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1.
This article reviews the research and application of airborne laser scanning for forest inventory in Finland, Norway and Sweden. The first experiments with scanning lasers for forest inventory were conducted in 1991 using the FLASH system, a full-waveform experimental laser developed by the Swedish Defence Research Institute. In Finland at the same time, the HUTSCAT profiling radar provided experiences that inspired the following laser scanning research. Since 1995, data from commercially operated time-of-flight scanning lasers (e.g. TopEye, Optech ALTM and TopoSys) have been used. Especially in Norway, the main objective has been to develop methods that are directly suited for practical forest inventory at the stand level. Mean tree height, stand volume and basal area have been the most important forest mensurational parameters of interest. Laser data have been related to field training plot measurements using regression techniques, and these relationships have been used to predict corresponding properties in all forest stands in an area. Experiences from Finland, Norway and Sweden show that retrieval of stem volume and mean tree height on a stand level from laser scanner data performs as well as, or better than, photogrammetric methods, and better than other remote sensing methods. Laser scanning is, therefore, now beginning to be used operationally in large-area forest inventories. In Finland and Sweden, research has also been done into the identification of single trees and estimation of single-tree properties, such as tree position, tree height, crown width, stem diameter and tree species. In coniferous stands, up to 90% of the trees represented by stem volume have been correctly identified from canopy height models, and the tree height has been estimated with a root mean square error of around 0.6 m. It is significantly more difficult to identify suppressed trees than dominant trees. Spruce and pine have been discriminated on a single-tree level with 95% accuracy. The application of densely sampled laser scanner data to change detection, such as growth and cutting, has also been demonstrated.  相似文献   

2.
In this paper, we present a study on the efficiency of multi-return LIDAR (Light Detection Ranging) data in the estimation of forest stem volume over a multi-layered forest area in the Italian Alps. The goals of this paper are (1) to verify the usefulness of multi-return LIDAR data compared to single-return data in forest volume estimation and (2) to define the optimal resolution of a stem volume distribution raster map over the investigated area. To achieve these goals, raw data were segmented into a net, and different cell dimensions were investigated to maximize the relationship between the LIDAR data and the ground-truth information. Twenty predicting variables (e.g., mean height, coefficient of variation) have been extracted from multi-return LIDAR data, and a multiple linear regression analysis has been used for predicting tree stem volume. Experimental results found that the optimal resolutions of the net square cells were 40 m. The analysis indicated that in a mixed multi-layered forest, characterized by a complex vertical structure, the correct selection of the map spatial resolution and the inclusion of the secondary-return data were important factors for improving the effectiveness of the laser scanning approach in forest inventories. The experimental tests showed that the chosen model is effective for the estimation of stem volume over the analyzed area, providing good results on all the three considered validation methods.  相似文献   

3.
The aim of this study was to develop prediction models using laser scanning for estimation of forest variables at plot level, validate the estimations at stand level (area 0.64 ha) and test the effect of different laser measurement densities on the estimation errors. The predictions were validated using 29 forest stands (80×80 m2), each containing 16 field plots with a 10 m radius. For the best tested case, mean tree height, basal area and stem volume were predicted with a root mean square error of 0.59 m (3% of average value), 2.7 m2 ha?1 (10% of average value) and 31 m3 ha?1 (11% of average value), respectively, at stand level. There were small differences in terms of prediction errors for different measuring densities. The results indicate that mean tree height, basal area and stem volume can be estimated in small stands with low laser measurement densities producing accuracies similar to traditional field inventories.  相似文献   

4.
Parties to the Kyoto Protocol and/or the United Nations Framework Convention on Climate Change (UNFCCC) are required to account for their direct human-induced carbon emissions and removals including those from forestry and other land use related activities. In most European countries, the forestry related greenhouse gas inventories are largely or exclusively based on converting tree volume data from national forest inventories to biomass using biomass conversion and expansion factors (BCEFs). However, country specific data for many species are often lacking, which considerably increases the uncertainties of the greenhouse gas inventories. The focus of this research was to develop, using internationally published datasets that cover a large geographical area, an extended set of generalized curves of such biomass expansion factors for several species or species groups by age, growing stock and site index.  相似文献   

