Comparing biophysical forest characteristics estimated from photogrammetric matching of aerial images and airborne laser scanning data

Recent development in aerial digital cameras and software facilitate the photogrammetric point cloud as a new data source in forest management planning. A total of 151 field training plots were distributed systematically within three predefined strata in a 852.6 ha study area located in the boreal forest in southeastern Norway. Stratum-specific regression models were fitted for six studied biophysical forest characteristics. The explanatory variables were various canopy height and canopy density metrics derived by means of photogrammetric matching of aerial images and small-footprint laser scanning. The ground sampling distance was 17 cm for the images and the airborne laser scanning (ALS) pulse density was 7.4 points m^–2. Resampled images were assessed to mimic acquisitions at higher flying altitudes. The digital terrain model derived from the ALS data was used to represent the ground surface. The results were evaluated using 63 independent test stands. When estimating height in young forest and mature forest on poor sites, the root mean square error (RMSE) values were slightly better using data from image matching compared to ALS. However, for all other combinations of biophysical forest characteristics and strata, better results were obtained using ALS data. In general, the best results were found using the highest image resolution.     

Aerial photo-interpretation using Z/I DMC images for estimation of forest variables

Abstract

Interpretation and tree height measurements in aerial photographs using photogrammetric workstations are frequently performed in standwise forest inventory. Images acquired by digital aerial cameras are now replacing the traditional film-based aerial photographs. In this study, digital images from the airborne Z/I DMC system for standwise estimation of stem volume, tree height and tree species composition were investigated at a 1200 ha forest area located in southern Sweden (58°30′N, 13°40′E). The 56 selected stands were dominated by Norway spruce [Picea abies (L.) Karst.] and Scots pine (Pinus sylvestris L.) with stem volume in the range of 30–630 m³ ha^?1 (average 300 m³ ha^?1) and tree height in the range of 6–28 m (average 20 m). The large-format pansharpened colour infrared images were captured at a flight altitude of 4800 m above ground level corresponding to a pixel size of 0.48 m. The photo-interpretation was conducted by four professional interpreters, independently. In particular, two different base-to-height ratios (i.e. the ratio between the ground distance between image centres at the time of exposure and the flight altitude above ground level) of 0.26 and 0.39 were evaluated, but no significant difference in the estimation accuracy for stem volume and tree height was found. The accuracy for stem volume estimation in terms of relative root mean square error, corrected for systematic errors, was on average 24% (in the range of 17–39%). The corresponding accuracy for tree height estimation was on average 1.4 m (in the range of 0.9–1.6 m). The tree species composition accuracy assessment using a fuzzy set evaluation procedure showed that 95% of the stands were correctly classified. The estimation accuracies are in agreement with previous results using conventional film-based aerial panchromatic photographs.     

Calibration of laser-derived tree height estimates by means of photogrammetric techniques

Techniques based on laser point clouds and digital terrestrial images were demonstrated for the calibration of tree-height estimation. Individual tree heights can be roughly estimated from laser scanning data by using the approximated ground level and the highest hit of the treetop. However, laser-derived measurements often underestimate tree heights. This underestimation can arise from various error sources. Digital terrestrial images can be used to verify and understand the behaviour of laser point clouds. When laser data are backprojected in a close-range image, it is possible to show where each laser beam has reflected. This, however, requires a proper orientation of the images. In this study an interactive orientation method was used to derive image orientations, using one laser strip at a time as the reference data. Consequently, the backprojection of laser point clouds confirmed the height underestimations found by comparing the tacheometer reference measurements with the laser-derived tree heights. In addition, by using the described procedure the cause of underestimating tree heights could be explained.     

Economic utility of 3D remote sensing data for estimation of site index in Nordic commercial forest inventories: a comparison of airborne laser scanning,digital aerial photogrammetry and conventional practices

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.     

