Factors influencing the accuracy of ground-based tree-height measurements for major European tree species

Stereńczak, Krzysztof; Mielcarek, Miłosz; Wertz, Bogdan; Bronisz, Karol; Zajączkowski, Grzegorz; Jagodziński, Andrzej M.; Ochał, Wojciech; Skorupski, Maciej

doi:10.1016/j.jenvman.2018.09.100

Cited by 40 publications

(38 citation statements)

References 23 publications

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“…Since our target species are large-size high-value broadleaved trees, some error in field measurement could be expected because of the tree height itself and tree crowns which limit the visibility to the tree tops. This was also highlighted by Hunter et al [15] and Stereńczak et al [17]. These studies reported that small measurement errors were found in conifer species and larger trees were subjected more to height measurement errors in the field.…”

Section: Discussionmentioning

confidence: 67%

“…The individual tree DBH can be measured accurately by traditional field measurements, but tree height is relatively difficult to measure accurately [13]. Further, the results of tree height measurements are greatly influenced by many factors including biophysical and topographic factors, instrument errors, and human errors [14][15][16][17]. Although errors are likely to be presented in the field measurements of tree height than other parameters, such as DBH [15,18], field-measured tree heights have been widely understood to be the most reliable source of tree height information [19].…”

Section: Introductionmentioning

confidence: 99%

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Comparing Individual Tree Height Information Derived from Field Surveys, LiDAR and UAV-DAP for High-Value Timber Species in Northern Japan

Moe

Owari

Furuya

et al. 2020

Forests

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High-value timber species such as monarch birch (Betula maximowicziana Regel), castor aralia (Kalopanax septemlobus (Thunb.) Koidz), and Japanese oak (Quercus crispula Blume) play important ecological and economic roles in forest management in the cool temperate mixed forests in northern Japan. The accurate measurement of their tree height is necessary for both practical management and scientific reasons such as estimation of biomass and site index. In this study, we investigated the similarity of individual tree heights derived from conventional field survey, digital aerial photographs derived from unmanned aerial vehicle (UAV-DAP) data and light detection and ranging (LiDAR) data. We aimed to assess the applicability of UAV-DAP in obtaining individual tree height information for large-sized high-value broadleaf species. The spatial position, tree height, and diameter at breast height (DBH) were measured in the field for 178 trees of high-value broadleaf species. In addition, we manually derived individual tree height information from UAV-DAP and LiDAR data with the aid of spatial position data and high resolution orthophotographs. Tree heights from three different sources were cross-compared statistically through paired sample t-test, correlation coefficient, and height-diameter model. We found that UAV-DAP derived tree heights were highly correlated with LiDAR tree height and field measured tree height. The performance of individual tree height measurement using traditional field survey is likely to be influenced by individual species. Overall mean height difference between LiDAR and UAV-DAP derived tree height indicates that UAV-DAP could underestimate individual tree height for target high-value timber species. The height-diameter models revealed that tree height derived from LiDAR and UAV-DAP could be better explained by DBH with lower prediction errors than field measured tree height. We confirmed the applicability of UAV-DAP data for obtaining the individual tree height of large-size high-value broadleaf species with comparable accuracy to LiDAR and field survey. The result of this study will be useful for the species-specific forest management of economically high-value timber species.

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Section: Discussionmentioning

confidence: 67%

Section: Introductionmentioning

confidence: 99%

Comparing Individual Tree Height Information Derived from Field Surveys, LiDAR and UAV-DAP for High-Value Timber Species in Northern Japan

Moe

Owari

Furuya

et al. 2020

Forests

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“…Thinned stands have for several decades lower basal area than unthinned stands. Evaluating the effects of thinning on forest carbon stocks need measurements of standing and lying deadwood and coarse woody debris (Woldendorp et al 2004, Harmon et al 2020, reliable biomass functions and accurate tree height measurements (Neumann et al 2016, Stereńczak et al 2019. This case study provides some evidence that oak-hornbeam forests may have a broad "plateau-like" relationship between increment and stocking (Assmann 1970), when stands approach their maximum basal area.…”

Section: Harvesting Versus Natural Mortalitymentioning

confidence: 97%

Thinning Response and Potential Basal Area in a Mixed Sub-humid Low-elevation Oak-Hornbeam Forest