5.
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.  相似文献   

6.
樟子松人工林单木生物量模型研究   总被引：5，自引：0，他引：5  
以不同林地条件下樟子松人工林为研究对象,根据8块标准地里的40株解析木数据,建立了樟子松人工林单木各分量（包括树干,树枝,树叶和全树重）的预测模型。结果表明,文中所建立的模型精度都高于90％,误差很小,可很好的用于预测樟子松人工林单木的生物量。  相似文献   

7.
以不同林地条件下落叶松人工林为研究对象,根据5块标准地里的25株解析木数据,建立了落叶松人工林单木各分量（包括树干,树枝,树叶和全树重）的预测模型。结果表明：文中所建立树干、全树重的模型精度都高于95%,误差很小,可很好的用于预测落叶松人工林单木的生物量。  相似文献   

8.
Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop models to predict longleaf pine tree diameter at breast height （dbh） and merchantable stem volume （V） using data obtained from field measurements. We used longleaf pine tree data from 3,376 planted trees on 127 permanent plots located in the U.S. Gulf Coastal Plain region to fit equations to predict dbh and V as functions of tree height （H） and crown area （CA）. Prediction of dbh as a function of H improved when CA was added as an additional independent variable. Similarly, predic- tions of V based on H improved when CA was included. Incorporation of additional stand variables such as age, site index, dominant height, and stand density were also evaluated but resulted in only small improvements in model performance. For model testing we used data from planted and naturally-regenerated trees located inside and outside the geographic area used for model fitting. Our results suggest that the models are a robust alternative for dbh and V estimations when H and CA are known on planted stands with potential for naturally-regenerated stands, across a wide range of ages. We discuss the importance of these models for use with metrics derived from remote sensing data.  相似文献   

9.
《林业研究》2021,32(4)
Sustainable forest management heavily relies on the accurate estimation of tree parameters.Among others,the diameter at breast height(DBH) is important for extracting the volume and mass of an individual tree.For systematically estimating the volume of entire plots,airborne laser scanning(ALS) data are used.The estimation model is frequently calibrated using manual DBH measurements or static terrestrial laser scans(STLS) of sample plots.Although reliable,this method is time-consuming,which greatly hampers its use.Here,a handheld mobile terrestrial laser scanning(HMTLS) was demonstrated to be a useful alternative technique to precisely and efficiently calculate DBH.Different data acquisition techniques were applied at a sample plot,then the resulting parameters were comparatively analysed.The calculated DBH values were comparable to the manual measurements for HMTLS,STLS,and ALS data sets.Given the comparability of the extracted parameters,with a reduced point density of HTMLS compared to STLS data,and the reasonable increase of performance,with a reduction of acquisition time with a factor of5 compared to conventional STLS techniques and a factor of3 compared to manual measurements,HMTLS is considered a useful alternative technique.  相似文献   

10.
Abstract

We evaluated the performance of two methods for estimating stem volume increment at individual tree level with respect to bias due to random measurement errors. Here, growth is either predicted as the difference between two consecutive volume estimates where single-tree volume functions are applied to data from repeated measurements or by a regression model that is applied to data from a single survey and includes radial increment. In national forest inventories (NFIs), the first method is typically used for permanent plots, the second for temporary plots. The Swedish NFI combines estimates from both plot types to assess growth at national and regional scales and it is, therefore, important that the two methods provide similar results. The accuracy of these estimates is affected by random measurement errors in the independent variables, which may lead to systematic errors in predicted variables due to model non-linearity. Using Taylor series expansion and empirical data from the Swedish NFI we compared the expected bias in stem volume growth estimates for different diameter classes of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.). Our results indicate that both methods are fairly insensitive to random measurement errors of the size that occur in the Swedish NFI. The empirical comparison between the two methods showed greater differences for large diameter trees of both pine and spruce. A likely explanation is that the regressions are uncertain because few large trees were available for developing the models.  相似文献   

