Impact of training on different observers in forest inventory

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.

scholarly journals An Improved Tree Height Measurement Technique Tested on Mature Southern Pines

2008 ◽  
Vol 32 (1) ◽  
pp. 38-43 ◽  
Author(s):  
Don C. Bragg
Keyword(s):  
Tree Height ◽  
Real Point ◽  
Horizontal Distance ◽  
Height Measurement ◽  
Similar Triangle ◽  
Height Determination ◽  
Southern Pines ◽  
Crown Shape ◽  
Tangent Method ◽  
Similar Triangles

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.

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

1995 ◽  
Vol 71 (5) ◽  
pp. 616-620 ◽  
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.

scholarly journals ESTIMATING PRECISION OF SYSTEMATIC SAMPLING IN FOREST INVENTORIES

2015 ◽  
Vol 39 (1) ◽  
pp. 15-22 ◽  
Author(s):  
José Marcio de Mello ◽  
Henrique Ferraço Scolforo ◽  
Marcel Régis Raimundo ◽  
José Roberto Soares Scolforo ◽  
Antônio Donizette de Oliveira ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Forest Inventory ◽  
Sampling Rate ◽  
Sampling Technique ◽  
Systematic Sampling ◽  
Native Vegetation ◽  
Forest Inventories ◽  
Key Factor ◽  
The Mean ◽  
The Impact

The sampling technique commonly used in forest inventories is the systematic sampling. This study aimed to evaluate the estimator of the variance of the mean proposed by Cochran for a systematic sampling technique in forests with high and low percentages of the sampled area. The study areas comprised native vegetation in Minas Gerais. To assess the efficiency of the estimators in situations involving high sampling rates (determined as the percentage of the area sampled), a fragment where a census was conducted was used. The remaining fragments comprised situations involving low sampling rates, and for these fragments, inventory accuracy was determined using the Cochran estimator. As a result it was observed, in the fragment where the census was conducted, that the structure of the correlation coefficient proposed by Cochran remained approximately constant for the area, and to the extent that sampling rate reduced, the impact of the Cochran estimator on the inventory accuracy decreased. For the fragments with a low sampling rate, it could be inferred that the sampling rate was a key factor for the correlation proposed by Cochran to have an impact on the forest inventory accuracy. The use of this estimator is indicated for fragments with a sampling rate greater than 10% of the area.

scholarly journals Voxel-Based Automatic Tree Detection and Parameter Retrieval from Terrestrial Laser Scans for Plot-Wise Forest Inventory

2021 ◽  
Vol 13 (4) ◽  
pp. 542
Author(s):  
Gábor Brolly ◽  
Géza Király ◽  
Matti Lehtomäki ◽  
Xinlian Liang
Keyword(s):  
Tree Height ◽  
Parameter Extraction ◽  
Estimation Accuracy ◽  
Tree Crowns ◽  
Tree Detection ◽  
Height Estimates ◽  
Forest Inventories ◽  
Point Density ◽  
Fully Automatic ◽  
The Mean

This paper presents a fully automatic method addressing tree mapping and parameter extraction (tree position, stem diameter at breast height, stem curve, and tree height) from terrestrial laser scans in forest inventories. The algorithm is designed to detect trees of various sizes and architectures, produce smooth yet accurate stem curves, and achieve tree height estimates in multi-layered stands, all without employing constraints on the shape of the crown. The algorithm also aims to balance estimation accuracy and computational complexity. The method’s tree detection combines voxel operations and stem surface filtering based on scanning point density. Stem diameters are obtained by creating individual taper models, while tree heights are estimated from the segmentation of tree crowns in the voxel-space. Twenty-four sample plots representing diverse forest structures in the south boreal region of Finland have been assessed from single- and multiple terrestrial laser scans. The mean percentages of completeness in stem detection over all stand complexity categories are 50.9% and 68.5% from single and multiple scans, respectively, while the mean root mean square error (RMSE) of the stem curve estimates ranges from ±1.7 to ±2.3 cm, all of which demonstrates the robustness of the algorithm. Efforts were made to accurately locate tree tops by segmenting individual crowns. Nevertheless, with a mean bias of −2.9 m from single scans and −1.3 m from multiple scans, the algorithm proved conservative in tree height estimates.

scholarly journals Re-calibrating stem volume models – is there change in the tree trunk form from the 1970s to the 2010s in Finland?

