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1.
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   

2.
The aim of this work was to examine how well species-specific stand attributes can be predicted using a combination of airborne laser scanning (ALS) and existing stand register data in urban forests. In this context, the ability of three data combinations: ALS data and stand register data, ALS data and digital aerial images and all of these combined, was tested in the prediction of species-specific basal areas. We divided tree species into seven and three different tree species strata and applied two prediction methods: (1) regression method, in which the predicted total basal area was divided into tree species based on tree species proportions from stand register data, and (2) the nearest neighbour (NN) method, in which tree species proportions were used as predictor variables for species-specific basal areas. Prediction models were built based on training data of 205 field plots, and the accuracy of the models was tested based on validation data of 52 forests stands. Our results showed that species-specific predictions of seven tree species were more accurate when tree species proportions from stand register data were used in the prediction. Both the regression and the NN method provided reasonable accuracy. This study showed that tree species information from existing stand register data could be used as an alternative for aerial images in ALS-based forests inventories. The use of ALS data together with stand register data and small field data could also be economically beneficial in an inventory of urban forests.  相似文献   

3.
Digital maps of forest resources are a crucial factor in successful forestry applications. Since manual measurement of this data on large areas is infeasible, maps must be constructed using a sample field data set and a prediction model constructed from remote sensing materials, of which airborne laser scanning (ALS) data and aerial images are currently widely used in management planning inventories. ALS data is suitable for the prediction of variables related to the size and volume of trees, whereas optical imagery helps in improving distinction between tree species. We studied the prediction of forest attributes using field data from National Forest Inventory complemented with ad hoc field plots in combination with ALS and aerial imagery data in Aland province, Finland. We applied feature selection with genetic algorithm and greedy forward selection and compared multiple linear and nonlinear estimators. Maximally around 40 features from a total of 154 were required to achieve the best prediction performances. Tree height was predicted with normalized root mean squared error value of 0.1 and tree volume with a value around 0.25. Predicting the volumes of spruce and broadleaved trees was the most challenging due to small proportions of these tree species in the study area.  相似文献   

4.
Abstract

An airborne laser scanning (ALS) dominant height model was developed based on data from a national scanning survey with the aim of developing a digital terrain model (DTM) for Denmark. Data obtained in the ongoing Danish national forest inventory (NFI) were used as reference data. The data comprised a total of 2072 measurements of dominant height on NFI sample plots inventoried in 2006–2007 and their corresponding ALS data. The dominant height model included four variables derived from the ALS point cloud distribution. The variables were related to canopy height, canopy density and species composition on individual plots. The RMSE of the final model was 2.25 m and the model explained 93.9% of the variation (R 2). The model was successful in predicting dominant height across a wide range of forest tree species, stand heights, stand densities, canopy cover and growing conditions. The study demonstrated how low-density ALS data obtained in a survey not specifically aimed at forest applications may be used for obtaining biophysical forest properties such as dominant height, thereby reducing the overall forest inventory costs.  相似文献   

5.
The three nonparametric k nearest neighbour (kNN) approaches, most similar neighbour inference (MSN), random forests (RF) and random forests based on conditional inference trees (CF) were compared for spatial predictions of standing timber volume with respect to tree species compositions and for predictions of stem number distributions over diameter classes. Various metrics derived from airborne laser scanning (ALS) data and the characteristics of tree species composition obtained from coarse stand level ground surveys were applied as auxiliary variables. Due to the results of iterative variable selections, only the ALS data proved to be a relevant predictor variable set. The three applied NN approaches were tested in terms of bias and root mean squared difference (RMSD) at the plot level and standard errors at the stand level. Spatial correlations were considered in the statistical models. While CF and MSN performed almost similarly well, large biases were observed for RF. The obtained results suggest that biases in the RF predictions were caused by inherent problems of the RF approach. Maps for Norway spruce and European beech timber volume were exemplarily created. The RMSD values of CF at the plot level for total volume and the species-specific volumes for European beech, Norway spruce, European silver fir and Douglas fir were 32.8, 80.5, 99.0, 137.0 and 261.1%. These RMSD values were smaller than the standard deviation, although Douglas fir volume did not belong to the actual response variables. All three non-parametric approaches were also capable of predicting diameter distributions. The standard errors of the nearest neighbour predictions on the stand level were generally smaller than the standard error of the sample plot inventory. In addition, the employed model-based approach allowed kNN predictions of means and standard errors for stands without sample plots.  相似文献   

