tree crown volume from a set of eight photographs taken from the N, S, E, W, NE, NW, SE and SW. This photographic method of reconstruction includes three steps. First, canopy height and diameter are estimated from each image from the location of the topmost, rightmost and leftmost vegetated pixel; second, a rectangular bounding box around the tree is constructed from canopy dimensions derived in Step 1, and the bounding box is divided into an array of voxels; and third, each tree image is divided into a set of picture zones. The gap fraction of each picture zone is calculated from image processing. A vegetated picture zone corresponds to a gap fraction of less than 1. Each picture zone corresponds to a beam direction from the camera to the target tree, the equation of which is computed from the zone location on the picture and the camera parameters. For each vegetated picture zone, the ray-box intersection algorithm (Glassner 1989) is used to compute the sequence of voxels intersected by the beam. After processing all vegetated zones, voxels that have not been intersected by any beam are presumed to be empty and are removed from the bounding box. The estimation of crown volume can be refined by combining several photographs from different view angles. The method has been implemented in a software package called Tree Analyzer written in C++. The photographic method was tested with three-dimensional (3D) digitized plants of walnut, peach, mango and olive. The 3D-digitized plants were used to estimate crown volume directly and generate virtual perspective photographs with POV-Ray Version 3.5 (Persistence of Vision Development Team). The locations and view angles of the camera were manually controlled by input parameters. Good agreement between measured data and values inferred from the photographic method were found for canopy height, diameter and volume. The effects of voxel size, size of picture zoning, location of camera and number of pictures were also examined.     

Estimation of aboveground biomass in mangrove forests using high-resolution satellite data

Mangroves play important roles in providing a range of ecosystem services, mitigation of strong waves, protection of coastlines against erosion, maintenance of water quality, and carbon sink in the context of global warming. For trees in mangrove forests in southern Ranong Province, Thailand, we investigated the allometric relationship between crown area derived from high-resolution satellite data and stem diameter and used the resulting model to estimate aboveground biomass. We used QuickBird panchromatic and multispectral data acquired for the study area on 15 October 2006 as the high-resolution satellite data. Individual tree crowns were extracted from the satellite image of panchromatic data by using the watershed method, and the species were identified by using the maximum-likelihood method for the multispectral data. Overall classification accuracy for species identification was 88.5 %. The biomass derived from our field survey was plotted against aboveground biomass in the sample plots, estimated from the QuickBird data. The regression line through the origin between the satellite-estimated biomass and biomass based on the field data had a slope of 1.26 (R ² = 0.65). Stand aboveground biomass estimated from the high-resolution satellite data was underestimated because of a lack of data on the biomass of suppressed trees and inappropriate segmentation of crowns of large trees into two or more trees.     

Allometric equations for aboveground biomass estimation by size class for Pinus brutia Ten. trees growing in North and South Aegean Islands, Greece

Empirical allometric equations relating biomass of aboveground components to dendrometric variables for Pinus brutia Ten. trees are derived in this paper. They are based on data collected from Lesvos (North Aegean Sea) and Crete (South Aegean Sea) Islands. Comparisons to published equations for the same species growing in northwestern and southeastern Turkey, for Pinus nigra A. growing in Turkey and Pinus halepensis Mill. found in Western Aegean (island of Evia), are also presented. The biomass of branches from destructively sampled trees (twelve in Crete and six in Lesvos) was divided into four size classes (0?C0.63 cm, 0.64?C2.5 cm, 2.51?C7.61 cm, and 7.62?C22.8 cm). Tree crown biomass was calculated as the sum of the biomass in the four classes plus the fraction of stem above crown base. Over bark stem biomass was estimated through bole volume conversion based on wood density. The results showed clearly that, for a given diameter, the Cretan trees had more crown biomass and a higher share of small branches than trees on Lesvos, probably due to differences in environment and stand structure. Comparisons to published diameter versus crown biomass equations reveal a lower crown biomass for Turkish sites of Calabrian pine and Aleppo pine on Evia Island, while only Turkish Black pine seems to be comparable to the Calabrian pine on Crete. The derived allometries can be used for landscape fire behavior modeling, for ecophysiological studies and for the Kyoto protocol requirements of carbon changes in Pinus brutia Ten. forests located in northern and southern Greek sites.     