Silva Fennica ◽  
2020 ◽  
Vol 54 (4) ◽  
Author(s):  
Annika Kangas ◽  
Helena Henttonen ◽  
Timo Pitkänen ◽  
Sakari Sarkkola ◽  
Juha Heikkinen
Keyword(s):  
Laser Scanning ◽  
Tree Height ◽  
Stem Volume ◽  
Large Dataset ◽  
Forest Inventories ◽  
National Forest Inventories ◽  
Downy Birch ◽  
The Mean ◽  
Volume Models ◽  
Diameter Classes

The tree stem volume models of Norway spruce, Scots pine and silver and downy birch currently used in Finland are based on data collected during 1968–1972. These models include four different formulations of a volume model, with three different combinations of independent variables: 1) diameter at height of 1.3 m above ground (), 2) and tree height () and 3) , and upper diameter at height of 6 m (). In recent National Forest Inventories of Finland, a difference in the mean volume prediction between the models with and without the upper diameter as predictor has been observed. To analyze the causes of this difference, terrestrial laser scanning (TLS) was used to acquire a large dataset in Finland during 2017–2018. Field-measured predictors and volumes predicted using spline functions fitted to the TLS data were used to re-calibrate the current volume models. The trunk form is different in these two datasets. The form height is larger in the new data for all diameter classes, which indicates that the tree trunks are more slender than they used to be. One probable reason for this change is the increase in stand densities, which is at least partly due to changed forest management. In models with both and as predictors, the volume is smaller a given class in the data new data than in the old data, and vice versa for the diameter classes. The differences between the old and new models were largest with pine and smallest with birch.dbhdbhhdbhhd6dbhhh

scholarly journals Investigating the influence of LiDAR ground surface errors on the utility of derived forest inventories

2012 ◽  
Vol 42 (3) ◽  
pp. 413-422 ◽  
Author(s):  
Wade T. Tinkham ◽  
Alistair M.S. Smith ◽  
Chad Hoffman ◽  
Andrew T. Hudak ◽  
Michael J. Falkowski ◽  
...  
Keyword(s):  
Vegetation Structure ◽  
Forest Inventory ◽  
Three Dimensional ◽  
Ground Surface ◽  
Tree Height ◽  
Dimensional Structure ◽  
Surface Errors ◽  
Forest Inventories ◽  
Significant Difference ◽  
Vertical Error

Light detection and ranging, or LiDAR, effectively produces products spatially characterizing both terrain and vegetation structure; however, development and use of those products has outpaced our understanding of the errors within them. LiDAR’s ability to capture three-dimensional structure has led to interest in conducting or augmenting forest inventories with LiDAR data. Prior to applying LiDAR in operational management, it is necessary to understand the errors in LiDAR-derived estimates of forest inventory metrics (i.e., tree height). Most LiDAR-based forest inventory metrics require creation of digital elevation models (DEM), and because metrics are calculated relative to the DEM surface, errors within the DEMs propagate into delivered metrics. This study combines LiDAR DEMs and 54 ground survey plots to investigate how surface morphology and vegetation structure influence DEM errors. The study further compared two LiDAR classification algorithms and found no significant difference in their performance. Vegetation structure was found to have no influence, whereas increased variability in the vertical error was observed on slopes exceeding 30°, illustrating that these algorithms are not limited by high-biomass western coniferous forests, but that slope and sensor accuracy both play important roles. The observed vertical DEM error translated into ±1%–3% error range in derived timber volumes, highlighting the potential of LiDAR-derived inventories in forest management.

scholarly journals Use of the correlation coefficient between plots in order to improve the accuracy of forest inventories

