• Journal of agriculture & life science
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• v.52 no.6
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• pp.37-47
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• 2018

The objective of this study was to analyze the influences of forest management activity on the diameter distribution of Larix kaempferi Carriere stands in South Korea. We used 232 managed stands data, 47 unmanaged stands data of National Forest Inventory for this study. We employed the Weibull distribution function for estimating diameter based on percentiles and parameter recovery method. The results revealed that the average diameter breast height movements and growth of tree in the managed stands higher than the unmanaged stands according to the scenario: age, site index, and tree density change. The finding shows the percentage of the total amount of large class diameter was also high in the managed stands. The results of this study could be apply for the estimation of multi-products of timbers per diameter classes and stand structure development for Larix kaempferi Carriere stands in South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1053-1065
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• 2019

Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.461-472
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• 2022

Natural and anthropogenic factors cause forest types to continuously change. Since the ratio of forest area by forest type is important information for identifying the characteristics of national forest resources, an accurate understanding of the prospect of forest type change is required. The study aim was to use National Forest Inventory (NFI) time-series data to understand the characteristics of forest type change and to estimate future prospects of nationwide forest type change. We used forest type change information from the fifth and seventh NFI datasets, climate, topography, forest stand, and disturbance variables related to forest type change to analyze trends and characteristics of forest type change. The results showed that the forests in Korea are changing in the direction of decreasing coniferous forests and increasing mixed and broadleaf forests. The forest sites that were changing from coniferous to mixed forests or from mixed to broadleaf forests were mainly located in wet topographic environments and climatic conditions. The forest type changes occurred more frequently in sites with high disturbance potential (high temperature, young or sparse forest stands, and non-forest areas). We used a climate change scenario (RCP 8.5) to establish a forest type change model (SVM) to predict future changes. During the 40-year period from 2015 to 2055, the SVM predicted that coniferous forests will decrease from 38.1% to 28.5%, broadleaf forests will increase from 34.2% to 38.8%, and mixed forests will increase from 27.7% to 32.7%. These results can be used as basic data for establishing future forest management strategies.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1067-1082
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• 2019

This review paper presents a review of evidence on systems and technologies for recent remote sensing techniques which were applied into forest and forest related sectors. The paper reviewed remote sensing techniques that will have, or already having, a substantial impact on improving data quality of forest inventory and forest management and planning. The aim of this review is to identify, categorize and discuss Korean and international sources published primarily in the last decades. The focus on remote sensing and ICT technologies examines issues related to their opportunities, limitation, use and impact on the forestry. More specifically, this literature review has focused on laser scanning, satellite imagery, and Unmanned aerial vehicles (UAV) utilization in forest management and inventory analysis.

• Journal of Forest and Environmental Science
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• v.30 no.4
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• pp.331-341
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• 2014

The present study is an attempt to give an account of the inventory of plant species, phytosociological characteristics of vegetation and pedological characteristics of Rambi Beat Forest under Senchal East Forest Zone, Darjeeling, West Bengal, India. Its plant community were analyzed quantitatively and synthetically. The results reflect dominancy of dicotyledons over monocotyledons in the four studied sites The plant community comprising of 50 plant species belonging to 40 genera of 27 families. Ramhi beat reflected higher diversity of species. Maximum IVI value was recorded by Viola surpense (47.17) in Rambhi forest beat. The Berger parker index and evenness index were found to be highest for Viola surpense, Fragaria nubicola, Pilea umbrosa in Rambhi beat. The soil characteristics of the different pedons revealed alkaline nature of soil in Rambhi beat. Higher levels of soil organic carbon content reflect higher fertility of the soil of Rambhi beat. The response towards soil available nitrogen and phosphate were different among the ten pedons of Rambhi beat. Therefore, proper management and conservative measures needs to be implemented for conservation of bioresources in Senchel wildlife Sanctuary of West Bengal, India.

• Journal of Forest and Environmental Science
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• v.31 no.2
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• pp.73-77
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• 2015

Acquiring accurate quantitative and qualitative information is necessary for the technical and scientific management of forest stands. In this study, stratification and systematic random sampling methods were used to estimation of quantitative characteristics in study area. The estimator ($((E%)^2xT)$) was used to compare the systematic random and stratified sampling methods. 100 percent inventory was carried out in an area of 400 hectares; characteristics as: tree density, crown cover (canopy), and basal area were measured. Tree density of stands was compared through systemic random and stratified sampling methods. Findings of the study reveal that stratified sampling method gives a better representation of estimates than systematic random sampling.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.295-304
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• 2017

This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change's (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

• Journal of People, Plants, and Environment
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• v.23 no.2
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• pp.245-254
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• 2020

Patients diagnosed with cancer face mental problems such as alienation, isolation, anxiety about death and fear, recovering from psychological difficulties. In this study, a forest healing program was provided for cancer patients to recover from psychological stress, depression, social isolation and self-esteem caused by cancer and changes in salivary cortisol through psychological and emotional recovery were measured. From September 19 to November 28, 2017, a forest healing program composed of a total of 10 sessions, two hours per session was provided for 12 cancer patients in the Forest of Taegyo located in Yongin. Psychological tests were performed with Social Adaptation Self-evaluation Scale (SASS), Korean-version Perceived Stress Scale (PSS) and Beck Depression Inventory (BDI) and the collected data were analyzed with the SPSS 18.0. The salivary cortisol level was measured along with the psychological tests and were analyzed by a specialized testing agency. The results of the analysis showed that the pre- and post-assessment score of SASS was 29.17 and 25.92, respectively, and that the pre- and post-assessment score of PSS was 30.50 and 23.92, respectively. The pre- and post-assessment score of BDI was 41.00 and 34.83, respectively, which showed significant differences. In addition, the pre- and post-assessment level of saliva cortisol was 3.13 and 1.68, respectively, showing a significant decrease. In short, the forest healing program was found to be effective in reducing physiological changes caused by social isolation and stress due to the emotional and psychological difficulties that the subjects who were diagnosed with cancer and were recovering from it have. In the future, it will be necessary to develop and implement a forest healing program by conducting a forest healing requirement survey on cancer patients.

• Journal of Korean Society of Forest Science
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• v.96 no.2
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• pp.203-207
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• 2007

Restorative effect of forest settings is an emerging issue in the field of forestry. It is also the central question facing those currently engaged in the psychotherapeutic interventions is which treatments work. This study was performed to investigate the efficacy of forest experience on alcoholics' depression. Among 531 participants in forest healing camps, 47 alcoholics who participated all three sessions of the camps were selected for this study. Using pre-test and post-test group design with Beck Depression Inventory (BDI), mean changes in alcoholics' depression by completion of the camp was measured. The result of this study indicated that the 3-session of forest camp played significant role in reducing participants depression levels (i.e., positive changes in depression scores).