Ontogeny partly explains the apparent heterogeneity of published biomass equations for Fagus sylvatica in central Europe

A set of robust biomass equations was developed for European beech (Fagus sylvatica), using a large database made of trees from three different European countries. Models were calibrated on the French control dataset, including a broad range of tree size, age and geographical conditions. Their independent validation on Belgian, German unfertilized, German and French fertilized stands gave very promising unbiased results for all of the main tree compartments. The basic fitted allometric equation (biomass = β × (d²h)^γ) allowed us to work with biologically meaningful parameters, where β encompasses both the form of the tree and the wood density, and γ is the allometric exponent that indicates the proportionality between the biomass and volume relative increments. The allometric parameters were found to vary with stand age (decreasing for the crown and increasing for the bole), and introducing these parameters to the equations significantly improved the performance of all aboveground biomass equations. This age effect was related to changes in both stem form and wood density for the trunk and to changes in hydraulic conductance for the crown. We argue that introducing stand age into the predictive parameters is the key for the accuracy of our equations. Management options and stand fertility stand for the low residual variations around this relationship. To confirm this result, we were able to homogenize most of the published biomass equations by accounting for the stand age given in each original paper. We noticed that our results were consistent with and matched the patterns that were observed for Eucalyptus (Eucalyptus). This could mean that species with similar wood properties and crown architecture may exhibit similar biomass equation structures.     

Comparison between TanDEM-X- and ALS-based estimation of aboveground biomass and tree height in boreal forests

Interferometric Synthetic Aperture Radar (InSAR) data from TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) were used to estimate aboveground biomass (AGB) and tree height with linear regression models. These were compared to models based on airborne laser scanning (ALS) data at two Swedish boreal forest test sites, Krycklan (64°N19°E) and Remningstorp (58°N13°E). The predictions were validated using field data at the stand-level (0.5–26.1 ha) and at the plot-level (10 m radius). Additionally, the ALS metrics percentile 99 (p99) and vegetation ratio, commonly used to estimate AGB and tree height, were estimated in order to investigate the feasibility of replacing ALS data with TanDEM-X InSAR data. Both AGB and tree height could be estimated with about the same accuracy at the stand-level from both TanDEM-X- and ALS-based data. The AGB was estimated with 17.2% and 14.6% root mean square error (RMSE) and the tree height with 7.6% and 4.1% RMSE from TanDEM-X data at the stand-level at the two test sites Krycklan and Remningstorp. The Pearson correlation coefficients between the TanDEM-X height and the ALS height p99 were r?=?.98 and r?=?.95 at the two test sites. The TanDEM-X height contains information related to both tree height and forest density, which was validated from several estimation models.     

油松当年生小枝异速生长规律研究

通过标准化主轴估计分析了10余年生油松一级枝、二级枝、三级枝的当年生小枝的异速生长规律,包括当年生小枝的节间生物量-节间长度、节间生物量-针叶生物量、节间截面积-节间生物量、节间截面积-针叶生物量两两相关关系,进而剖析了油松当年生小枝的生物量分配方式、传输模式和形态结构关系,并通过独立样本进行检验。结果表明,异速生长关系的相关关系均非常显著,观测值和预估值之间的相关系数除了节间截面积和针叶生物量外均大于0.85,说明上述异速生长关系的相关关系非常显著;一级枝、二级枝、三级枝的SMA斜率没有明显差异,说明不同级别的枝的异速生长关系是相同的;小枝生物量和叶生物量的权度关系明显小于1;叶生物量和小枝截面积的权度关系接近于1,说明二者为等速生长。     

Allometric models for leaf area and leaf mass predictions across different growing seasons of elm tree (<Emphasis Type="Italic">Ulmus japonica</Emphasis>)

Convenient and effective methods to determine seasonal changes in individual leaf area (LA) and leaf mass (LM) of plants are useful in research on plant physiology and forest ecology. However, practical methods for estimating LA and LM of elm (Ulmus japonica) leaves in different periods have rarely been reported. We collected sample elm leaves in June, July and September. Then, we developed allometric models relating LA, LM and leaf parameters, such as leaf length (L) and width (W) or the product of L and W (LW). Our objective was to find optimal allometric models for conveniently and effectively estimating LA and LM of elm leaves in different periods. LA and LM were significantly correlated with leaf parameters (P < 0.05), and allometric models with LW as an independent variable were best for estimating LA and LM in each period. A linear model was separately developed to predict LA of elm leaves in June, July and September, and it yielded high accuracies of 93, 96 and 96%, respectively. Similarly, a specific allometric model for predicting LM was developed separately in three periods, and the optimal model form in both June and July was a power model, but the linear model was optimal for September. The accuracies of the allometric models in predicting LM were 88, 83 and 84% for June, July and September, respectively. The error caused by ignoring seasonal variation of allometric models in predicting LA and LM in the three periods were 1–4 and 16–59%, respectively.     

