• Journal of Ecology and Environment
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• v.37 no.2
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• pp.105-111
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• 2014

To elucidate whether small diameter at breast height correlates with tree death in an overcrowded tree population, we analyzed self-thinning occurring over the course of 37 years in naturally established Pinus densiflora populations in Sugadaira, central Japan. As trees grew, their diameters at breast height increased and the number of trees consequently decreased. Spatial distribution, which was initially clumped, changed accordingly, first becoming random and finally uniform. We calculated the "available area" of individual trees to elucidate the contribution of this parameter to tree mortality. Small diameter at breast height was strongly correlated with tree death, with a slight correlation observed between tree death and small available area of individual trees.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1042-1044
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• 2003

A methodology of the integrating the similar color circle search of the spectral data and segmentation of the height data is developed. The method is then applied to study areas, and the results by IKONOS, LIDAR and data fusion are verified with the ground truth, and examined in terms of the accuracy. Results show that with the data fusion the accuracy are improved by about 15% in most of the study areas. The methodology for the detection of individual tree stands by data fusion is explored, and the utility of combinatorial use of the spectral and the height information is demonstrated.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.67-74
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• 2016

Drone images with high spatial resolution are emerging as an alternative to previous studies with extraction limits in high density forests. Individual tree in the dense forests were extracted from drone images. To detect the individual tree extracted through the image segmentation process, the image segmentation results were compared between the combination of DSM and all R,G,B band and the combination of DSM and R,G,B band separately. The changes in the tree density of a deciduous forest was experimented by time and image. Especially the image of May when the forests are dense, among the images of March, April, May, the individual tree extraction rate based on the trees surveyed on the site was 50%. The analysis results of the width of crown showed that the RMSE was less than 1.5m, which was the best result. For extraction of the experimental area, the two sizes of medium and small trees were extracted, and the extraction accuracy of the small trees was higher. The forest tree volume and forest biomass could be estimated if the tree height is extracted based on the above data and the DBH(diameter at breast height) is estimated using the relational expression between crown width and DBH.

• 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.200-203
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• 2008

The objective of this study is to produce the $CO_2$ (carbon dioxide) absorption map using KOMPSAT-2 imagery. For estimating the amount of $CO_2$ absorption, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated by the crown width extracted from KOMPSAT-2 imagery. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the IPCC (Intergovernmental Panel on Climate Change) guideline, was used to convert the stand biomass into the amount of $CO_2$ absorption. Thereafter, the KOMPSAT-2 imagery was classified with the SBC (segment based classification) method in order to quantify $CO_2$ absorption by tree species. As a result, the map of $CO_2$ absorption was produced and the amount of $CO_2$ absorption was estimated by tree species.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.2
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• pp.68-76
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• 2001

The purpose of this study is to computerize street tree management using a CAD program in order to manage the drawing record of street trees systematically and concurrently. The configuration of this program is composed of Reference Data, Data Inquiry, and Cost Assessment. The Reference Data includes characteristics of trees, monthly managements records, damage by blight and insects and usage of pesticides. The Data Inquiry includes an individual search of the tree index, simple searches and multiple searches. The Cost Assessment includes two main components, the data input with labor cost, manure ocst and pesticide cost and the assesment of management cost for prevention of blight and insects, pruning and fertilization. The results of this study are as follows: 1) When there are practices such as transplanting and removing of street trees it is immediately updated with the various situation. By creating an in progress a tree management system, up to the date information can be given to the manager for decision making. 2) To identify individual tree at the site or in drawing, the street name and numbers were used instead of coordinates. Tree tags are attached to the street trees individually. It can make DB management simple and easy. 3) By doing simple or multiple search with constructed DB, data can be provided quickly. 4) The result of this type of search are useful in the assessment of management cost very useful in regards to items such as the pruning, pesticides scattering and fertilization. 5) By using the AutoCAD software and existing PC without purchasing new equipment, the cost of system implementation can be minimized.

