scholarly journals Re-calibrating stem volume models – is there change in the tree trunk form from the 1970s to the 2010s in Finland?

Silva Fennica ◽  
2020 ◽  
Vol 54 (4) ◽  
Author(s):  
Annika Kangas ◽  
Helena Henttonen ◽  
Timo Pitkänen ◽  
Sakari Sarkkola ◽  
Juha Heikkinen
Keyword(s):  
Laser Scanning ◽  
Tree Height ◽  
Stem Volume ◽  
Large Dataset ◽  
Forest Inventories ◽  
National Forest Inventories ◽  
Downy Birch ◽  
The Mean ◽  
Volume Models ◽  
Diameter Classes

The tree stem volume models of Norway spruce, Scots pine and silver and downy birch currently used in Finland are based on data collected during 1968–1972. These models include four different formulations of a volume model, with three different combinations of independent variables: 1) diameter at height of 1.3 m above ground (), 2) and tree height () and 3) , and upper diameter at height of 6 m (). In recent National Forest Inventories of Finland, a difference in the mean volume prediction between the models with and without the upper diameter as predictor has been observed. To analyze the causes of this difference, terrestrial laser scanning (TLS) was used to acquire a large dataset in Finland during 2017–2018. Field-measured predictors and volumes predicted using spline functions fitted to the TLS data were used to re-calibrate the current volume models. The trunk form is different in these two datasets. The form height is larger in the new data for all diameter classes, which indicates that the tree trunks are more slender than they used to be. One probable reason for this change is the increase in stand densities, which is at least partly due to changed forest management. In models with both and as predictors, the volume is smaller a given class in the data new data than in the old data, and vice versa for the diameter classes. The differences between the old and new models were largest with pine and smallest with birch.dbhdbhhdbhhd6dbhhh

scholarly journals Augmentation of Traditional Forest Inventory and Airborne Laser Scanning with Unmanned Aerial Systems and Photogrammetry for Forest Monitoring

2018 ◽  
Vol 10 (10) ◽  
pp. 1562 ◽  
Author(s):  
Kathryn Fankhauser ◽  
Nikolay Strigul ◽  
Demetrios Gatziolis
Keyword(s):  
Laser Scanning ◽  
Canopy Cover ◽  
Tree Height ◽  
Forest Monitoring ◽  
Unmanned Aerial Systems ◽  
Aerial Laser Scanning ◽  
Forest Inventories ◽  
Airborne Laser ◽  
Aerial Systems

Forest inventories are constrained by resource-intensive fieldwork, while unmanned aerial systems (UASs) offer rapid, reliable, and replicable data collection and processing. This research leverages advancements in photogrammetry and market sensors and platforms to incorporate a UAS-based approach into existing forestry monitoring schemes. Digital imagery from a UAS was collected, photogrammetrically processed, and compared to in situ and aerial laser scanning (ALS)-derived plot tree counts and heights on a subsample of national forest plots in Oregon. UAS- and ALS-estimated tree counts agreed with each other (r2 = 0.96) and with field data (ALS r2 = 0.93, UAS r2 = 0.84). UAS photogrammetry also reasonably approximated mean plot tree height achieved by the field inventory (r2 = 0.82, RMSE = 2.92 m) and by ALS (r2 = 0.97, RMSE = 1.04 m). The use of both nadir-oriented and oblique UAS imagery as well as the availability of ALS-derived terrain descriptions likely sustain a robust performance of our approach across classes of canopy cover and tree height. It is possible to draw similar conclusions from any of the methods, suggesting that the efficient and responsive UAS method can enhance field measurement and ALS in longitudinal inventories. Additionally, advancing UAS technology and photogrammetry allows diverse users access to forest data and integrates updated methodologies with traditional forest monitoring.