6.
We investigated conifer plantation management in Japan using high-resolution airborne data based on an individual tree crown (ITC) approach. This study is the first to apply this technique to Japanese forests. We found that forest resources can be measured at the level of a single tree. We also produced a tree-crown map for a test site with Chamaecyparis obtusa, Pinus densiflora, Larix kaempferi, Cryptomeria japonica, other conifers, and broadleaved trees, with a classification accuracy of 78%. Forest-stand polygons with tree-cover types were generated from this map, a tree-density map, and a crown-occupied-area map. Forest information for the stand polygons was extracted automatically and compared with detailed field-survey data. The error between our ITC estimates and the field-survey data ranged from 0.3 to 30.2%, depending on tree crown size, density, and other factors. Errors were highest for high-density stands with mixed compositions and tree crown diameters ≤5.0 m. However, the error for stands with crown diameters ≥6.2 m was 11.6% or less. Therefore, this technique is best suited to pure Japanese conifer plantations without multiple layers or high-density stands.  相似文献   

7.
Scots pine (Pinus sylvestris L.) and European beech (Fagus sylvatica L.) dominate many of the European forest stands. Also, mixtures of European beech and Scots pine more or less occur over all European countries, but have been scarcely investigated. The area occupied by each species is of high relevance, especially for growth evaluation and comparison of different species in mixed and monospecific stands. Thus, we studied different methods to describe species proportions and their definition as proportion by area. 25 triplets consisting of mixed and monospecific stands were established across Europe ranging from Lithuania to Spain in northern to southern direction and from Bulgaria to Belgium in eastern to western direction. On stand level, the conclusive method for estimating the species proportion as a fraction of the stand area relates the observed density (tree number or basal area) to its potential. This stand-level estimation makes use of the potential from comparable neighboring monospecific stands or from maximum density lines derived from other data, e.g. forest inventories or permanent observations plots. At tree level, the fraction of the stand area occupied by a species can be derived from the proportions of their crown projection area or of their leaf area. The estimates of the potentials obtained from neighboring monospecific stands, especially in older stands, were poorer than those from the maximum density line depending on the Martonne aridity index. Therefore, the stand-level method in combination with the Martonne aridity index for potential densities can be highly recommended. The species’ proportions estimated with this method are best approximated by the proportions of the species’ leaf areas. In forest practice, the most commonly applied method is an ocular estimation of the proportions by crown projection area. Even though the proportions of pine were calculated here by measuring crown projection areas in the field, we found this method to underestimate the proportion by 25% compared to the stand-level approach.  相似文献   

8.
Norway spruce structural timber is one of the most important products of the Norwegian sawmilling industry, and a high grade-yield of structural timber is therefore important for the economic yield. Presorting of logs suited for production of structural timber might be one option to increase the grade yield. In this study, dynamic modulus of elasticity (Edyn) of structural timber was predicted based on forest inventory data at site level and single-tree data from airborne laser scanning (ALS) and harvester. The models were based on 611 boards from 4 sites in southeastern Norway. Important variables at site level were elevation, site index (SI), and mean stand age. However, when combining data from all information sources, mean stand age and site index were the only significant variables at site level. Tree height and variables describing the crown, like crown length and crown volume, were important vaiables extracted from ALS data. Stem diameter measures and tapering were important variables measured by the harvester. The combined model with variables from all three information sources reduced the variance the most, especially when using individual tree age instead of average stand age. However, combining all these data requires accurate positioning of the trees by the harvester.  相似文献   

