Bragg, D.C. Technical note: An improved tree height measurement technique tested on mature southern pines. South. J. Appl. For. 32(1):38–43

Abstract Virtually all techniques for tree height determination follow one of two principles: similar triangles or the tangent method. Most people apply the latter approach, which uses the tangents of the angles to the top and bottom and a true horizontal distance to the subject tree. However, few adjust this method for ground slope, tree lean, crown shape, and crown configuration, making errors commonplace. Given documented discrepancies exceeding 30% with current methods, a reevaluation of height measurement is in order. The sine method is an alternative that measures a real point in the crown. Hence, it is not subject to the same assumptions as the similar triangle and tangent approaches. In addition, the sine method is insensitive to distance from tree or observer position and can not overestimate tree height. The advantages of the sine approach are shown with mature southern pines from Arkansas.

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The Sine Method: An Alternative Height Measurement Technique

10.2737/srs-rn-22 ◽

2011 ◽

Author(s):

Don C. Bragg ◽

Lee E. Frelich ◽

Robert T. Leverett ◽

Will Blozan ◽

Dale J. Luthringer

Keyword(s):

Measurement Technique ◽

Height Measurement

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Development and Testing of a New Ground Measurement Tool to Assist in Forest GIS Surveys

Forests ◽

10.3390/f10080643 ◽

2019 ◽

Vol 10 (8) ◽

pp. 643 ◽

Cited By ~ 2

Author(s):

Guangpeng Fan ◽

Feixiang Chen ◽

Yan Li ◽

Binbin Liu ◽

Xu Fan

Keyword(s):

Root Mean Square Error ◽

Mobile Phone ◽

Mean Square Error ◽

Tree Species ◽

Tree Height ◽

Measurement Tool ◽

Mean Square ◽

Height Measurement ◽

Test Dataset ◽

Ground Measurement

In present forest surveys, some problems occur because of the cost and time required when using external tools to acquire tree measurement. Therefore, it is of great importance to develop a new cost-saving and time-saving ground measurement method implemented in a forest geographic information system (GIS) survey. To obtain a better solution, this paper presents the design and implementation of a new ground measurement tool in which mobile devices play a very important role. Based on terrestrial photogrammetry, location-based services (LBS), and computer vision, the tool assists forest GIS surveys in obtaining important forest structure factors such as tree position, diameter at breast height (DBH), tree height, and tree species. This paper selected two plots to verify the accuracy of the ground measurement tool. Experiments show that the root mean square error (RMSE) of the position coordinates of the trees was 0.222 m and 0.229 m, respectively, and the relative root mean square error (rRMSE) was close to 0. The rRMSE of the DBH measurement was 10.17% and 13.38%, and the relative Bias (rBias) of the DBH measurement was −0.88% and −2.41%. The rRMSE of tree height measurement was 6.74% and 6.69%, and the rBias of tree height measurement was −1.69% and −1.27%, which conforms to the forest investigation requirements. In addition, workers usually make visual observations of trees and then combine their personal knowledge or experience to identify tree species, which may lead to the situations when they cannot distinguish tree species due to insufficient knowledge or experience. Based on MobileNets, a lightweight convolutional neural network designed for mobile phone, a model was trained to assist workers in identifying tree species. The dataset was collected from some forest parks in Beijing. The accuracy of the tree species recognition model was 94.02% on a test dataset and 93.21% on a test dataset in the mobile phone. This provides an effective reference for workers to identify tree species and can assist in artificial identification of tree species. Experiments show that this solution using the ground measurement tool saves time and cost for forest resources GIS surveys.

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Tree height measurement based on image processing embedded in smart mobile phone

2011 International Conference on Multimedia Technology ◽

10.1109/icmt.2011.6002029 ◽

2011 ◽

Cited By ~ 2

Author(s):

Dianyuan Han ◽

Chengduan Wang

Keyword(s):

Image Processing ◽

Mobile Phone ◽

Tree Height ◽

Height Measurement ◽

Smart Mobile Phone ◽

Smart Mobile

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Mesure de la hauteur des arbres avec la perche Sokkisha : Test de précision

The Forestry Chronicle ◽

10.5558/tfc71616-5 ◽

1995 ◽

Vol 71 (5) ◽

pp. 616-620 ◽

Cited By ~ 1

Author(s):

Richard Zarnovican ◽

Jean De Grâce

Keyword(s):

Prediction Interval ◽

Tree Height ◽

Balsam Fir ◽

Negative Bias ◽

Tolerance Interval ◽

Probability Level ◽

Height Measurement ◽

Quadratic Error ◽

North Shore ◽

The Mean

The accuracy of measuring tree height using a Sokkisha pole compared with that obtained using a tape measure was tested. This test was conducted in young thinned balsam fir stands in the Upper North Shore region of the province of Quebec. The results show a slightly negative bias, -0.06 m or -1.03%, significantly different from zero at the 95% probability level. A study of the precision shows that the mean quadratic error does not exceed ±0.11 m or ±1.77%. Using the prediction interval, we can be 95% confident that in a single future measurement, the error will be around ±0.21 m or ±3.49%. According to tolerance interval, we can be 95% confident that at least 95% of the population of errors produced by using the pole will fall between ±0.23 m or ±3.9%. Key words: Test of accuracy, measuring poles, tree height measurement, mensuration, balsam fir.