Retrieving individual tree heights from a point cloud generated with optical imagery from an unmanned aerial vehicle (UAV)

2020 ◽  
Vol 50 (10) ◽  
pp. 1012-1024
Author(s):  
Meimei Wang ◽  
Jiayuan Lin
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Point Cloud ◽  
Laser Scanning ◽  
Tree Height ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Surface Model ◽  
Individual Tree ◽  
Aerial Vehicle ◽  
The Mean

Individual tree height (ITH) is one of the most important vertical structure parameters of a forest. Field measurement and laser scanning are very expensive for large forests. In this paper, we propose a cost-effective method to acquire ITHs in a forest using the optical overlapping images captured by an unmanned aerial vehicle (UAV). The data sets, including a point cloud, a digital surface model (DSM), and a digital orthorectified map (DOM), were produced from the UAV imagery. The canopy height model (CHM) was obtained by subtracting the digital elevation model (DEM) from the DSM removed of low vegetation. Object-based image analysis was used to extract individual tree crowns (ITCs) from the DOM, and ITHs were initially extracted by overlaying ITC outlines on the CHM. As the extracted ITHs were generally slightly shorter than the measured ITHs, a linear relationship was established between them. The final ITHs of the test site were retrieved by inputting extracted ITHs into the linear regression model. As a result, the coefficient of determination (R2), the root mean square error (RMSE), the mean absolute error (MAE), and the mean relative error (MRE) of the retrieved ITHs against the measured ITHs were 0.92, 1.08 m, 0.76 m, and 0.08, respectively.

scholarly journals Reliable Estimates of Merchantable Timber Volume from Terrestrial Laser Scanning

2021 ◽  
Vol 13 (18) ◽  
pp. 3610
Author(s):  
Dimitrios Panagiotidis ◽  
Azadeh Abdollahnejad
Keyword(s):  
Laser Scanning ◽  
Accurate Determination ◽  
Laser Scanner ◽  
Terrestrial Laser Scanning ◽  
Tree Height ◽  
Tree Level ◽  
Consensus Method ◽  
Field Methods ◽  
Forest Inventories ◽  
Random Sampling Consensus

Simple and accurate determination of merchantable tree height is needed for accurate estimations of merchantable volume. Conventional field methods of forest inventory can lead to biased estimates of tree height and diameter, especially in complex forest structures. Terrestrial laser scanner (TLS) data can be used to determine merchantable height and diameter at different heights with high accuracy and detail. This study focuses on the use of the random sampling consensus method (RANSAC) for generating the length and diameter of logs to estimate merchantable volume at the tree level using Huber’s formula. For this study, we used two plots; plot A contained deciduous trees and plot B consisted of conifers. Our results demonstrated that the TLS-based outputs for stem modelling using the RANSAC method performed very well with low bias (0.02 for deciduous and 0.01 for conifers) and a high degree of accuracy (97.73% for deciduous and 96.14% for conifers). We also found a high correlation between the proposed method and log length (−0.814 for plot A and −0.698 for plot B), which is an important finding because this information can be used to determine the optimum log properties required for analyzing stem curvature changes at different heights. Furthermore, the results of this study provide insight into the applicability and ergonomics during data collection from forest inventories solely from terrestrial laser scanning, thus reducing the need for field reference data.

scholarly journals Harmonisation of stem volume estimates in European National Forest Inventories

2019 ◽  
Vol 76 (1) ◽  
Author(s):  
Thomas Gschwantner ◽  
Iciar Alberdi ◽  
András Balázs ◽  
Sébastien Bauwens ◽  
Susann Bender ◽  
...  
Keyword(s):  
Stem Volume ◽  
National Forest ◽  
Forest Inventories ◽  
National Forest Inventories ◽  
Volume Estimates

scholarly journals THE EFFECT OF WIND ON TREE STEM PARAMETER ESTIMATION USING TERRESTRIAL LASER SCANNING

2016 ◽  
Vol III-8 ◽  
pp. 117-122 ◽  
Author(s):  
M. T. Vaaja ◽  
J.-P. Virtanen ◽  
M. Kurkela ◽  
V. Lehtola ◽  
J. Hyyppä ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Tree Height ◽  
Individual Tree ◽  
Finnish Meteorological Institute ◽  
Wind Speeds ◽  
Forest Inventories ◽  
Level Data ◽  
Tree Stem