Practical large-scale forest stand inventory using a small-footprint airborne scanning laser

Mean tree height, dominant height, mean diameter, stem number, basal area and timber volume of 116 georeferenced field sample plots were estimated from various canopy height and canopy density metrics derived by means of a small-footprint laser scanner over young and mature forest stands using regression analysis. The sample plots were distributed systematically throughout a 6500 ha study area, and the size of each plot was 232.9 m². Regressions for coniferous forest explained 60–97% of the variability in ground reference values of the six studied characteristics. A proposed practical two-phase procedure for prediction of corresponding characteristics of entire forest stands was tested. Fifty-seven test plots within the study area with a size of approximately 3740 m² each were divided into 232.9 m² regular grid cells. The six examined characteristics were predicted for each grid cell from the corresponding laser data using the estimated regression equations. Average values for each test plot were computed and compared with ground-based estimates measured over the entire plot. The bias and standard deviations of the differences between predicted and ground reference values (in parentheses) of mean height, dominant height, mean diameter, stem number, basal area and volume were ?0.58 to ?0.85 m (0.64–1.01 m), ?0.60 to ?0.99 m (0.67–0.84 m), 0.15–0.74 cm (1.33–2.42 cm), 34–108 ha^?1 (97–466 ha^?1), 0.43–2.51 m² ha^?1 (1.83–3.94 m² ha^?1) and 5.9–16.1 m³ ha^?1 (15.1–35.1 m³ ha^?1), respectively.     

Using canopy heights from digital aerial photogrammetry to enable spatial transfer of forest attribute models: a case study in central Europe

This paper describes a workflow utilizing detailed canopy height information derived from digital airphotos combined with ground inventory information gathered in state-owned forests and regression modelling techniques to quantify forest-growing stocks in private woodlands, for which little information is generally available. Random forest models were trained to predict three different variables at the plot level: quadratic mean diameter of the 100 largest trees (d₁₀₀), basal area weighted mean height of the 100 largest trees (h₁₀₀), and gross volume (V). Two separate models were created – one for a spruce- and one for a beech-dominated test site. We examined the spatial portability of the models by using them to predict the aforementioned variables at actual inventory plots in nearby forests, in which simultaneous ground sampling took place. When data from the full set of available plots were used for training, the predictions for d₁₀₀, h₁₀₀, and V achieved out-of-bag model accuracies (scaled RMSEs) of 15.1%, 10.1%, and 35.3% for the spruce- and 15.9%, 9.7%, and 32.1% for the beech-dominated forest, respectively. The corresponding independent RMSEs for the nearby forests were 15.2%, 10.5%, and 33.6% for the spruce- and 15.5%, 8.9%, and 33.7% for the beech-dominated test site, respectively.     

Laser scanning of forest resources: the nordic experience

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.     

0.5M分辨率航摄数字影像数据在森林资源规划设计调查中的应用

以0.5 M分辨率航摄数字影像数据为基础,结合以往调查设计及经营资料,对森林资源规划设计调查小班的部分因子进行判读,探讨高分辨率航摄数字影像数据在森林资源规划设计调查中的应用,结果表明:利用0.5M分辨率航摄数字影像数据进行小班因子判读,可以作为小班因子调查的辅助手段,并可显著提高小班调查质量及效率。     

Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia

Abstract

This research reports the major evaluation results from an operational stand-based forest inventory using airborne laser scanner data carried out in Norway. This is the first operational inventory in which data from two separate districts are combined. Laser data from two forest areas of 65 and 110 km² were used to predict six biophysical stand variables used in forest planning. The predictions were based on regression equations estimated from 250 m² field training plots distributed systematically throughout the two forest areas. Test plots with a size of 0.1 ha were used for validation. The testing revealed standard deviations between ground-truth values and predicted values of 0.58–0.85 m (3.4–5.6%) for mean and dominant heights, 2.62–2.87 m² ha^?1 (9.3–14.3%) for basal area, and 18.7–25.1 m³ ha^?1 (10.8–12.8%) for stand volume. No serious bias was detected. For 10 of the 12 estimated regression models there were no significant effects of district.     