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Comparison of Optical Dendrometers for Prediction of Standing Tree Volume

Southern Journal of Applied Forestry ◽

10.1093/sjaf/23.2.100 ◽

1999 ◽

Vol 23 (2) ◽

pp. 100-107 ◽

Cited By ~ 7

Author(s):

Robert C. Parker ◽

Thomas G. Matney

Keyword(s):

Measurement Data ◽

Tree Height ◽

Standing Tree ◽

Height Measurement ◽

Total Height ◽

Profile Equation ◽

Standing Trees ◽

Pine Trees ◽

Tree Data ◽

Mean Differences

Abstract Enhanced sets of compatible stem profile equations were used with data collected from felled and standing pine trees to calculate tree volumes to various top merchantability limits. Standing trees were measured with the Criterion 400 Laser, Tele-Relaskop, and Wheeler Pentaprism. These measurements were used to compare accuracies of the optical dendrometers for the measurement of tree dbh and height and the prediction of tree volume from stem profile equations. The Criterion 400 Laser was more accurate for dbh and total height measurement than was the Tele-Relaskop or the Wheeler Pentaprism, but the accuracy differences are not significantly different in a practical sense. Mean percent differences in dbh measurement translated, in absolute units, to -0.05, +0.20, and -0.34 in. of the mean tree dbh for the Criterion 400, Tele-Relaskop, and Wheeler Pentaprism instruments, respectively. Mean percent differences in total height measurement translated, in absolute units, to 0.5, 1.6, and 1.7 ft, respectively, of the average tree height and were not practically different. The combined measurement data for dbh and dob16, indicated the Tele-Relaskop would produce more reliable volume results than the other instruments if the dendrometer measurements were used with form class volumes. Profile equations developed with felled-tree data produced the most consistent estimates of merchantable height and cubic foot volume to specified merchantable top limits. In general, the Criterion 400 produced the smallest mean differences in standing tree measurements and profile equation predictions of merchantable height and cubic foot volume. However, the Tele-Relaskop produced the most consistent tree measurement and profile prediction trends. The Wheeler Pentaprism was the least accurate of the three dendrometers. South. J. Appl. For. 23(2):100-107.

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Tree height and tropical forest biomass estimation

Biogeosciences Discussions ◽

10.5194/bgd-10-10491-2013 ◽

2013 ◽

Vol 10 (6) ◽

pp. 10491-10529 ◽

Cited By ~ 12

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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UAV-Based LiDAR Scanning for Individual Tree Detection and Height Measurement in Young Forest Permanent Trials

Remote Sensing ◽

10.3390/rs14010170 ◽

2021 ◽

Vol 14 (1) ◽

pp. 170

Author(s):

Francisco Rodríguez-Puerta ◽

Esteban Gómez-García ◽

Saray Martín-García ◽

Fernando Pérez-Rodríguez ◽

Eva Prada

Keyword(s):

Pinus Radiata ◽

Repeated Measures ◽

Pinus Pinaster ◽

Tree Height ◽

Cost Effective ◽

Permanent Plots ◽

Height Measurement ◽

Measured Variable ◽

Individual Tree ◽

Tree Detection

The installation of research or permanent plots is a very common task in growth and forest yield research. At young ages, tree height is the most commonly measured variable, so the location of individuals is necessary when repeated measures are taken and if spatial analysis is required. Identifying the coordinates of individual trees and re-measuring the height of all trees is difficult and particularly costly (in time and money). The data used comes from three Pinus pinaster Ait. and three Pinus radiata D. Don plantations of 0.8 ha, with an age ranging between 2 and 5 years and mean heights between 1 and 5 m. Five individual tree detection (ITD) methods are evaluated, based on the Canopy Height Model (CHM), where the height of each tree is identified, and its crown is segmented. Three CHM resolutions are used for each method. All algorithms used for individual tree detection (ITD) tend to underestimate the number of trees. The best results are obtained with the R package, ForestTools and rLiDAR. The best CHM resolution for identifying trees was always 10 cm. We did not detect any differences in the relative error (RE) between Pinus pinaster and Pinus radiata. We found a pattern in the ITD depending on the height of the trees to be detected: the accuracy is lower when detecting trees less than 1 m high than when detecting larger trees (RE close to 12% versus 1% for taller trees). Regarding the estimation of tree height, we can conclude that the use of the CHM to estimate height tends to underestimate its value, while the use of the point cloud presents practically unbiased results. The stakeout of forestry research plots and the re-measurement of individual tree heights is an operation that can be performed by UAV-based LiDAR scanning sensors. The individual geolocation of each tree and the measurement of heights versus pole and/or hypsometer measurement is highly accurate and cost-effective, especially when tree height reaches 1–1.5 m.

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Impact of training on different observers in forest inventory

Banko Janakari ◽

10.3126/banko.v31i1.37338 ◽

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.

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

Remote Sensing ◽

10.3390/rs12244104 ◽

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.

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