9.
A timber volume regression model applicable to the state and communal forest area of the federal German state of Rhineland-Palatinate is identified using a combination of airborne laser scanning (ALS)-derived metrics and information from a satellite-based tree species classification map available on the federal state level. As is common in many forest inventory datasets, strong heterogeneity in the ALS data due to different acquisition dates and misclassifications in the tree species classification map had noticeable effects on the regression model’s performance. This article specifically addresses techniques that improve the performance of ordinary least square regression models under such restricting conditions. We introduce a calibration technique to neutralize the effect of misclassifications in the tree species variable that originally caused a residual inflation of 0.05 in adjusted \(R^2\). Incorporating the calibrated tree species information improved the model accuracy by up to 0.07 in adjusted \(R^2\) and suggests the use of such information in forthcoming inventories. We also found that including ALS quality information as categorical variables within the regression model considerably mitigates issues with time lags between the ALS and terrestrial data acquisition and ALS quality variations (increase of 0.09 in adjusted \(R^2\)). The model achieved an adjusted \(R^2\) of 0.48 and a cross-validated root-mean-square error (RMSE\(_{\mathrm{cv}}\)) of 46.7% under incorporation of the tree species and ALS quality information and was thus improved by 0.12 in adjusted \(R^2\) (5% in RMSE\(_{\mathrm{cv}}\)) compared to the simple model only containing ALS height metrics (adjusted \(R^2=0.36\), RMSE\(_{\mathrm{cv}}=51.7\)%).  相似文献   

10.
Masting is a well-marked variation in yields of oak forests. In Japan, this phenomenon is also related to wildlife management and oak regeneration practices. This study demonstrates the capability of integrating remote sensing techniques into mapping spatial variation of acorn production. The hyperspectral images in 72 wavelengths (407–898 nm) were acquired over the study area ten times over a period of three years (2003–2005) during the early growing season of Quercus serrata using the Airborne Imaging Spectrometer Application (AISA) Eagle System. With the canopy spectral reflectance values of 22 sample trees extracted from the images, yield estimation models were developed via multiple linear regression (MLR) analyses. Using the object-oriented classification approach in eCognition, canopies representative of individual oak trees (Q. serrata) were identified from the corresponding hyperspectral imagery and combined with the fitted estimation models developed, acorn yield over the entire forest were estimated and visualized into maps. Three estimation models, obtained for June 27 in 2003, July 13 in 2004 and June 21 in 2005, showed good performance in acorn yield estimation both for the training and validation datasets, all with R2 > 0.4, p < 0.05 and RRMSE < 1 (the relative root mean square of error). The present study shows the potential of airborne hyperspectral imagery not only in estimating acorn yields during early growing seasons, but also in identifying Q. serrata from other image objects, based on which of the spatial distribution patterns of acorn production over large areas could be mapped. The yield map can provide within-stand abundance and valuable information for the size and spatial synchrony of acorn production.  相似文献   

11.
We present a decision support tool for guiding the selection of marked stands based on airborne laser scanning (ALS) data. We describe three stages, namely (1) wall-to-wall mapping of the stands matured for cutting using low-density ALS data; (2) tree-level inventory of these stands using high-density ALS data and (3) theoretical bucking of the imputed tree stems to produce detailed information on their characteristics. We tested them in a Scots pine dominated boreal forest area in Eastern Finland, where 79 sample plots were measured in the field. The detection of the stands matured for cutting had a success rate of 95% and our results demonstrated a further potential to limit the result towards stands dominated by certain species by means of intensity values derived from the low-density ALS data. The applied single-tree detection and estimation chain produced detailed tree-level information and realistic diameter distributions, yet the detection was highly emphasised on the dominant tree layer. The error levels in the estimates were generally less than standard deviations of the field attributes. Finally, plot-level accumulations of saw-log volumes were found rather similar, whether the input was based on the imputed tree data or trees measured in the field. The results are considered useful for ranking the stands based on their properties, whether the aim in the wood procurement is to focus on certain species or to select stands suitable for production needs.  相似文献   

