• Korean Journal of Environment and Ecology
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• v.26 no.3
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• pp.382-393
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• 2012

The purpose of this study was to research the vegetation structure of the Bongamsa Forest Genetic Resourses Resreve Area in Mt. Heuyang, Mungyeong, Gyeongsangbuk-do. For doing this, ninety-two plots($100m^2/plot$) were set up and investigated, and then Classification analysis and Ordination analysis were carried out. As a result, the vegetation of this area is divided to nine communities; Quercus mongolica community, Quercus variabilis community, Pinus densiflora community, Pinus densiflora-Quercus serrata community, Pinus densiflora-Quercus mongolica community, Quercus serrata community, Decideous broad leaf community, Pinus koraiensis community, Larix kaempferi community. To compare between the communities, statistical analyses were conducted with topographical condition and the results of the vegetational investigation of each community. In altitude, slope, the number of species, the number of individuals in canopy and the number of individuals of understory layer, the mean averages among the communities were different in statistically significance. Then we analysed the vegetation community structure with Importance Percentage of each stratum. The oak tree communities were expected to keep or expand the actual communities because oak trees are spread widely in canopy and understory layers. But the pine tree dominant communities were expected to be succeeded to oak tree communities in the future because of the wide expansion of oak trees.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.201-214
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• 2020

This study aimed to early detect damaged trees by pine wilt disease using the vegetation indices of UAV images. The location data of 193 pine wilt disease trees were constructed through field surveys and vegetation index analyses of NDVI, GNDVI, NDRE and SAVI were performed using multi-spectral UAV images at the same time. K-Means algorithm was adopted to classify damaged trees and confusion matrix was used to compare and analyze the classification accuracy. The results of the study are summarized as follows. First, the overall accuracy of the classification was analyzed in order of NDVI (88.04%, Kappa coefficient 0.76) > GNDVI (86.01%, Kappa coefficient 0.72) > NDRE (77.35%, Kappa coefficient 0.55) > SAVI (76.84%, Kappa coefficient 0.54) and showed the highest accuracy of NDVI. Second, K-Means unsupervised classification method using NDVI or GNDVI is possible to some extent to find out the damaged trees. In particular, this technique is to help early detection of damaged trees due to its intensive operation, low user intervention and relatively simple analysis process. In the future, it is expected that the utilization of time series images or the application of deep learning techniques will increase the accuracy of classification.

• International Area Studies Review
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• v.15 no.3
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• pp.583-603
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• 2011

This study was designed to comprehensively understand and separate the characteristics of recreation forests of Korea through the multi-variate analysis for the provision of fundamental materials for recreation forests development policies and planning, and attempted to evaluate on the validity of classification of recreation forests, which has never been performed before. According to analysis results, recreation forests could be divided into 4 types; type I(recreation forests whose ecological nature status is not good, but the risk of calamity is low and accessibility is good), type II(recreation forests whose the risk of calamity is low, but ecological nature status is not good, slope is steep, and accessibility is poor), type III(recreation forests that have charming vegetation and landscape, various rest opportunity, and a gentle slope, but poor accessibility), and type IV(recreation forests that ecological nature status is good, but have poor landscape, less rest opportunity, and a steep slope). Also, each type was adjusted as follows; type I($25{\rightarrow}24$ reviews), type II($25{\rightarrow}26$ reviews), type III($17{\rightarrow}16$ reviews), and type IV($25{\rightarrow}25$ reviews). This study can be said to show the usability of validation of classified types, which was not done before. It is clear that the classification of recreation forests increases the efficiency in policy making and performance. Furthermore, by validating the separated types, we could expect high efficiency in policy making and performance on planned recreation forests in the future.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.1
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• pp.55-63
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• 2006

