The accuracy of estimating individual tree variables with airborne laser scanning in a boreal nature reserve

2004 ◽  
Vol 34 (9) ◽  
pp. 1791-1801 ◽  
Author(s):  
M Maltamo ◽  
K Mustonen ◽  
J Hyyppä ◽  
J Pitkänen ◽  
X Yu
Keyword(s):  
Norway Spruce ◽  
Scots Pine ◽  
Laser Scanning ◽  
Stand Structure ◽  
Tree Height ◽  
Heterogeneous Structure ◽  
Mixed Stands ◽  
Individual Tree ◽  
Tree Layer ◽  
Pine Trees

This study examines the ability of high-density laser scanning to produce single-tree estimates in mixed stands of heterogeneous structure. Individual trees were detected from a constructed digital canopy height model by locating local maxima of the height values. The reference material comprised accurately measured field data for 10 mapped sample plots containing Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and different birches. To verify the accuracy of height measurements of single trees in more detail, the height of 29 Scots pine trees and their annual shoots of the last few years was carefully measured with a tacheometer and a glass fibre rod. The considered variables were the proportion of detected trees and tree height. As more than 80% of the dominant trees were detected, the results indicated that laser scanning can accurately describe the trees of the dominant tree layer. Because of the dense understorey tree layer in most of the sample plots, about 40% of all trees were detected. On the plot level, the stand structure affected the accuracy of the results considerably. The scanning-based tree height was most accurate for Norway spruce and least accurate for birches. The height of the separately measured 29 Scots pine trees was obtained with an accuracy of ±50 cm or better.

scholarly journals Estimation of crown and canopy cover from airborne lidar data

2010 ◽  
Vol 52 (1) ◽  
pp. 5-17 ◽  
Author(s):  
Mait Lang
Keyword(s):  
Norway Spruce ◽  
Scots Pine ◽  
Stand Structure ◽  
Canopy Cover ◽  
Airborne Lidar ◽  
Silver Birch ◽  
Lidar Data ◽  
Crown Cover ◽  
Pine Trees ◽  
Airborne Lidar Data

Metsa katvuse ja liituse hindamine lennukilt laserskanneriga Tests were carried out in mature Scots pine, Norway spruce and Silver birch stands at Järvselja, Estonia, to estimate canopy cover (K) and crown cover (L) from airborne lidar data. Independent estimates Kc and Lc for K and L were calculated from the Cajanus tube readings made on the ground at 1.3 m height. Lidar data based cover estimates depended on the inclusion of different order returns significantly. In all the stands first order return based estimate K1 was biased positively (3-10%) at the reference height of 1.3 m compared to ground measurements. All lidar based estimates decreased with increasing the reference height. Single return (Ky) and all return (Kk) based canopy cover estimates depended more on the sand structure compared to K1. The ratio of all return count to the first return count D behaved like crown cover estimate in all stands. However, in spruce stand D understimated Lc significantly. In the Scots pine stand K1(1.3) = 0.7431 was most similar canopy cover estimate relative to the ground estimate Kc = 0,7362 whereas Ky(1.3) and Kk(1.3) gave significant underestimates (>15%) of K. Caused by the simple structure of Scots pine stand - only one layer pine trees, the Cajanus tube based canopy cover (Kc), crown cover (Lc) and lidar data based canopy density D(1.3) values were rather similar. In the Norway spruce stand and in the Silver birch stand second layer and regeneration trees were present. In the Silver birch stand Kk(1.3) and Ky(1.3) estimated Kc rather well. In the Norway spruce stand Ky(1.3) and K1(1.3) were the best estimators of Kc whereas Kk(1.3) underestimated canopy cover. Lidar data were found to be usable for canopy cover and crown cover assessment but the selection of the estimator is not trivial and depends on the stand structure.

scholarly journals Adjudicating Perspectives on Forest Structure: How Do Airborne, Terrestrial, and Mobile Lidar-Derived Estimates Compare?

