scholarly journals Automatic Delineation and Height Measurement of Regenerating Conifer Crowns under Leaf-Off Conditions Using UAV Imagery

2020 ◽  
Vol 12 (24) ◽  
pp. 4104
Author(s):  
Andrew J. Chadwick ◽  
Tristan R. H. Goodbody ◽  
Nicholas C. Coops ◽  
Anne Hervieux ◽  
Christopher W. Bater ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Picea Glauca ◽  
Pinus Contorta ◽  
Tree Height ◽  
Point Clouds ◽  
Strongly Correlated ◽  
Tree Crown ◽  
Height Measurement ◽  
Individual Tree ◽  
Fine Spatial Resolution

The increasing use of unmanned aerial vehicles (UAV) and high spatial resolution imagery from associated sensors necessitates the continued advancement of efficient means of image processing to ensure these tools are utilized effectively. This is exemplified in the field of forest management, where the extraction of individual tree crown information stands to benefit operational budgets. We explored training a region-based convolutional neural network (Mask R-CNN) to automatically delineate individual tree crown (ITC) polygons in regenerating forests (14 years after harvest) using true colour red-green-blue (RGB) imagery with an average ground sampling distance (GSD) of 3 cm. We predicted ITC polygons to extract height information using canopy height models generated from digital aerial photogrammetric (DAP) point clouds. Our approach yielded an average precision of 0.98, an average recall of 0.85, and an average F1 score of 0.91 for the delineation of ITC. Remote height measurements were strongly correlated with field height measurements (r2 = 0.93, RMSE = 0.34 m). The mean difference between DAP-derived and field-collected height measurements was −0.37 m and −0.24 m for white spruce (Picea glauca) and lodgepole pine (Pinus contorta), respectively. Our results show that accurate ITC delineation in young, regenerating stands is possible with fine-spatial resolution RGB imagery and that predicted ITC can be used in combination with DAP to estimate tree height.

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 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.

scholarly journals A Comparison of Forest Tree Crown Delineation from Unmanned Aerial Imagery Using Canopy Height Models vs. Spectral Lightness

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 605 ◽  
Author(s):  
Jianyu Gu ◽  
Heather Grybas ◽  
Russell G. Congalton
Keyword(s):  
Spectral Data ◽  
Spatial Resolution ◽  
Forest Type ◽  
Canopy Height ◽  
Aerial Imagery ◽  
Tree Level ◽  
Tree Crown ◽  
Remotely Sensed Data ◽  
Individual Tree ◽  
Tree Crowns

Improvements in computer vision combined with current structure-from-motion photogrammetric methods (SfM) have provided users with the ability to generate very high resolution structural (3D) and spectral data of the forest from imagery collected by unmanned aerial systems (UAS). The products derived by this process are capable of assessing and measuring forest structure at the individual tree level for a significantly lower cost compared to traditional sources such as LiDAR, satellite, or aerial imagery. Locating and delineating individual tree crowns is a common use of remotely sensed data and can be accomplished using either UAS-based structural or spectral data. However, no study has extensively compared these products for this purpose, nor have they been compared under varying spatial resolution, tree crown sizes, or general forest stand type. This research compared the accuracy of individual tree crown segmentation using two UAS-based products, canopy height models (CHM) and spectral lightness information obtained from natural color orthomosaics, using maker-controlled watershed segmentation. The results show that single tree crowns segmented using the spectral lightness were more accurate compared to a CHM approach. The optimal spatial resolution for using lightness information and CHM were found to be 30 and 75 cm, respectively. In addition, the size of tree crowns being segmented also had an impact on the optimal resolution. The density of the forest type, whether predominately deciduous or coniferous, was not found to have an impact on the accuracy of the segmentation.

scholarly journals Ecoregion-Based Individual Tree Height-Diameter Models for Lodgepole Pine in Alberta

