Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest

Moskal, L. Monika; Zheng, Guang

doi:10.3390/rs4010001

Cited by 186 publications

(126 citation statements)

References 51 publications

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“…Several studies have shown that TLS is a promising technology because it provides objective measures of tree characteristics including height, plot level volumes, diameter at breast height (DBH), canopy cover, and stem density [12]. However, drawbacks include reduced spatial resolution of the tree surface point cloud with increasing distance to the sensor, and laser pulses are unable to penetrate through occluding vegetation; thus, TLS point density may be insufficient and provide underestimates compared to field-measured estimates [13,14]. However, the modern laser scanners with a sufficiently wide beam, either terrestrials or installed on Unmanned Aerial Vehicles (UAVs) (for example Riegl Vux-1), appear to be very promising.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

2016

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Airborne laser scanning (ALS) allows for extensive coverage, but the accuracy of tree detection and form can be limited. Although terrestrial laser scanning (TLS) can improve on ALS accuracy, it is rather expensive and area coverage is limited. Multi-view stereopsis (MVS) techniques combining computer vision and photogrammetry may offer some of the coverage benefits of ALS and the improved accuracy of TLS; MVS combines computer vision research and automatic analysis of digital images from common commercial digital cameras with various algorithms to reconstruct three-dimensional (3D) objects with realistic shape and appearance. Despite the relative accuracy (relative geometrical distortion) of the reconstructions available in the processing software, the absolute accuracy is uncertain and difficult to evaluate. We evaluated the data collected by a common digital camera through the processing software (Agisoft PhotoScan ©) for photogrammetry by comparing those by direct measurement of the 3D magnetic motion tracker. Our analyses indicated that the error is mostly concentrated in the portions of the tree where visibility is lower, i.e., the bottom and upper parts of the stem. For each reference point from the digitizer we determined how many cameras could view this point. With a greater number of cameras we found increasing accuracy of the measured object space point positions (as expected), with a significant positive change in the trend beyond five cameras; when more than five cameras could view this point, the accuracy began to increase more abruptly, but eight cameras or more provided no increases in accuracy. This method allows for the retrieval of larger datasets from the measurements, which could improve the accuracy of estimates of 3D structure of trees at potentially reduced costs.

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Section: Introductionmentioning

confidence: 99%

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

2016

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“…Of these, LiDAR (Light Detection And Ranging) and especially terrestrial laser scanning (TLS) have been applied to analyze standard tree dendrometrics such as stem position, tree density, DBH, TH, basal area, and wood volume [10][11][12][13]. For example, Hopkinson et al [10] estimated DBH and TH based on TLS data, but still relied on standard allometric equations for wood volume estimates.…”

Section: Introductionmentioning

confidence: 99%

Does Tree Architectural Complexity Influence the Accuracy of Wood Volume Estimates of Single Young Trees by Terrestrial Laser Scanning?

Hess

Bienert

Oheimb

2015

Forests

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Accurate estimates of the wood volume or biomass of individual trees have gained considerable importance in recent years. The accuracy of wood volume estimation by terrestrial laser scanning (TLS) point cloud data may differ between individual trees due to species-specific differences in tree architecture. We selected three common and ecologically important central European deciduous tree species, which differ considerably in tree architectural complexity in early ontogenetic stages: Acer pseudoplatanus (simple), Sorbus aucuparia (intermediate) and Betula pendula (complex). We scanned six single young trees for each species (18 trees in total) under optimal scan conditions (single tree stand, leafless state, four scanning positions, high resolution). TLS-based volume estimates were derived for the total tree as well as for the two compartments; trunk and branches, using a voxel-based bounding box method. These estimates were compared with highly accurate xyolmetric (water displacement) volume measurements. Coefficients of determination between xylometric measurements and bounding box estimates were very high for total trees (R 2 adj = 0.99), trunks (R 2 adj = 0.99), and high for branches (R 2 adj = 0.78).The accuracy of estimations for total tree and trunk volume was highly similar among the three tree species. In contrast, significant differences were found for branch volume OPEN ACCESSForests 2015, 6 3848 estimates: the accuracy was very high for Sorbus aucuparia, intermediate for Betula pendula, and low for Acer pseudoplatanus. A stepwise multiple regression showed that the accuracy of branch volume estimates was negatively related to the number of the first-order branches within diameter sizes of D ≤ 5 mm and crown surface area (R 2 adj = 0.61). We conclude that the accuracy in total tree and trunk volume estimates was not affected by the studied types of tree architectural complexity. The impact of the structural variability of branches and occlusion by branches was, thus, not as high as expected. In contrast, the accuracy of branch volume estimates was strongly influenced by tree architectural complexity, though not in a simple way. Because underestimations originated from different sources, the accuracy of branch volume estimates cannot be directly derived from the degree of architectural complexity. These results imply that the voxel-based bounding box method provides highly accurate total tree and trunk volume estimates, whereas further research is needed to improve branch volume estimation for young trees of different architectural types.

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“…Calipers, a device used to measure the distance between two opposite sides, can easily measure the diameter or cross-section of a tree trunk [10]. With advancements in equipment, modern methods of collecting forest inventory data include laser rangefinders [11], terrestrial light detection and ranging (LiDAR; [12,13]), and even smartphone applications [14], which improve efficiency and data quality. Although different methods can be used to collect forest data depending on various technologies and their suitability, the methods must always be used on the ground.…”

Section: Introductionmentioning

confidence: 99%

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

et al. 2017

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Methods for accurately measuring biophysical parameters are a key component for quantitative evaluation regarding to various forest applications. Conventional in situ measurements of these parameters take time and expense, encountering difficultness at locations with heterogeneous microtopography. To obtain precise biophysical data in such situations, we deployed an unmanned aerial system (UAS) multirotor drone in a cypress forest in a mountainous area of Japan. The structure from motion (SfM) method was used to construct a three-dimensional (3D) model of the forest (tree) structures from aerial photos. Tree height was estimated from the 3D model and compared to in situ ground data. We also analyzed the relationships between a biophysical parameter, diameter at breast height (DBH), of individual trees with canopy width and area measured from orthorectified images. Despite the constraints of ground exposure in a highly dense forest area, tree height was estimated at an accuracy of root mean square error = 1.712 m for observed tree heights ranging from 16 to 24 m. DBH was highly correlated with canopy width (R 2 = 0.7786) and canopy area (R 2 = 0.7923), where DBH ranged from 11 to 58 cm. The results of estimating forest parameters indicate that drone-based remote-sensing methods can be utilized to accurately analyze the spatial extent of forest structures.

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Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest

Cited by 186 publications

References 51 publications

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

Does Tree Architectural Complexity Influence the Accuracy of Wood Volume Estimates of Single Young Trees by Terrestrial Laser Scanning?

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

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