12.
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   

13.
King DA 《Tree physiology》1991,9(3):369-381
Relationships between tree height and crown dimensions and trunk diameter were determined for shade-tolerant species of old-growth forests of western Oregon. The study included both understory and overstory species, deciduous and evergreen angiosperms and evergreen conifers. A comparison of adult understory species with sapling overstory species of similar height showed greater crown width and trunk diameter in the former, whether the comparison is made among conifers or deciduous trees. Conifer saplings had wider crowns than deciduous saplings, but the crown widths of the two groups converged with increase in tree height. Conifer saplings had thicker trunks than deciduous saplings of similar crown width, possibly because of selection for resistance to stem bending under snow loads. The results suggest that understory species have morphologies that increase light interception and persistence in the understory, whereas overstory species allocate their biomass for efficient height growth, thereby attaining the high-light environment of the canopy. The greater crown widths and the additional strength requirements imposed by snow loads on conifer saplings result in less height growth per biomass increment in conifer saplings than in deciduous saplings. However, the convergence in crown width of the two groups at heights greater than 20 m, and the proportionately smaller effect of snow loads on large trees, may result in older conifers equalling or surpassing deciduous trees in biomass allocation to height growth.  相似文献   

14.
机载LiDAR和高光谱融合实现普洱山区树种分类   总被引：4，自引：2，他引：2       下载免费PDF全文
[目的]通过机载遥感影像对普洱山区进行植被分类研究,为山区森林经营规划与可持续经营方案的制图提供高效应用途径。[方法]将2014年4月航拍的机载AISA Eagle II高光谱和Li DAR同步数据融合,利用点云数据提取的数字冠层高度模型(CHM)得到树种的垂直结构信息,结合经过主成分分析(PCA)的高光谱降维影像,选用支持向量机(SVM)分类器进行分类。[结果]普洱市万掌山实验区主要树种分为思茅松、西南桦、刺栲、木荷等。融合影像数据分类的总体精度和Kappa系数分别为80.54%、0.78,比单一高光谱影像数据分类精度分别提高6.55%、0.08,其中主要经营树种思茅松的制图精度达到了90.24%。[结论]该方法对山区主要树种的识别是有效的,将机载Li DAR与高光谱影像融合可以有效改善分类精度。  相似文献   

15.
Abstract

This study compares the results of the prediction of crown height characteristics using airborne laser scanner (ALS) data and intensive field measurements in boreal forests. The data consisted of 31 sample plots located in Kalkkinen, southern Finland. Crown height models were constructed at both the tree and plot level. Scots pine, Norway spruce and birches were used. The models included independent variables of tree levels, such as tree height, crown area and independent plot-level variables, i.e. canopy height and density quantiles and proportion of vegetation hits. Field measurement-based models used tree height and diameter at breast height as the independent tree-level variables, whereas basal area, mean diameter and height were used as the plot-level variables. The results indicated that the ALS-based crown height models were more accurate than the field measurement-based models when plot-level information was used as independent variables. However, the field measurement-based tree-level models for Scots pine and Norway spruce were more accurate than the ALS-based models. Even so, the accuracy of the different models was very similar and the study data set was quite small. The results of this study can be used for different tree growth studies and for the assessment of tree stock quality in boreal forests.  相似文献   

16.
Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree positions. In this paper, we present a raster-based method for determining tree position and delineating crown coverage. We collected data from nine research plots that supported different mixes of species. We applied a raster-based method to raster layers with six different spatial resolutions and used terrestrial measurement data as reference data. Tree identification at a spatial resolution of 1.5 m was demonstrated to be the most accurate, with an average identification ratio (IR) of 95% and average detection ratio of 68% being observed. At a higher spatial resolution of 0.5 m, IR was overestimated by more than 600%. At a lower spatial resolution of 3 m, IR was underestimated at less than 44% of terrestrial measurements. The inventory process was timed to enable evaluation of the time efficiency of automatic methods.  相似文献   