Neumann¹,

Hasenauer²

2021

Preprint

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Competition for resources (light, water, nutrients, etc.) limits the size and abundance of alive trees a site can support. This carrying capacity determines the potential carbon sequestration in alive trees as well as the maximum growing stock. Lower stocking through thinning can change growth and mortality. We were interested in the relations between stand structure, increment and mortality using a long-unmanaged oak-hornbeam forest near Vienna, Austria, as case study. We expected lower increment for heavy thinned compared to unmanaged stands. We tested the thinning response using three permanent growth plots, whereas two were thinned (50% and 70% basal area removed) and one remained unmanaged. We calculated stand structure (basal area, stem density, diameter distribution) and increment and mortality of single trees. The heavy thinned stand had over ten years similar increment as the moderate thinned and unthinned stands. Basal area of the unthinned stand remained constant and stem density decreased due to competition-related mortality. The studied oak-hornbeam stands responded well even to late and heavy thinning suggesting a broad “plateau” of stocking and increment for these forest types. Lower stem density for thinned stands lead to much larger tree increment of single trees, compared to the unthinned reference. The findings of this study need verification for other soil and climatic conditions.

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“…According to the extensive research of Stereńczak et al [49], the relative errors for tree height measurements using a Vertex instrument are 2.52% and −1.25% for Q. robur and A. glutinosa, respectively. Other tree species (C. betulus, F. angustifolia) found in the study area of the present research were not in the scope of the research by Stereńczak et al [49], but it can be assumed that expected errors do not significantly deviate from those reported for Q. robur and A. glutinosa. For trees without height measurements, tree heights were estimated using the developed local species-specific dbh-height models fitted with Michailloff's function [50].…”

Section: Field (Ground-truth) Datamentioning

confidence: 99%

Impact of UAS Image Orientation on Accuracy of Forest Inventory Attributes

et al. 2020

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The quality and accuracy of Unmanned Aerial System (UAS) products greatly depend on the methods used to define image orientations before they are used to create 3D point clouds. While most studies were conducted in non- or partially-forested areas, a limited number of studies have evaluated the spatial accuracy of UAS products derived by using different image block orientation methods in forested areas. In this study, three image orientation methods were used and compared: (a) the Indirect Sensor Orientation (InSO) method with five irregularly distributed Ground Control Points (GCPs); (b) the Global Navigation Satellite System supported Sensor Orientation (GNSS-SO) method using non-Post-Processed Kinematic (PPK) single-frequency carrier-phase GNSS data (GNSS-SO1); and (c) using PPK dual-frequency carrier-phase GNSS data (GNSS-SO2). The effect of the three methods on the accuracy of plot-level estimates of Lorey’s mean height (HL) was tested over the mixed, even-aged pedunculate oak forests of Pokupsko basin located in Central Croatia, and validated using field validation across independent sample plots (HV), and leave-one-out cross-validation (LOOCV). The GNSS-SO2 method produced the HL estimates of the highest accuracy (RMSE%: HV = 5.18%, LOOCV = 4.06%), followed by the GNSS-SO1 method (RMSE%: HV = 5.34%, LOOCV = 4.37%), while the lowest accuracy was achieved by the InSO method (RMSE%: HV = 5.55%, LOOCV = 4.84%). The negligible differences in the performances of the regression models suggested that the selected image orientation methods had no considerable effect on the estimation of HL. The GCPs, as well as the high image overlaps, contributed considerably to the block stability and accuracy of image orientation in the InSO method. Additional slight improvements were achieved by replacing single-frequency GNSS measurements with dual-frequency GNSS measurements and by incorporating PPK into the GNSS-SO2 method.

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Factors influencing the accuracy of ground-based tree-height measurements for major European tree species

Cited by 40 publications

References 23 publications

Comparing Individual Tree Height Information Derived from Field Surveys, LiDAR and UAV-DAP for High-Value Timber Species in Northern Japan

Comparing Individual Tree Height Information Derived from Field Surveys, LiDAR and UAV-DAP for High-Value Timber Species in Northern Japan

Thinning Response and Potential Basal Area in a Mixed Sub-humid Low-elevation Oak-Hornbeam Forest

Impact of UAS Image Orientation on Accuracy of Forest Inventory Attributes

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