2021 ◽  
Vol 13 (12) ◽  
pp. 2297
Author(s):  
Jonathon J. Donager ◽  
Andrew J. Sánchez Meador ◽  
Ryan C. Blackburn
Keyword(s):  
Ponderosa Pine ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Basal Area ◽  
Tree Height ◽  
Absolute Error ◽  
Forest Monitoring ◽  
Individual Tree ◽  
Structural Configurations ◽  
Individual Trees

Applications of lidar in ecosystem conservation and management continue to expand as technology has rapidly evolved. An accounting of relative accuracy and errors among lidar platforms within a range of forest types and structural configurations was needed. Within a ponderosa pine forest in northern Arizona, we compare vegetation attributes at the tree-, plot-, and stand-scales derived from three lidar platforms: fixed-wing airborne (ALS), fixed-location terrestrial (TLS), and hand-held mobile laser scanning (MLS). We present a methodology to segment individual trees from TLS and MLS datasets, incorporating eigen-value and density metrics to locate trees, then assigning point returns to trees using a graph-theory shortest-path approach. Overall, we found MLS consistently provided more accurate structural metrics at the tree- (e.g., mean absolute error for DBH in cm was 4.8, 5.0, and 9.1 for MLS, TLS and ALS, respectively) and plot-scale (e.g., R2 for field observed and lidar-derived basal area, m2 ha−1, was 0.986, 0.974, and 0.851 for MLS, TLS, and ALS, respectively) as compared to ALS and TLS. While TLS data produced estimates similar to MLS, attributes derived from TLS often underpredicted structural values due to occlusion. Additionally, ALS data provided accurate estimates of tree height for larger trees, yet consistently missed and underpredicted small trees (≤35 cm). MLS produced accurate estimates of canopy cover and landscape metrics up to 50 m from plot center. TLS tended to underpredict both canopy cover and patch metrics with constant bias due to occlusion. Taking full advantage of minimal occlusion effects, MLS data consistently provided the best individual tree and plot-based metrics, with ALS providing the best estimates for volume, biomass, and canopy cover. Overall, we found MLS data logistically simple, quickly acquirable, and accurate for small area inventories, assessments, and monitoring activities. We suggest further work exploring the active use of MLS for forest monitoring and inventory.

scholarly journals Stand structure links up canopy processes and forest management

2009 ◽  
Vol 51 (1) ◽  
pp. 40-48
Author(s):  
Toomas Frey
Keyword(s):  
Forest Management ◽  
Stand Structure ◽  
Net Primary Production ◽  
Stand Density ◽  
Tree Height ◽  
Belowground Biomass ◽  
Unit Mass ◽  
Total Biomass ◽  
Individual Tree ◽  
Mean Values

Stand structure links up canopy processes and forest management Above- and belowground biomass and net primary production (Pn) of a maturing Norway spruce (Picea abies (L.) Karst.) forest (80 years old) established on brown soil in central Estonia were 227, 50 and 19.3 Mg ha correspondingly. Stand structure is determined mostly by mean height and stand density, used widely in forestry, but both are difficult to measure with high precision in respect of canopy processes in individual trees. However, trunk form quotient (q2) and proportion of living crown in relation to tree height are useful parameters allowing describe stand structure tree by tree. Based on 7 model trees, leaf unit mass assimilation activity and total biomass respiration per unit mass were determined graphically as mean values for the whole tree growth during 80 years of age. There are still several possible approaches not used carefully enough to integrate experimental work at instrumented towers with actual forestry measurement. Dependence of physiological characteristics on individual tree parameters is the missing link between canopy processes and forest management.

