• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.389-401
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• 2011

Most nations around the world have expressed significant concern in the climate change due to a rapid increase in green-house gases and thus reach an international agreement to control total amount of these gases for the mitigation of global warming. As the most important absorber of carbon dioxide, one of major green-house gases, forest resources should be more tightly managed with a means to measure their total amount, forest biomass, efficiently and accurately. Forest biomass has close relations with forest areas and tree height. Airborne LiDAR data helps extract biophysical properties on forest resources such as tree height more efficiently by providing detailed spatial information about the wide-range ground surface. Many researchers have thus developed various methods to estimate tree height using LiDAR data, which retain different performance and characteristics depending on forest environment and data characteristics. In this study, we attempted to investigate such various techniques to estimate tree height, elaborate their advantages and limitations, and suggest future research directions. We first examined the characteristics of LiDAR data applied to forest studies and then analyzed methods on filtering, a precedent procedure for tree height estimation. Regarding the methods for tree height estimation, we classified them into two categories: individual tree-based and regression-based method and described the representative methods under each category with a summary of their analysis results. Finally, we reviewed techniques regarding data fusion between LiDAR and other remote sensing data for future work.

• Journal of Forest and Environmental Science
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• v.33 no.3
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• pp.187-196
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• 2017

The use of unmanned aerial vehicles (UAV) for the estimation of tree height is gaining recognition. This study aims to assess the effectiveness of tree height estimation of Pinus densiflora Sieb. et Zucc. and Pinus koraiensis Sieb. et Zucc. using digital surface model (DSM) generated from UAV-acquired imageries. Images were taken with the $Trimble^{(R)}$ UX5 equipped with Sony ${\alpha}5100$. The generated DSM, together with the digital elevation model (DEM) generated from a digital map of the study areas, were used in the estimation of tree height. Field measurements were conducted in order to generate a regression model and carry out accuracy assessment. The obtained coefficients of determination (R2) and root mean square error (RMSE) for P. densiflora (R2=0.71; RMSE=1.00 m) and P. koraiensis (R2=0.64; RMSE=0.85 m) are comparable to the results of similar studies. The results of the paired two-tailed t-test show that the two tree height estimation methods are not significantly different (p-value=0.04 and 0.10, alpha level=0.01), which means that tree height estimation using UAV imagery could be used as an alternative to field measurement.

• Spatial Information Research
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• v.20 no.3
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• pp.27-38
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• 2012

As the necessity of forest conservation and management has been increased, various forest studies using LIDAR data have been actively performed. These studies often utilize the tree height as an important parameter to measure the forest quantitatively. This study thus attempt to apply two representative methods to estimate tree height from airborne LIDAR data and compare the results. The first method based on the detection of the individual trees using a local maximum filter estimates the number of trees, the position and heights of the individual trees, and the mean tree height. The other method estimates the maximum and mean tree height, and the crown mean height for each grid cell or the entire area from the canopy height model (CHM) and height histogram. In comparison with the field measurements, 76.6% of the individual trees are detected correctly; and the estimated heights of all trees and only conifer trees show the RMSE of 1.91m and 0.75m, respectively. The tree mean heights estimated from CHM retain about 1~2m RMSE, and the histogram method underestimates the tree mean height with about 0.6m. For more accurate derivation of diverse forest information, we should select and integrate the complimentary methods appropriate to the tree types and estimation parameters.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.394-397
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• 2008

This research aimed at developing a technique for estimating the tree height using BRF (Bi-directional Reflectance Factor) through the clarification of the relation between shape of the tree crown and the tree height and the relations between the shape of the tree crown and BRF. This paper, reports the results of analyses of data acquired by field measurements done to clarify relation between crown shape and tree height.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.441-448
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• 2010

This paper estimates the tree height using Airborne LiDAR that is obtained for each season to analyze its influence based on a canopyclosure and data fusion. The tree height was estimated by extracting the First Return (RF) from the tree and the Last Return (LR) from the surface of earth to assume each tree via image segmentation and to obtain the height of each tree. Each data on tree height that is collected from seasonal data and the result of tree height acquired from the data fusion were compared. A tree height measuring device was used to measure on site and its accuracy was compared. Also, its applicability on the result of fused data that is obtained through the Airborne LiDAR is examined. As a result of the experiment, the result of image segmentation for an individual tree was closer to the result of site study for 1 meter interval when compared to the 0.5 meter interval of point cloud. In case of the tree height, the application of fused data enables a closer site measurement result than the application of data for each season.

• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.47-54
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• 1999

To estimate optimal tree diameter and height growth function in Pinus thunbergii stands with site index of 12 class, quoted from two linear models of linear transformation(1) and linear transformation (2) and four non-linear models of exponential, Gompertz, Chapman-Richards, and Weibull etc.. Analyzed correlation among the estimated tree diameter and height by these function models, and observed diameter and height growth were compared. In the results of tree diameter and height growth estimation by stand age, non-linear models showed better appropriation than linear model and Chapman-Richards model was most fitted for tree height growth but few, if any, differences among their nonlinear models. Therefore, it is consider to be much more study about non-linear model to estimate tree diameter and height growth in the actual stands hereafter.

• Journal of The Korean Society of Grassland and Forage Science
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• v.14 no.2
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• pp.120-124
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• 1994

Browse from oriental white oak(Quercus aliena Blume) was analysed for nutritive value and biomass estimation. The content of cmde protein was high on August and September. NDF, ADF and lignin contents were increased with progressing the seasons but IVDMD, TDN, DE and ME levels were not different from the variation of seasons. Tannin content was high on May and June. Basal stem diameter $\times$ height of tress was highly correlated with browse dry weights(r=0.80**) and the linear regression equation are the follows; Y = 8.23 + O.57X(Y = browse dry weight(g), X= basal stem diameter $\times$ height(cm)). Using the traditional cutting method, the amounts of browse was determined as 823 g dry weight per tree, while the new method by the above equation gave a similar results, i. e., 793 g dry weight per tree. The possibility of browse biomass estimation of oriental white oak by the basal stem diameter $\times$ height index was found.

• Journal of Korean Society of Forest Science
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• v.98 no.5
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• pp.576-583
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• 2009

Based on the stem analysis and biomass measurement of 36 trees and 1,576 branches in Pinus sylvestris var. mongolica (Mongolian pine) plantations of Northeast China, this study was conducted to develop estimation model equation for leaf biomass of a single tree and branch, to examine the vertical distribution of leaf biomass in the crown, and to evaluate the proportional ratios of biomass by tree parts, stem, branch, and leaf. The results indicated that DBH and crown length were quite appropriate to estimate leaf biomass. The biomass of single branch was highly correlated with branch collar diameter and relative height of branch in the crown, but not much with stand density, site quality, and tree height. Weibull distribution function would have been appropriate to express vertical distribution of leaf biomass. The shape parameters from 29 sample trees out of 36 were less than 3.6, indicating that vertical distribution of leaf biomass in the crown was displayed by bell-shaped curve, a little inclined toward positive side. Apparent correlationship was obtained between leaf biomass and branch biomass having resulted in linear function equation. The stem biomass occupied around 80% and branch and leaf made up about 20% of total biomass in a single tree. As the level of tree class was increased from class I to class V, the proportion of the stem biomass to total biomass was gradually increased, but that of branch and leaf became decreased.

• Journal of Korean Society of Forest Science
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• v.89 no.3
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• pp.414-421
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• 2000

This study was carried out for the artificial forest stand of 23 years old jack pine(Pinus banksiana Lamb.) in Soheul-myun, Pochun-kun, Kyunggi province of Korea. The objectives of this study were to investigate the stand volume increment and the rate of stand volume, and were to investigate present stand volume to determine annual cutting volume for keeping stand volume to an ideal level for investigated jack pine stand. For a reasonable calculation of stand volume increment, diameter of breast height(DBH), tree height, bark width, and core length for the last 10 years for respective sampling plots were measured. By using these measurements annual diameter increment in DBH class, stand volume increment of 95% confidence interval and tree height curve equation were calculated. The tree height value was derived from the tree height curve equation. Calculation of tree volume by using the tree volume table was made by conferring the tree height value. The summarized results for investigated jack pine trees were having 7.7% annual stand volume increment with 6.1% estimated error. The total stand volume per ha was $79.58m^3$, accordingly the annual stand volume increment was $6.13m^3$ per ha, and the 95% confidence intervals range from 5.77 to $6.51m^3$.

• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.204-212
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• 2010

This study was performed in 22 unthinned Larix olgensis plantations in northeast China. Data were collected on 95 sample trees of different canopy positions and the diameter at breast height ($d_{1.3}$) ranged from 5.7 cm to 40.2 cm. The individual tree models for the prediction of vertical distribution of live crown, branch and needle biomass were built. Our study showed that the crown, branch and needle biomass distributions were most in the location of 60% crown length. These results were also parallel to previous crown studies. The cumulative relative biomass of live crown, branch and needle were fitted by the sigmoid shape curve and the fitting results were quite well. Meanwhile, we developed the crown ratio and width models. Tree height was the most important predictor for crown ratio model. A negative competition factor, ccf and bas which reflected the effect of suppression on a tree, reduced the crown ratio estimates. The height-diameter ratio was a significant predictor. The higher the height-diameter ratio, the higher crown ratio is. Diameter at breast height is the strongest predictor in crown width model. The models can be used for the planning of harvesting operations, for the selection of feasible harvesting methods, and for the estimation of nutrient removals of different harvesting practices.