The 3D measurement technique of terrestrial laser scanning (TLS) in forest inventories has shown great potential for improving the accuracy and efficiency of both individual tree and plot level data collection. However, the effect of wind has been poorly estimated in the error analysis of TLS tree measurements although it causes varying deformations to the trees. In this paper, we evaluated the effect of wind on tree stem parameter estimation at different heights using TLS. The data consists of one measured Scots pine captured from three different scanning directions with two different scanning resolutions, 6.3 mm and 3.1 mm at 10 m. The measurements were conducted under two different wind speeds, approximately 3 m/s and 9 m/s, as recorded by a nearby weather station of the Finnish Meteorological Institute. Our results show that the wind may cause both the underestimation and overestimation of tree diameter when using TLS. The duration of the scanning is found to have an impact for the measured shape of the tree stem under 9 m/s wind conditions. The results also indicate that a 9 m/s wind does not have a significant effect on the stem parameters of the lower part of a tree (<28% of the tree height). However, as the results imply, the wind conditions should be taken into account more comprehensively in analysis of TLS tree measurements, especially if multiple scans from different positions are registered together. In addition, TLS could potentially be applied to indirectly measure wind speed by observing the tree stem movement.

Calibration of nationwide airborne laser scanning based stem volume models

2018 ◽  
Vol 210 ◽  
pp. 179-192 ◽  
Author(s):  
Eetu Kotivuori ◽  
Matti Maltamo ◽  
Lauri Korhonen ◽  
Petteri Packalen
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Stem Volume ◽  
Airborne Laser ◽  
Volume Models

Impact of training on different observers in forest inventory

2021 ◽  
Vol 31 (1) ◽  
pp. 12-22
Author(s):  
P. Paudel ◽  
P. Beckschäfer ◽  
C. Kleinn
Keyword(s):  
Forest Inventory ◽  
Tree Height ◽  
Measurement Procedure ◽  
Horizontal Distance ◽  
Limited Information ◽  
Quality Of Data ◽  
Height Measurement ◽  
Forest Inventories ◽  
The Mean ◽  
Level Of Training

Observers with different experience levels are involved in the measurement of large number of sample plots during forest inventories, particularly in national forest inventories. However, limited information exist on the quality of data produced by different observers in forest inventory after certain levels of training. This study tries to evaluate the measurement error in forest inventory associated with observers' experience after initial and field-based training for measuring the most fundamental variables- DBH (cm), total tree height (m), and horizontal distance (m) together with bearing (azimuth) to tree from the plot-centre. On completing the second level of training, the mean of the differences in DBH measurement decreased for both the ‘experienced’ and ‘inexperienced’ groups. The mean of the differences in height measurement in the case of the experienced observers was very low as compared to the inexperienced ones. However, the mean of the differences in azimuth measurement showed that the experienced groups were overestimating by at least 1 degree. There was no trend in deviation of measurement for all four variables regardless of tree size. The decrease in the mean and error of differences in measurements after second training showed that field-based training with supervision and training on the use of instruments at laboratories were required for inexperienced surveyors whereas update in working and measurement procedure would be sufficient for the experienced ones.

National forest inventories in the service of small area estimation of stem volume

2014 ◽  
Vol 44 (9) ◽  
pp. 1079-1090 ◽  
Author(s):  
Steen Magnussen ◽  
Daniel Mandallaz ◽  
Johannes Breidenbach ◽  
Adrian Lanz ◽  
Christian Ginzler
Keyword(s):  
Model Selection ◽  
Small Area ◽  
Small Area Estimation ◽  
Model Averaging ◽  
Stem Volume ◽  
National Forest ◽  
Area Estimation ◽  
Forest Inventories ◽  
Area Effects ◽  
National Forest Inventories

This study introduces five facets that can improve inference in small area estimation (SAE) problems: (1) model groups, (2) test of area effects, (3) conditional EBLUPs, (4) model selection, and (5) model averaging. Two contrasting case studies with data from the Swiss and Norwegian national forest inventories demonstrate the five facets. The target variable of interest was mean stem volume per hectare on forested land in 108 Swiss forest districts (FD) and in 14 Norwegian municipalities (KOM) in the County of Vestfold. Auxiliary variables from airborne laser scanning (Switzerland) and photogrammetric point clouds (Vestfold) with full coverage and a resolution of 25 m × 25 m (Switzerland) and 16 m × 16 m (Vestfold) were available. Only the data metric mean canopy height was statistically significant. Ten linear fixed-effects models and three mixed linear models were assessed. Area effects were statistically significant in the Swiss case but not in Vestfold case. A model selection based on AIC favored separate linear regression models for each FD and a single common regression model in Vestfold. Model averaging increased, on average, an estimated variance by 15%. Reported estimates of uncertainty were consistently larger than corresponding unconditional EBLUPs.