11.
Airborne laser scanning (ALS) data are not usually considered to be very informative with respect to tree species, and this information is often obtained by combining such data with spectral image material. The aim was to test the ability of height, density, intensity and applied 2D and 3D texture variables derived solely from a very high-density ALS point cloud to describe the crown shape and structure characteristics required for tree species discrimination. Linear discriminant analysis was used to find optimal combinations of variables within the predictor groups, and classifications based on variables from different groups were compared. The third power of the tree diameter was used as a stem volume approximate, and rather than examining species alone, the classification was evaluated with respect to the volume approximates assigned to the predicted species. The sensitivity of pulse density to the methodology presented here was determined by simulating thinned data sets by reducing the initial pulse density. The reliability of the estimates was analysed both with functions generated using the original data and with new functions for each thinning level. Alpha shape metrics developed for describing tree crowns constructed from the 3D point clouds proved capable of discriminating between all three species groups evaluated, and several height distribution and textural variables were found to discriminate between the coniferous tree species. The results demonstrate the importance of species interpretation in forest inventories based on allometric modelling, but then indicate that species-specific estimation could be carried out using ALS-derived variables alone.  相似文献   

12.
In this study we assessed the potential of using photogrammetric data for species-specific forest inventories. The method is based on a combination of Dirichlet and ordinary linear regression models. This approach was used to predict species proportions, main tree species, total, and species-specific volume. Structural and spectral variables were used as predictors. The models were validated using 63 independent validation stands. The results from airborne laser scanning (ALS) data combined with spectral data and photogrammetric data obtained using aerial imagery with different forward overlaps of 80% and 60% were compared. The best photogrammetry-based models predicted species proportions with a relative root mean square error (RMSE) of 21.4%, classified dominant species with 79% accuracy, predicted total volume with relative RMSE of 13.4%, and predicted species-specific volume with relative RMSE of 36.6%, 46.5%, and 84.9% for spruce, pine, and deciduous species, respectively. The results were similar for the three point cloud datasets obtained from aerial imagery and ALS and the accuracies of the predictions were comparable to methods used in operational FMI. The study highlights the effectiveness of forest inventories carried out using photogrammetric data, which – differently from ALS, can include species-specific information without relying on multiple data sources.  相似文献   

13.
Double sampling for stratification is a sampling design that is widely used for forest and other resource inventories in forest ecosystems. It is shown that this sampling design can be adapted to repeated inventories including estimators of net change, even for non-proportional allocation of second-phase units and periodically updated stratification. The method accounts for the transition of sampling units among strata. Moreover, it may outperform classical single phase designs if sample plots are appropriately allocated to strata with respect to predefined target variables, here: volume per ha of bigger trees of the main tree species. The latter requires a clear definition of predominant aims of the inventory and an appropriate optimization method. Access to inventory data of a state forest district from two occasions allowed for an optimization of the design based on the first occasion, which proved to be still advantageous on the following occasion. Estimators are developed under the infinite population approach, which is generally deemed more appropriate for forest inventories.  相似文献   

14.
In this article, we present equations derived for the prediction of the aboveground tree volume and phytomass for twenty-five of the most important forest species growing in Italy. These equations result from ongoing research aiming to fill a gap in the models available at the national scale. With regard to volume, the results are particularly important for thirteen species or groups of species that were once scaled with models, conventionally assumed as reference models, available for other species. In Italy, phytomass models had never been constructed at the national level before. For any single tree, specific equations allow estimations of the following tree components to be made: stem and large branches (for either volume or phytomass), small branches (phytomass), stump (phytomass) and the whole tree phytomass. The models have been constructed on the basis of nearly 1,300 sampling units (sample trees). Although these equations must be considered intermediate results of the ongoing research because only half the scheduled number of samples has been collected, they have already been used in the practice, for example in the estimates reported in the recently published second national forest inventory.  相似文献   

15.
Forest variables are typically surveyed using sample plots, from which parameters for large areas are estimated. The diameter at breast height (DBH) is one of the main variables collected in the field and can be used with other forest measures. This study presents an automatic technique for the mapping and measurement of individual tree stems using vertical terrestrial images collected with a fisheye camera. Distinguishable points from the stem surface are automatically extracted in the images, and their 3D ground coordinates are determined by bundle adjustment. The XY coordinates of each stem define an arc shape, and these points are used as observations in a circle fitting by least squares. The circle centre determines the tree position in a local reference system, and the estimated radius is used to calculate the DBH. Experiments were performed in a sample plot to assess the approach and compare it with a technique based on terrestrial laser scanning. In the validation with measurements collected on the stems using a measuring tape, the discrepancies had an average error of 1.46?cm with a standard deviation of 1.09?cm. These results were comparable with the manual measurements and with the values generated from laser point clouds.  相似文献   