This study was carried out to analyze community character and classify forest community with phytosociological method and quadrat method to forest of Mt. Busosan in Buyeo-Gun.1. Communities by phytosociological method were classified into Pinus densiflora community and Quercus sp. community. With the classification of TWINSPAN, the community was categorized into Pinus densiflora - Quercus variabilis community and Pinus densiflora - Styrax japonica community.2. The importance value of Pinus densiflora, Quercus acutissima, Prunus sargentii, Styrax japonica, Quercus serrata, Quercus variabilis, Pinus rigida, Quercus aliena in tree layer were 83.20, 41.87, 30.93, 24.85, 23.27, 20.97, 20.28, and 9.46, respectively. The relative coverage of Stephanandra incisa, Quercus serrata, Styrax japonica, Parthenocissua tricuspidata, Rhododendron mucronulatum, Lindera obtusiloba, Prunus sargentii, Quercus variabilis, Indigofera kirilowii, Quercus acutissima, Lespedeza maximowiczii, and Acer pseudosibolianum in shrub layer were 9.62%, 9.55%, 9.18%, 7.85%, 6.18%, 5.25%, 4.82%, 4.15%, 3.98%, 3.98%, 3.55%, and 2.98%, respectively.3. According to size distribution map of diameter breast height of dominant species, the dominant species of Mt. Busosan was Pinus densiflora, and Quercus sp. such as Quercus acutissima, Quercus variabilis, and Quercus serrata may compete with the Pinus densiflora in the future.4. According to the ordination analysis of Mt. Busosan forest, Pinus densiflora - Styrax japonica community was found in moist site and Pinus densiflora - Quercus variabilis community was found in dry site.

• Korean Journal of Environment and Ecology
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• v.26 no.5
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• pp.770-779
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• 2012

In order to verify the characteristics of vegetation structure in Jeolgu valley, Nakdongjeongmaek, we set up 29 plots(each plot area is $10m{\times}10m(100m^2)$. The survey site is located in around the valley and its range is about 3km section. The forest vegetation communities were analysed by TWINSPAN classification. The results of communities were classified 5 types such as Pinus densiflora community, deciduous broad-leaved tree community, Quercus variabilis community, Quercus mongolica community, Larix leptolepis community. The deciduous broad-leaved tree which prefer to moist environment and Quercus spp. has dominant in around the valley and the northern slope. In addition, Larix leptolepis community expect to maintain the present status for a while. However, the under story of Larix leptolepis community have expanded the influence of deciduous broad-leaved tree such as Fraxinus mandshurica, Morus bombycis, Acer mono and so on. Therefore, there will be developed next ecological succession by species of deciduous broad-leaved tree. The diversity index showed form 0.9665 to 1.2450. It were analyzed that diversity index of Jeolgu valley was higher than other places in Nakdongjeongmaek.

• Journal of Forest and Environmental Science
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• v.29 no.1
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• pp.49-57
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• 2013

Malaysia possesses about 1.56 million ha of Peat Swamp Forest (PSF). The PSF safeguard enormous biological diversity, while providing crucial benefits for the sustainable development of human communities. Numbers of threatened plant species are associated with the PSF, including the commercially important Gonystylus bancanus timber. To prevent significant losses of biodiversity, it is important to manage the PSF for both biological conservation and sustainable use. Equally important is to restore all degraded PSF in an attempt to ensure the PSF ecosystem is suitable for the vegetation to grow and rehabilitate back to the normal condition. Prior to plan any forest restoration program, there is a need to properly map the degraded PSF in order to estimate the forest conditions and determine the vegetations status. Most of the time this need to be done at a landscape level and requires a technology that can provide accurate, timely and reliable information for the planner to make decision. This paper describes a study using geospatial technology in combination with ground survey to classify the degraded PSF in South East Pahang Peat Swamp Forest (SEPPSF), Malaysia, into different degree of vegetation classes. With map accuracy of about 83%, the technique proved to be useful in delineating the different degree of PSF degradation from which the information can be used to properly plan forest restoration program in the area. The final output which is in the form of map can be used in developing a Restoration Master Plan for the degraded PSF areas.