scholarly journals Voxel-Based Automatic Tree Detection and Parameter Retrieval from Terrestrial Laser Scans for Plot-Wise Forest Inventory

2021 ◽  
Vol 13 (4) ◽  
pp. 542
Author(s):  
Gábor Brolly ◽  
Géza Király ◽  
Matti Lehtomäki ◽  
Xinlian Liang
Keyword(s):  
Tree Height ◽  
Parameter Extraction ◽  
Estimation Accuracy ◽  
Tree Crowns ◽  
Tree Detection ◽  
Height Estimates ◽  
Forest Inventories ◽  
Point Density ◽  
Fully Automatic ◽  
The Mean

This paper presents a fully automatic method addressing tree mapping and parameter extraction (tree position, stem diameter at breast height, stem curve, and tree height) from terrestrial laser scans in forest inventories. The algorithm is designed to detect trees of various sizes and architectures, produce smooth yet accurate stem curves, and achieve tree height estimates in multi-layered stands, all without employing constraints on the shape of the crown. The algorithm also aims to balance estimation accuracy and computational complexity. The method’s tree detection combines voxel operations and stem surface filtering based on scanning point density. Stem diameters are obtained by creating individual taper models, while tree heights are estimated from the segmentation of tree crowns in the voxel-space. Twenty-four sample plots representing diverse forest structures in the south boreal region of Finland have been assessed from single- and multiple terrestrial laser scans. The mean percentages of completeness in stem detection over all stand complexity categories are 50.9% and 68.5% from single and multiple scans, respectively, while the mean root mean square error (RMSE) of the stem curve estimates ranges from ±1.7 to ±2.3 cm, all of which demonstrates the robustness of the algorithm. Efforts were made to accurately locate tree tops by segmenting individual crowns. Nevertheless, with a mean bias of −2.9 m from single scans and −1.3 m from multiple scans, the algorithm proved conservative in tree height estimates.

scholarly journals THE EFFECT OF WIND ON TREE STEM PARAMETER ESTIMATION USING TERRESTRIAL LASER SCANNING

2016 ◽  
Vol III-8 ◽  
pp. 117-122 ◽  
Author(s):  
M. T. Vaaja ◽  
J.-P. Virtanen ◽  
M. Kurkela ◽  
V. Lehtola ◽  
J. Hyyppä ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Tree Height ◽  
Individual Tree ◽  
Finnish Meteorological Institute ◽  
Wind Speeds ◽  
Forest Inventories ◽  
Level Data ◽  
Tree Stem

The 3D measurement technique of terrestrial laser scanning (TLS) in forest inventories has shown great potential for improving the accuracy and efficiency of both individual tree and plot level data collection. However, the effect of wind has been poorly estimated in the error analysis of TLS tree measurements although it causes varying deformations to the trees. In this paper, we evaluated the effect of wind on tree stem parameter estimation at different heights using TLS. The data consists of one measured Scots pine captured from three different scanning directions with two different scanning resolutions, 6.3 mm and 3.1 mm at 10 m. The measurements were conducted under two different wind speeds, approximately 3 m/s and 9 m/s, as recorded by a nearby weather station of the Finnish Meteorological Institute. Our results show that the wind may cause both the underestimation and overestimation of tree diameter when using TLS. The duration of the scanning is found to have an impact for the measured shape of the tree stem under 9 m/s wind conditions. The results also indicate that a 9 m/s wind does not have a significant effect on the stem parameters of the lower part of a tree (<28% of the tree height). However, as the results imply, the wind conditions should be taken into account more comprehensively in analysis of TLS tree measurements, especially if multiple scans from different positions are registered together. In addition, TLS could potentially be applied to indirectly measure wind speed by observing the tree stem movement.

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