CERNE ◽  
2013 ◽  
Vol 19 (4) ◽  
pp. 575-580
Author(s):  
Daniela Cunha da Sé ◽  
José Márcio de Mello ◽  
João Domingos Scalon ◽  
Joel Augusto Muniz ◽  
Marcelo Silva de Oliveira ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Correlation Coefficient ◽  
Forest Inventory ◽  
Environmental Variables ◽  
Sampling Procedure ◽  
Systematic Sampling ◽  
Native Forest ◽  
Forest Inventories ◽  
Area Of Interest ◽  
The Mean

Forest inventories are usually compiled without taking into account the existing correlations between sampling units, which is debatable particularly where the calculations involve environmental variables. When the potential correlations between sampling units are overlooked, the accuracy of such inventories becomes distorted in terms of the confidence interval range for the variable of interest, which is volume in cubic meters. The magnitude and form of such distortion will vary according to the correlation intensity between sampling units. This study aimed to present an analysis of the addition of the correlation coefficient to the calculation of the variance of the mean in a systematic sampling procedure of a native forest population or area, as well as its impact on the accuracy of the resulting estimates, with the assumption of independence between sampling units and with the addition of a correlation between sampling units as suggested by Cochran. Results revealed that, where the correlation coefficient was added to the variance of the mean formula, it increased inventory accuracy by about 14.3%, leading to the conclusion that such an effect will occur in any forest inventory being compiled for any forest population or area of interest.

scholarly journals Reuse of field data in ALS-assisted forest inventory

Silva Fennica ◽  
2020 ◽  
Vol 54 (5) ◽  
Author(s):  
Ana de Lera Garrido ◽  
Terje Gobakken ◽  
Hans Ørka ◽  
Erik Næsset ◽  
Ole Bollandsås
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Field Data ◽  
Reference Data ◽  
Growth Models ◽  
Basal Area ◽  
Tree Height ◽  
Cost Component ◽  
Forest Inventories ◽  
Forest Attributes

Forest inventories assisted by wall-to-wall airborne laser scanning (ALS), have become common practice in many countries. One major cost component in these inventories is the measurement of field sample plots used for constructing models relating biophysical forest attributes to metrics derived from ALS data. In areas where ALS-assisted forest inventories are planned, and in which the previous inventories were performed with the same method, reusing previously acquired field data can potentially reduce costs, either by (1) temporally transferring previously constructed models or (2) projecting field reference data using growth models that can serve as field reference data for model construction with up-to-date ALS data. In this study, we analyzed these two approaches of reusing field data acquired 15 years prior to the current ALS acquisition to estimate six up-to-date forest attributes (dominant tree height, mean tree height, stem number, stand basal area, volume, and aboveground biomass). Both approaches were evaluated within small stands with sizes of approximately 0.37 ha, assessing differences between estimates and ground reference values. The estimates were also compared to results from an up-to-date forest inventory relying on concurrent field- and ALS data. The results showed that even though the reuse of historical information has some potential and could be beneficial for forest inventories, systematic errors may appear prominent and need to be overcome to use it operationally. Our study showed systematic trends towards the overestimation of lower-range ground references and underestimation of the upper-range ground references.

Customized anterior craniocervical reconstruction via a modified high-cervical retropharyngeal approach following resection of a spinal tumor involving C1–2/C1–3

2020 ◽  
Vol 32 (3) ◽  
pp. 432-440
Author(s):  
Shaohui He ◽  
Chen Ye ◽  
Nanzhe Zhong ◽  
Minglei Yang ◽  
Xinghai Yang ◽  
...  
Keyword(s):  
Cervical Spinal Cord ◽  
Perioperative Complications ◽  
Japanese Orthopaedic Association ◽  
Spinal Tumor ◽  
Spinal Tumors ◽  
Limited Information ◽  
Improvement Rate ◽  
The Mean ◽  
High Cervical ◽  
Occipital Condyles