1999 ◽  
Vol 14 (4) ◽  
pp. 186-193 ◽  
Author(s):  
Shongming Huang
Keyword(s):  
Pinus Contorta ◽  
Lodgepole Pine ◽  
Tree Height ◽  
Error Variance ◽  
Weighting Factor ◽  
Composite Model ◽  
Sum Of Squares ◽  
Individual Tree ◽  
Richards Function ◽  
Tree Data

Abstract Using the felled tree data, ecoregion-based height-diameter models were developed for lodgepole pine (Pinus contorta var. latifolia) in Alberta. A large number of height-diameter functions were evaluated, and the Chapman-Richards function was found to produce some of the most satisfactory fits. Residual analysis was conducted to identify the error structure of the models. A weighting factor of wi = 1/Di was found appropriate for achieving the equal error variance assumption. Differences of the height-diameter models among different ecoregions were examined and tested using the nonlinear extra sum of squares method. Most height-diameter relationships were found to be different among different ecoregions. Ecoregions of similar height-diameter relationships were combined to provide a composite model to facilitate the practical use of such relationships. West. J. Appl. For. 14(4):186-193.

TADAM: A dynamic whole-stand approximation for the TASS growth model

2005 ◽  
Vol 81 (4) ◽  
pp. 575-581 ◽  
Author(s):  
Oscar Garcia
Keyword(s):  
Growth Model ◽  
Picea Glauca ◽  
Pinus Contorta ◽  
Initial Conditions ◽  
Growth And Yield ◽  
Planting Density ◽  
Individual Tree ◽  
Model Driven ◽  
Planning Models ◽  
Dependent Growth

Growth and yield predictions for managed even-aged stands in British Columbia are based on TASS, an individual-tree distance-dependent growth model driven by an unusually detailed description of crown development. Because of its complexity, most applications utilize previously generated stand-level yield tables rather than running TASS directly. I have developed a differential equation approximation to the stand-level dynamics predicted by TASS that mimics the aggregate behaviour with sufficient accuracy for many practical purposes. Versions of this model, called TADAM, exist for planted coastal Douglas-fir, lodgepole pine, and white spruce. TADAM can efficiently project stand development starting from any initial conditions, and subject to any combination of thinnings. Its relative simplicity makes it suitable for embedding into landscape-level planning models and other decision support systems. It has been implemented as a C function library, as an interactive simulator running on a PDA, and as an Excel spreadsheet add-in. An example of thinning and planting density optimization is briefly described. Key words: growth and yield, stand dynamics, thinning, optimization, Pinus contorta, Picea glauca

scholarly journals Individual Tree Crown Segmentation of a Larch Plantation Using Airborne Laser Scanning Data Based on Region Growing and Canopy Morphology Features

2020 ◽  
Vol 12 (7) ◽  
pp. 1078 ◽  
Author(s):  
Zhenyu Ma ◽  
Yong Pang ◽  
Di Wang ◽  
Xiaojun Liang ◽  
Bowei Chen ◽  
...  
Keyword(s):  
Region Growing ◽  
Point Clouds ◽  
Tree Canopy ◽  
Segmentation Method ◽  
Tree Crown ◽  
Two Stage ◽  
Individual Tree ◽  
Tree Structures ◽  
Larch Plantation

The detection of individual trees in a larch plantation could improve the management efficiency and production prediction. This study introduced a two-stage individual tree crown (ITC) segmentation method for airborne light detection and ranging (LiDAR) point clouds, focusing on larch plantation forests with different stem densities. The two-stage segmentation method consists of the region growing and morphology segmentation, which combines advantages of the region growing characteristics and the detailed morphology structures of tree crowns. The framework comprises five steps: (1) determination of the initial dominant segments using a region growing algorithm, (2) identification of segments to be redefined based on the 2D hull convex area of each segment, (3) establishment and selection of profiles based on the tree structures, (4) determination of the number of trees using the correlation coefficient of residuals between Gaussian fitting and the tree canopy shape described in each profile, and (5) k-means segmentation to obtain the point cloud of a single tree. The accuracy was evaluated in terms of correct matching, recall, precision, and F-score in eight plots with different stem densities. Results showed that the proposed method significantly increased ITC detections compared with that of using only the region growing algorithm, where the correct matching rate increased from 73.5% to 86.1%, and the recall value increased from 0.78 to 0.89.