海南岛热带天然次生林生长动态研究

本文对两类处于不同演替阶段的天然次生林,从直径生长、胸高断面积生长、材积生长、林木死亡率等方面进行了对比分析。研究结果表明:随着演替的进程,天然次生林直径生长、胸高断面生长和材积生长呈现下降趋势,林木死亡率也呈现明显的下降趋势,其主要原因是,在演替的早期阶段,速生喜光先锋种在林分中占据较高比例,进而林分表现出较高的死亡率和较高的生长力,但是随着演替的进行,喜光先锋速生树种逐步被耐荫的顶级或亚顶级树种所取代,进而表现出低生长和低的死亡率。     

Estimation of forest stem volume using multispectral optical satellite and tree height data in combination

Abstract

The accuracy of forest stem volume estimation at stand level was investigated using multispectral optical satellite and tree height data in combination. The stem volumes for the investigated coniferous stands, located in southern Sweden, were in the range of 15–585 m³ ha^?1 with an average stem volume of 266 m³ ha^?1. The results from regression analysis showed a substantial improvement for the combined stem volume estimates compared with using satellite data only. The accuracy in terms of root mean square error (RMSE) was calculated to 11.2% of the average stem volume using SPOT-4 data and tree height data in combination compared with 23.9% using SPOT-4 data only. By replacing SPOT-4 data with Landsat TM data the RMSE was improved from 25.2% to 12.2%. In addition, a sensitivity analysis was performed on the combined stem volume estimates by adding random errors, normally distributed with zero expectations, with standard deviations of 1, 1.5 and 2 m to tree height data. The results showed that the RMSE increased with increasing random tree height error to 15.4%, 18.0% and 19.9% using SPOT-4 data and 16.3%, 19.2% and 21.2% using Landsat TM data. The results imply that multispectral optical satellite data in combination with accurate tree height data could be used for standwise stem volume estimation in forestry applications.     

地面三维激光扫描技术在林业中的应用与展望

以地面三维激光扫描技术的测量原理、技术特征为切入点, 重点论述了该技术在国内外林业领域的应用现状、不足及前景。与传统研究手段相比, 地面三维激光扫描技术在测树效率、三维建模、模型化精度等方面具有较大的优势, 显示出更广阔的应用前景。     

Assessment of bias due to random measurement errors in stem volume growth estimation by the Swedish National Forest Inventory

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.     

Preliminary estimation of carbon stock in a logging concession with a forest management plan in East Cameroon

ABSTRACT

Logging operations in Cameroon are based on the extraction of wood from natural forests. In this article, we assessed the carbon stock in a forest management unit (FMU) located in East Cameroon from field inventory to postfelling operations up to sawmill and export terminals. Tree basal area and aboveground biomass were calculated based on trees inventoried in the annual allowable cut. We observed that from an exploitable tree potential of 0.696 trees ha^?1 inventoried within a diameter range of 50–110 cm, 0.141 tree ha^?1 (i.e., 20% of the inventoried trees) were logged. In other words, out of 6.78 tC ha^?1 inventoried, 1.84 tC ha^?1 (i.e., 27% was logged), 1.62 tC ha^?1 arrived in the log yard and 1.3 tC ha^?1 arrived in sawmill, while 0.32 tC ha^?1 reached the export terminal. In terms of damages caused on vegetation, 4.45% of all the annual allowance cut (AAC) were affected during logging activities, this represents almost 33,188.07 tons of carbon. These findings show that the implementation of reduced-impact logging (RIL) could reduce these losses throughout the logging steps and help propose a process for the valuation of wood waste in the forest and sawmill. In this context, reducing emissions from deforestation and degradation will be engaged with the right approach.     

Stem quality assessment using terrestrial laser scanning technology: a case study of ash trees with a range of defects in two stands in Ireland

Information on stem quality of standing (broadleaf) timber is of great importance to the forestry sector to help optimise harvesting and marketing strategies. Manual assessment of such quality parameters in standing trees is extremely difficult, time consuming and costly. The objectives of this study were therefore to assess stem quality parameters such as taper, lean and sweep in ash (Fraxinus excelsior L.) stands, during leaves-on and leaves-off conditions, using terrestrial laser scanning technology, and to compare the estimated parameters with manually measured values in a mature and young stand. Diameter estimation was more accurate during the leaves-off condition in both stands, resulting in taper estimates that were closer to the manually obtained values as well. However, in general, the taper values did not match those obtained manually very closely. Given that the sample trees were chosen deliberately to include noticeable defects such as non-circularity, bending, swellings, knots resulting from the removal of branches and multiple leaders, this is not surprising. It probably is the case that the scanned data capture these defects more accurately than the manually collected data, especially when multi-scan data are used.