16.
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.  相似文献   

17.
《Southern Forests》2013,75(3-4):141-146
Volume equations predict the volume of the stem of a tree from dendrometrical characteristics that are easy to measure, such as diameter and/or height. These equations can serve as a surrogate for biomass equations, by converting the stem volume to stem biomass, and then expanding it to the total aboveground biomass. This is especially important for Central Africa where biomass equations are scarce, whereas volume equations are common. We measured the stem volume of 459 trees in the Yoko forest, Orientale province, Democratic Republic of Congo. These trees belonged to three species: Gilbertiodendron dewevrei (limbali), Guarea thompsonii (bossé foncé) and Scorodophloeus zenkeri (divida). Species-specific volume equations were fitted using these data, and biomass estimates were derived from these volume equations. The fitted volume equations were consistent with other location-specific volume equations for the same species. The biomass estimates derived from the fitted volume equations were also found to be consistent with multispecies pantropical biomass equations.  相似文献   

18.
应用遥感技术、地理信息系统和野外观测数据,评估了热带森林环境下地上生物量和木材蓄积量。用于模拟森林属性的这些数据具有地理特异性和高度的不确定性,因此,这方面需要开展更多的研究工作。选取了16个试样地带1460个样地,测定树木胸径及其他用于评估生物量的其他森林属性。本实验在印尼加里曼丹东部的热带雨林开展。应用现有的胸径-生物量公式来评估地上生物量密度。估测值在研究区修正的GIS地图上重叠显示,计算各种地被物的生物量密度。用样品数据子集表达遥感方法来形成地上生物量和材积线性方程模型。皮尔森相关统计检验采用ETM条带反射率、植被指数、图像变化图层、主成分分析条带、缨帽变换、灰度共生矩阵纹理特征和DEM数据作为预报值。在显著的遥感数据中形成了两个线性模型。为了分析每块地被物总的生物量和材积量,对2000年到2003年卫星ETM图进行了预处理、最大似然估计法分类和主体分析过滤。遥感方法获得的结果表明:材积量为(158±16)m3·hm-2,地上生物量为(168±15)t·hm-2;而野外测定和地理信息系统估计的结果分别是材积量为(157±92)m3·hm-2、地上生物量为(167±94)t·hm-2。用多个瞬间ETM数据评估了从2000年到2003年间的生物量丰富度动态,结果发现这一时期总生物量呈略微的下降趋势。遥感技术评估的生物量丰富度低于地理信息系统和野外测定的结果。前一种测定方法估计2000年和2003年总生物量分别是10.47Gt和10.3Gt,而后一种则估计11.9Gt和11.6Gt。还发现,灰度共生矩阵纹理特征与材积量和生物量之间存在较强的相关性。图7表9参43。  相似文献   

19.
The assessment of a forest resource in national inventories provides a firm basis for the calculation of biomass and carbon (C) stocks of forests. Biomass expansion factors (BEFs) and conversion factors provide a robust and simple method of converting from forest tree stem volume to total forest biomass. These factors should be constructed on the basis of nationally specific data in order to take account of regional differences in growth rates, management practices, etc. The objective of this study is to improve the accuracy of biomass estimation by calculating a range of age-dependant BEFs from representative data that more accurately describe the allometry of present forests. The results from this study show that the allocation of biomass to compartments in forest stands and throughout a rotation varies considerably, and that the use of BEFs for the calculation of C stocks in forests of sub-timber dimensions is highly impractical.
Brian TobinEmail:
  相似文献   

20.
河南省森林碳储量及动态变化研究   总被引：1，自引：1，他引：1  
利用河南省1949—2003年间8次森林资源清查资料,建立不同优势树种生物量与蓄积量之间的回归方程,对河南省54a来森林的碳储量进行了推算。结果表明:河南省54a间森林的总碳储量虽然存在一定的波动现象,但总体呈上升的趋势。全省森林的总碳储量由1949年的2 863.91万t C增加到2003年的4 673.43万t C,共增加1 809.52万t C,年均增加33.51万t C。阔叶林占全省各时期森林总碳储量的80%以上,栎类和杨树两个树种占主导地位。河南森林幼、中龄林占的比重较大。全省森林平均碳密度为22.86~23.64t C/hm2,远低于全国、世界的平均水平。  相似文献   

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