Growth and crown morphological responses of boreal conifer seedlings and saplings with contrasting shade tolerance to a gradient of light and height

2002 ◽  
Vol 32 (3) ◽  
pp. 458-468 ◽  
Author(s):  
Yves Claveau ◽  
Christian Messier ◽  
Philip G Comeau ◽  
K Dave Coates
Keyword(s):  
Picea Glauca ◽  
Pinus Banksiana ◽  
Pinus Contorta ◽  
Morphological Changes ◽  
Abies Balsamea ◽  
Tree Height ◽  
Light Level ◽  
Abies Lasiocarpa ◽  
Morphological Responses ◽  
Picea Species

The effects of gradients in light levels and tree height on growth and crown attributes of six conifer species were studied in eastern and western Canada. Three conifers were studied in British Columbia (Abies lasiocarpa (Hook.) Nutt., Picea glauca (Moench) Voss × Picea engelmannii Parry ex Engelm., and Pinus contorta Dougl. ex Loud. var. latifolia Engelm.), and three in Quebec (Abies balsamea (L.) Mill., Picea glauca, and Pinus banksiana Lamb.). For several growth and morphological parameters, conifers reacted strongly to both an increase in light and tree height. Significant or nearly significant interactions between light classes and height were found for height and diameter growth of most species as well as for many crown attributes for both Abies and Picea. These interactions usually indicated that growth or morphological changes occurred with increasing height from a certain light level. Within a single genus, both eastern and western tree species showed the same overall acclimation to light and height. As generally reported, Pinus species showed less variation in growth and morphological responses to light than Abies and Picea species.

scholarly journals Tree height and tropical forest biomass estimation

2013 ◽  
Vol 10 (6) ◽  
pp. 10491-10529 ◽  
Author(s):  
M. O. Hunter ◽  
M. Keller ◽  
D. Vitoria ◽  
D. C. Morton
Keyword(s):  
Tropical Forest ◽  
Tropical Forests ◽  
Reference Values ◽  
Tree Height ◽  
Carbon Stocks ◽  
Estimation Accuracy ◽  
Biomass Estimation ◽  
Height Measurement ◽  
Individual Tree ◽  
Allometric Relations

Abstract. Tropical forests account for approximately half of above-ground carbon stored in global vegetation. However, uncertainties in tropical forest carbon stocks remain high because it is costly and laborious to quantify standing carbon stocks. Carbon stocks of tropical forests are determined using allometric relations between tree stem diameter and height and biomass. Previous work has shown that the inclusion of height in biomass allometries, compared to the sole use of diameter, significantly improves biomass estimation accuracy. Here, we evaluate the effect of height measurement error on biomass estimation and we evaluate the accuracy of recently published diameter : height allometries at four sites within the Brazilian Amazon. As no destructive sample of biomass was available at these sites, reference biomass values were based on allometries. We found that the precision of individual tree height measurements ranged from 3 to 20% of total height. This imprecision resulted in a 5–6% uncertainty in biomass when scaled to 1 ha transects. Individual height measurement may be replaced with existing regional and global height allometries. However, we recommend caution when applying these relations. At Tapajós National Forest in the Brazilian state of Pará, using the pantropical and regional allometric relations for height resulted in site biomass 26% to 31% less than reference values. At the other three study sites, the pan-tropical equation resulted in errors of less that 2%, and the regional allometry produced errors of less than 12%. As an alternative to measuring all tree heights or to using regional and pantropical relations, we recommend measuring height for a well distributed sample of about 100 trees per site. Following this methodology, 95% confidence intervals of transect biomass were constrained to within 4.5% on average when compared to reference values.

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