Modeling individual tree height to diameter ratio for Norway spruce and European beech in Czech Republic

Trees ◽  
2016 ◽  
Vol 30 (6) ◽  
pp. 1969-1982 ◽  
Author(s):  
Ram P. Sharma ◽  
Zdeněk Vacek ◽  
Stanislav Vacek
Keyword(s):  
Czech Republic ◽  
Norway Spruce ◽  
Tree Height ◽  
European Beech ◽  
Diameter Ratio ◽  
Individual Tree

scholarly journals Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 905 ◽  
Author(s):  
Guerra-Hernández ◽  
Cosenza ◽  
Cardil ◽  
Silva ◽  
Botequim ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Basal Area ◽  
Remote Sensing Data ◽  
Tree Height ◽  
Point Clouds ◽  
Volume Estimation ◽  
P Value ◽  
Test Statistic ◽  
Individual Tree ◽  
Significant Difference

Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from Unmanned Aerial Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantations.

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.

Individual Tree Measurement in Tropical Environment using Terrestrial Laser Scanning

2015 ◽  
Vol 73 (5) ◽  
Author(s):  
Muhammad Zulkarnain Abdul Rahman ◽  
Zulkepli Majid ◽  
Md Afif Abu Bakar ◽  
Abd Wahid Rasib ◽  
Wan Hazli Wan Kadir
Keyword(s):  
Laser Scanning ◽  
Mean Squared Error ◽  
Tree Height ◽  
Point Clouds ◽  
Tree Crown ◽  
Individual Tree ◽  
Branch Diameter ◽  
Reference Tree ◽  
Crown Volume ◽  
Tree Branch

Detailed forest inventory and mensuration of individual trees have drawn attention of research society mainly to support sustainable forest management. This study aims at estimating individual tree attributes from high density point cloud obtained by terrestrial laser scanner (TLS). The point clouds were obtained over single reference tree and group of trees in forest area. The reference tree is treated as benchmark since detailed measurements of branch diameter were made on selected branches with different sizes and locations. Diameter at breast height (DBH) was measured for trees in forest. Furthermore tree height, height to crown base, crown volume and tree branch volume were also estimated for each tree. Branch diameter is estimated directly from the point clouds based on semi-automatic approach of model fitting i.e. sphere, ellipse and cylinder. Tree branch volume is estimated based on the volume of the fitted models. Tree height and height to crown base are computed using histogram analysis of the point clouds elevation. Tree crown volume is estimated by fitting a convex-hull on the tree crown. The results show that the Root Mean Squared Error (RMSE) of the estimated tree branch diameter does not have a specific trend with branch sizes and number of points used for fitting process. This explains complicated distribution of point clouds over the branches. Overall cylinder model produces good results with most branch sizes and number of point clouds for fitting. The cylinder fitting approach shows significantly better estimation results compared to sphere and ellipse fitting models.   

scholarly journals The Effect of Crown Social Class on Bark Thickness and Sapwood Moisture Content in Norway Spruce

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1316
Author(s):  
Luka Krajnc ◽  
Jožica Gričar
Keyword(s):  
Social Class ◽  
Moisture Content ◽  
Norway Spruce ◽  
Research Study ◽  
Physiological State ◽  
Tree Height ◽  
Social Classes ◽  
Bark Thickness ◽  
Individual Tree ◽  
The Relationship

The research study examined the effect of tree properties (crown social class, diameter at breast height (DBH), and tree height) on bark thickness (BT) and sapwood moisture content (SMC) in Norway spruce (Picea abies (L.) H. Karst.). Both examined variables were shown to be positively affected by DBH and tree height. The relationship between DBH and SMC varied among crown social classes, while the relationship between DBH and BT was relatively constant across crown social classes. Crown social class had a relatively small effect on BT and SMC, having a more pronounced effect on SMC than on BT. The relationship between tree height and BT did not vary across crown social classes, while the relationship between SMC and tree height was found to change slightly across crown social classes. Measurements of BT and SMC in the field are affordable, fast, and easy to use. Both variables could potentially be used to improve predictions of bark beetle attacks, as they reflect the physiological state of an individual tree.

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