Estimating models of vegetation fractional coverage based on remote sensing images at different radiometric correction levels

The images of post atmospheric correction reflectance (PAC), top of atmosphere reflectance (TOA), and digital number (DN) of a SPOT5 HRG remote sensing image of Nanjing, China were used to derive four vegetation indices (VIs), that is, normalized difference vegetation index (NDVI), transformed vegetation index (TVI), soil-adjusted vegetation index (SAVI), and modified soil-adjusted vegetation index (MSAVI). Based on these VIs and the vegetation fractional coverage (VFC) data obtained from field measurements, thirty-six VI-VFC relationship models were established. The results showed that cubic polynomial models based on NDVI and TVI from PAC were the best, followed by those based on SAVI and MSAVI from DN, with their accuracies being slightly higher than those of the former two models when VFC>0.8. The accuracies of these four models were higher in medium densely vegetated areas (VFC = 0.4–0.8) than in sparsely vegetated areas (VFC = 0–0.4). All the models could be used elsewhere via the introduction of a calibration model. In VI-VFC modeling, using VIs derived from different radiometric correction levels of remote sensing images could help explore and show valuable information from remote sensing data and thus improve the accuracy of VFC estimation.     

Functions for estimating aboveground biomass of birch in Norway

A suite of regional allometric aboveground biomass functions were derived for Betula pubescens and Betula pendula for Norwegian conditions. The data consisted of 67 trees sampled throughout Norway. A total of 14 component functions were developed for total aboveground, total stem, stemwood, stem bark, live crown, live branch, leaf, and dead branch biomass using combinations of diameter at breast height and height as predictor variables. Application of the derived functions to existing local southern Norwegian mountain birch and regional Swedish biomass datasets indicated an overall good predictive ability of the developed functions. However, the functions produced slight underestimates, suggesting that the respective birch populations had differing biomass allocation patterns. When the developed functions were applied to Norwegian National Forest Inventory data, they produced slightly higher biomass stock and stock change estimates than what is obtained using existing Swedish functions. The higher estimates were evident in the north, central, and western part of Norway, while estimates were similar in southeastern Norway where growing conditions are most similar to Swedish conditions. The analysis indicates that the derived functions are the best available for regional birch biomass stock and stock change estimation in Norway.     

Species-specific biomass allometric models and expansion factors for indigenous and planted forests of the Mozambique highlands

Secondary Miombo woodlands and forest plantations occupy increasing areas in Mozambique, the former due to anthropogenic activities. Plantations, mainly species of Eucalyptus and Pinus, are being established on sites previously covered by secondary Miombo woodlands. This affects the evolution, cycle and spatiotemporal patterns of carbon(C) storage and stocks in forest ecosystems. The estimation of C storage, which is indispensable for formulating climate change policies on sequestrating CO_2, requires tools such as biomass models and biomass conversion and expansion factors(BCEF). In Mozambique, these tools are needed for both indigenous forests and plantations. The objective of this study is to fit species-specific allometric biomass models and BCEF for exotic and indigenous tree species. To incorporate efficient inter-species variability, biomass equations were fitted using nonlinear mixed-effects models. All tree component biomass models had good predictability; however, better predictive accuracy and ability was observed for the 2-predictors biomass model with tree height as a second predictor. The majority of the variability in BCEF was explained by the variation in tree species. Miombo species had larger crown biomass per unit of stem diameter and stored larger amounts of biomass per stem volume. However, due to relatively rapid growth, larger stem diameters, heights, and stand density, the plantations stored more biomass per tree and per unit area.     

Allometric relations for biomass partitioning of Nothofagus antarctica trees of different crown classes over a site quality gradient

Data on tree biomass are essential for understanding the forest carbon cycle and plant adaptations to the environment. We determined biomass accumulation and allometric relationships in the partitioning of biomass between aboveground woody biomass, leaves and roots in Nothofagus antarctica. We measured above- and belowground biomass of N. antarctica trees across different ages (5–220 years) and crown classes (dominant, codominant, intermediate and suppressed) in three site qualities. The biomass allocation patterns were studied by fitting allometric functions in biomass partitioning between leaves (M_L), stem and branches (M_S) and roots (M_R). These patterns were tested for all pooled data and according to site quality and crown classes. Biomass accumulation varied with crown class and site quality. The root component represented 26–72% of the total biomass depending on age and site. N. antarctica scaling exponents for the relationships M_Lvs. M_S, M_Avs. M_R, and M_Svs. M_R were close to those predicted by the allometric biomass partitioning model. However, when biomass allocation was analyzed by site quality the scaling exponents varied following the optimal partitioning theory which states that plants should allocate more biomass to the part of the plant that acquires the most limiting resource. In contrast, the crown class effect on biomass partitioning was almost negligible. In conclusion, to obtain accurate estimations of biomass in N. antarctica trees the allometric approach appears as an useful tool but the site quality should be taken into consideration.     

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.