• Journal of Ecology and Environment
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• v.35 no.4
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• pp.359-365
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• 2012

We investigated leaf disease intensity of Kalopanax septemlobus (prickly castor oil tree) caused by the parasitic fungus Mycosphaerella acanthopanacis, in thirty natural host populations in the Japanese Archipelago. The disease intensity observed for individual trees were analyzed using a generalized additive model as a function of tree size, tree density, climatic terms and spatial trend surface. Individual tree size and conspecific tree density were shown to have significant negative and positive effects on disease intensity, respectively. The findings suggest that the probability of disease infection is partly determined by dispersal of infection agents (ascospores) from the fallen leaves on the ground, which can be enhanced by aggregation of host trees in a forest stand. Regional-scale spatial bias was also present in disease intensity; the populations in northern Japan and southern Kyushu were more severely infected by the fungus than those in southwestern Honshu and Shikoku. Regional variation of disease intensity was explained by both climatic factors and a trend surface term, with a latitudinal cline detected, which increases towards the north. Further research should be conducted in order to understand all of the factors generating the latitudinal cline detected in this study.

• Journal of the Korean Society of Safety
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• v.10 no.1
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• pp.56-63
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• 1995

Two methods of the numerical method of CPQRA(Chemical Process Quantitative Risk Analysis) and the manual method of IAEA(International Atomic Energy Agency) were used to estimate the individual risk and societal risk around the chemical plant. Where, the CPQRA is introduced to verify the theoritical background of the manual of international atomic energy agency. The Gaussian plume model which has a weather stability class D with velocity of 5m/s was applied to calculate dispersion of hazard material. Also, 8-point method was employed to the effects of accidents for wind distribution. Furthermore, historical record, FTA(Fault Tree Analysis) and ETA(Event Tree Analysis) were used to estimate the probability or frequency of accidents. Eventually, the individual risk shows isorisk contour and the societal risk shows F-N curve around hazard facility, especially in chemical plants. Caulculated results, which both individual and societal risk, by using IAEA manual show simillar results to those of calculation by numerical method of CPQRA.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1731-1738
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• 2021

The objective of this study was to extract individual trees and tree heights using UAV drone images. The study site was Gongju national university experiment forest, located in Yesan-gun, Chungcheongnam-do. The thinning intensity study sites consisted of 40% thinning, 20% thinning, 10% thinning and control. The image was filmed by using the "Mavic Pro 2" model of DJI company, and the altitude of the photo shoot was set at 80% of the overlay between 180m pictures. In order to prevent image distortion, a ground reference point was installed and the end lap and side lap were set to 80%. Tree heights were extracted using Digital Surface Model (DSM) and Digital Terrain Model (DTM), and individual trees were split and extracted using object-based analysis. As a result of individual tree extraction, thinning 40% stands showed the highest extraction rate of 109.1%, while thinning 20% showed 87.1%, thinning 10% showed 63.5%, and control sites showed 56.0% of accuracy. As a result of tree height extraction, thinning 40% showed 1.43m error compared with field survey data, while thinning 20% showed 1.73 m, thinning 10% showed 1.88 m, and control sites showed the largest error of 2.22 m.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.99-110
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• 2023

In this paper, we propose a system termed ForestLi that can accurately estimate the diameter at breast height (DBH) and tree height using LiDAR point cloud data. The ForestLi system processes LiDAR point cloud data through the following steps: downsampling, outlier removal, ground segmentation, ground height normalization, stem extraction, individual tree segmentation, and DBH and tree height measurement. A commercial system, such as LiDAR360, for processing LiDAR point cloud data requires the user to directly correct errors in lower vegetation and individual tree segmentation. In contrast, the ForestLi system can automatically remove LiDAR point cloud data that correspond to lower vegetation in order to improve the accuracy of estimating DBH and tree height. This enables the ForestLi system to reduce the total processing time as well as enhance the accuracy of accuracy of measuring DBH and tree height compared to the LiDAR360 system. We performed an empirical study to confirm that the ForestLi system outperforms the LiDAR360 system in terms of the total processing time and accuracy of measuring DBH and tree height.