17.
ABSTRACT

Forest productivity is a crucial variable in forest planning, usually expressed as site index (SI). In Nordic commercial forest inventories, SI is commonly estimated by a combination of aerial image interpretation, field assessment and information obtained from previous inventories. Airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) data can alternatively be used for SI estimation, however the economic utilities of the inventory methods have not been compared. We compared seven methods of SI estimation in a cost-plus-loss analysis, by which we added the expected economic losses due to sub-optimal treatment decisions to the inventory costs. The methods comprised direct and indirect estimation from combinations of ALS, DAP and stand register data, and manual interpretation from aerial imagery supported by field assessment and information from previous inventories (conventional practices). The choice of method had great impact on both the accuracy and the economic value of the produced estimates. Direct methods using bitemporal ALS and DAP data gave the best accuracy and the smallest total cost. DAP was a suitable and low-cost data source for SI estimation. Estimation from single-date ALS and DAP data and age obtained from the stand register provided practical alternatives when applied to even-aged stands.  相似文献   

18.
The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the pipe model and the optimal control model provide a framework for expressing the components of tree biomass in terms of three standard inventory variables: tree height, crown height and stem cross-sectional area. Growth rates of the inventory variables and the components of biomass are formulated from a carbon balance. Fundamentally, the parameters of the model comprise physiological rates and morphological ratios. In principle, the values of these parameters may be estimated by lower-level process models. Alternatively, the physiological and morphological parameters combine, under reasonable assumptions, into a set of aggregate parameters, whose values can be estimated from inventory data with a statistical fitting procedure.  相似文献   

19.
Grassland primary productivity is the function that underpins the majority of the fodder production in cattle-rearing silvopastoral farms. Hence, understanding the factors that determine grassland productivity is critical for the design and management of silvpastoral systems. We studied the effect of two factors with documented impact on grassland productivity in seasonally dry silvopastures of Nicaragua, rainfall and trees. We assessed the effects of three species that differed in crown size and phenology, one evergreen, Cassia grandis, and two deciduous species, Guazuma ulmifolia and Tabebuia rosea. Overall, grassland ANPP had a quadratic response to rainfall, with a decline at high rainfall that coincided with peak standing biomass and grassland cover. Trees had a predominately negative effect on grassland productivity, and the effect was concentrated in the rainy season at peak productivity. The effect of the trees corresponded with the tree crown area, but not with crown density. Trees reduced the standing biomass of graminoids and increased forb biomass; thus, the effect of trees on grassland ANPP appears in part to respond to changes in grassland composition. We also found higher levels of soil moisture content below the tree canopy, particularly at the peak of the rainy season when soils tend to become waterlogged. The evergreen species, C. grandis, affected grassland ANPP more strongly than the deciduous species.  相似文献   

20.
The efficiency of a sample-based inventory can be greatly improved if lower cost information on the study area is utilized. It has been observed that the use of airborne laser scanning (ALS) data in the design phase may improve the efficiency of dead wood (coarse woody debris, CWD) volume inventory notably, i.e. a smaller standard error of the mean is observed with the same inventory costs. In the present case, several auxiliary data sources were employed in the design phase by using ‘probability proportional to size’ sampling to select the sample units to be inventoried in the field. It was observed that a combination of ALS data with either aerial photographs or stand-register data can improve the sampling efficiency even more than the use of ALS as a single data source. Since these additional data sources are often gathered for the inventory of living trees, their use does not incur extra expenses for CWD assessment. Thus, the use of these data separately or together with ALS data can greatly improve the cost-efficiency of a CWD volume inventory. It was also observed that the size of the sample units has a slight effect on the sampling efficiency. Even though the improvement in the sampling efficiency was usually greater with larger sample unit sizes, the CWD volume inventory was most efficient with moderate grid cell sizes.  相似文献   

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