OBJECTIVEThe surgical treatment of an upper cervical spinal tumor (UCST) at C1–2/C1–3 is challenging due to anterior exposure and reconstruction. Limited information has been published concerning the effective approach and reconstruction for an anterior procedure after C1–2/C1–3 UCST resection. The authors attempted to introduce a novel, customized, anterior craniocervical reconstruction between the occipital condyles and inferior vertebrae through a modified high-cervical retropharyngeal approach (mHCRA) in addressing C1–2/C1–3 spinal tumors.METHODSSeven consecutive patients underwent 2-stage UCST resection with circumferential reconstruction. Posterior decompression and occiput-cervical instrumentation was conducted at the stage 1 operation, and anterior craniocervical reconstruction using a 3D-printed implant was performed between the occipital condyles and inferior vertebrae via an mHCRA. The clinical characteristics, perioperative complications, and radiological outcomes were reviewed, and the rationale for anterior craniocervical reconstruction was also clarified.RESULTSThe mean age of the 7 patients in the study was 47.6 ± 19.0 years (range 12–72 years) when referred to the authors’ center. Six patients (85.7%) had recurrent tumor status, and the interval from primary to recurrence status was 53.0 ± 33.7 months (range 24–105 months). Four patients (57.1%) were diagnosed with a spinal tumor involving C1–3, and 3 patients (42.9%) with a C1–2 tumor. For the anterior procedure, the mean surgical duration and average blood loss were 4.1 ± 0.9 hours (range 3.0–6.0 hours) and 558.3 ± 400.5 ml (range 100–1300 ml), respectively. No severe perioperative complications occurred, except 1 patient with transient dysphagia. The mean pre- and postoperative visual analog scale scores were 8.0 ± 0.8 (range 7–9) and 2.4 ± 0.5 (range 2.0–3.0; p < 0.001), respectively, and the mean improvement rate of cervical spinal cord function was 54.7% ± 13.8% (range 42.9%–83.3%) based on the modified Japanese Orthopaedic Association scale score (p < 0.001). Circumferential instrumentation was in good position and no evidence of disease was found at the mean follow-up of 14.8 months (range 7.3–24.2 months).CONCLUSIONSThe mHCRA provides optimal access to the surgical field at the C0–3 level. Customized anterior craniocervical fixation between the occipital condyles and inferior vertebrae can be feasible and effective in managing anterior reconstruction after UCST resection.

scholarly journals Deriving Tree Size Distributions of Tropical Forests from Lidar

2021 ◽  
Vol 13 (1) ◽  
pp. 131
Author(s):  
Franziska Taubert ◽  
Rico Fischer ◽  
Nikolai Knapp ◽  
Andreas Huth
Keyword(s):  
Size Distribution ◽  
Spatial Scales ◽  
Basal Area ◽  
Tree Height ◽  
Tree Size ◽  
Diameter Distribution ◽  
Forest Inventories ◽  
Allometric Relations ◽  
Lidar Measurements ◽  
Derived Data

Remote sensing is an important tool to monitor forests to rapidly detect changes due to global change and other threats. Here, we present a novel methodology to infer the tree size distribution from light detection and ranging (lidar) measurements. Our approach is based on a theoretical leaf–tree matrix derived from allometric relations of trees. Using the leaf–tree matrix, we compute the tree size distribution that fit to the observed leaf area density profile via lidar. To validate our approach, we analyzed the stem diameter distribution of a tropical forest in Panama and compared lidar-derived data with data from forest inventories at different spatial scales (0.04 ha to 50 ha). Our estimates had a high accuracy at scales above 1 ha (1 ha: root mean square error (RMSE) 67.6 trees ha−1/normalized RMSE 18.8%/R² 0.76; 50 ha: 22.8 trees ha−1/6.2%/0.89). Estimates for smaller scales (1-ha to 0.04-ha) were reliably for forests with low height, dense canopy or low tree height heterogeneity. Estimates for the basal area were accurate at the 1-ha scale (RMSE 4.7 tree ha−1, bias 0.8 m² ha−1) but less accurate at smaller scales. Our methodology, further tested at additional sites, provides a useful approach to determine the tree size distribution of forests by integrating information on tree allometries.

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