• Journal of the Korean Institute of Landscape Architecture
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• v.32 no.1
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• pp.33-46
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• 2004

This study is aimed to redesign established parks and to propose a series of devices protecting them from vandalism. To solve the problems, we ascertained the damaged areas of the park greens. The trace analysis was performed to grasp the transverse inside the parks of Jeonju and Iksan in Collabuldo. Then, we presented the basic plan for minimizing park damage and for remodeling the system of movement. The results of the study are summarized as follows: it is identified that the transverse phenomenon is considerably wide-spread in majority of parks, and has no relationship to the park area or the green area. It is considered that the $\ulcorner$Condition rating class$\lrcorner$ of grass damage, which is grade 6, is extraordinarily high and the damage is accumulated considerably. Also, the damage part of other grade is discovered equally, and when unattended, the acceleration of damage is positive. A damage width a 0.5∼1.5m makes up the greater part of 79.6%. It also constitutes most of a rectilinear form. The difference in the height between the original point and destination point is below 0.7m, which is above 70%. It is identified that the interrelationship between the damage continuation length and plan distance is relatively high by the simple regression: analysis and by Pearson' correlation analysis. In spite of the normal damage continuation length is 20m, the frequency degree is downward with extreme point at 10m. Accordingly, it is assumed that park users have physical and psychological pressure when they cross the lawn field. Damage types are classified as the Simple cut cross type, the Behavioral facilitates type, Access advantage type and the Strolling type through type classification. It is considered that this classification is effective when identifying short pass type on lawn field according to the damage length and intensity.

• Korean Journal of Environmental Biology
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• v.21 no.3
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• pp.262-270
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• 2003

This study was carried out to analyze forest vegetation of Jinaksan in Geumsan, Chungnam Province. Employing the releve method of Braun-Blanquet, 26 plots were sampled in forest of Jinaksan. The communities were classified into Quercus mongolica, Quercus variabilis, Quercus aliena, and Pinus densiflora communities. Coverage rate was 79.4% in tree layer,27.6% in subtree layer,37.0% in shrub layer, 31.1% in herb layer, respectively. The importance values were 45.51 in Q. mongolica,44.17 in P. densiflora,26.56 in Q. variabilis,26.78 in Q. serrata,20.81 in Q. aliena, and 15.58 in Prunus serrulata var. spontanea, respectively. Most of the DBH in the Q. mongolica, Q. variabilis, Q. aliena, and p. densiflora was between 5 cm and 15 cm. Therefore, Q. mongolica, Q. variabilis, and Q. aliena will be dominant species in the study area for several decades.

• Journal of People, Plants, and Environment
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• v.24 no.4
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• pp.441-450
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• 2021

Background and objective: The purpose of study is to analyze the three-dimensional (3D) structure by creating a 3D model for green spaces in a park using unmanned aerial vehicle (UAV) images. Methods: After producing a digital surface model (DSM) and a digital terrain model (DTM) using UAV images taken in Mureung Park in Chuncheon-si, we generated a digital tree height model (DHM). In addition, we used the mean shift algorithm to test the classification accuracy, and obtain accurate tree height and volume measures through field survey. Results: Most of the tree species planted in Mureung Park were Pinus koraiensis, followed by Pinus densiflora, and Zelkova serrata, and most of the shrubs planted were Rhododendron yedoense, followed by Buxus microphylla, and Spiraea prunifolia. The average height of trees measured at the site was 7.8 m, and the average height estimated by the model was 7.5 m, showing a difference of about 0.3 m. As a result of the t-test, there was no significant difference between height values of the field survey data and the model. The estimated green coverage and volume of the study site using the UAV were 5,019 m² and 14,897 m³, respectively, and the green coverage and volume measured through the field survey were 6,339 m² and 17,167 m³. It was analyzed that the green coverage showed a difference of about 21% and the volume showed a difference of about 13%. Conclusion: The UAV equipped with RTK (Real-Time Kinematic) and GNSS (Global Navigation Satellite System) modules used in this study could collect information on tree height, green coverage, and volume with relatively high accuracy within a short period of time. This could serve as an alternative to overcome the limitations of time and cost in previous field surveys using remote sensing techniques.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.686-697
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• 2018

Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.