• Journal of Forest and Environmental Science
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• v.28 no.2
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• pp.68-74
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• 2012

A total of 45 Pinus sylvestnis var. mongolica trees from 9 plots in northeast China were destructively sampled to develop aboveground prediction equations for inventory application. Sampling plots covered a range of stand ages (12-47-years-old) and densities (450-3,840/ha). The distribution of aboveground biomass of whole-trees and tree component (stems, branches and leaves) of individual trees were studied and 4 equations were developed as functions of diameter at breast height (DBH), total height (HT). All the equations have good estimation effect with high prediction precision over 90%. Forest biomass was estimated based on the individual biomass prediction equations. It was found forest biomass of all organs increased with the increasing of stand age and density. And the period of 45-50 years was the suitable harvest time for Pinus sylvesris plantation.

• Journal of Forest and Environmental Science
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• v.36 no.2
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• pp.113-121
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• 2020

This study was carried out in degraded and non-degraded community forests (CF) in the Terai region of Kanchanpur district, Nepal. A total of 63 concentric sample plots each of 500 ㎡ was laid in the inventory for estimating above and below-ground biomass of forests by using systematic random sampling with a sampling intensity of 0.5%. Mallotus philippinensis and Shorea robusta were the most dominant species in degraded and non-degraded CF accounting Importance Value Index (I.V.I) of 97.16 and 178.49, respectively. Above-ground tree biomass carbon in degraded and non-degraded community forests was 74.64±16.34 t ha^-1 and 163.12±20.23 t ha^-1, respectively. Soil carbon sequestration in degraded and non-degraded community forests was 42.55±3.10 t ha^-1 and 54.21±3.59 t ha^-1, respectively. Hence, the estimated total carbon stock was 152.68±22.95 t ha^-1 and 301.08±27.07 t ha^-1 in degraded and non-degraded community forests, respectively. It was found that the carbon sequestration in the non-degraded community forest was 1.97 times higher than in the degraded community forest. CO₂ equivalent in degraded and non-degraded community forests was 553 t ha^-1 and 1105 t ha^-1, respectively. Statistical analysis showed a significant difference between degraded and non-degraded community forests in terms of its total biomass and carbon sequestration potential (p<0.05). Studies indicate that the community forest has huge potential and can reward economic benefits from carbon trading to benefit from the REDD⁺/CDM mechanism by promoting the sustainable conservation of community forests.

• Journal of Korean Society of Forest Science
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• v.104 no.3
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• pp.427-433
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• 2015

This study was conducted to provide a method of establishing two-storied forests by the adjustment of stand structures in natural deciduous forests of Pyeongchang area. Three permanent sampling plots of 0.09 ha were established in study site and some tree variables were measured in each sampling plot before the treatment of two-storied system. Stand attributes and stand structures before treatment were estimated based on the data measured in sampling plots. The results indicate that the current stand status is different from typical stand structures of two-storied forests. A simulation technique was applied to predict stand attributes and stand structures after the treatment of two-storied system. Results suggest that significant time is required to accomplish target stand structures even after applying the treatment of two-storied system. Number of trees in the upper canopy class after treatment was predicted to be 170 trees/ha, which adequately meets the target of two-storied forests. It was predicted, however, that the lower canopy class trees has much less trees compared with the typical stand structures of two-storied forests. This problem could be solved with ingrowth of infant trees over time or by under-planting of tolerant species. It is confirmed that the target growing stock volumes of the upper canopy class should be approximately $150m^3/ha$ considering stand status after treatment. It is predicted that twenty years of conversion period is required to accomplish this goal. The changes in stand structures over time should be assessed based on stand inventory carried out every five years, and additional treatments for inducing two-storied forests should be applied if necessary.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.929-933
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• 2010

According to the IPCC guideline (2006), uncertainty assessment is very important in terms of the greenhouse gas inventory. Therefore, the purpose of this study is to estimate the basic wood density (BWD) and its uncertainty for Pinus densiflora in Korea. In this study, Pinus densiflora forests were divided into two ecotypes which were Gangwon and Jungbu regions. A total of 33 representative sampling plots was selected to collect sample trees after considering the tree ages and DBH distributions. The BWD showed statistically no difference between age classes based on IPCC's classification. While, it showed statistically difference(pvalue=0.0017) between eco-types. The BWD and uncertainty was 0.396(g/$cm^3$) and 12.9(%) for Pinus densiflora in Gangwon, while it was 0.470(g/$cm^3$) and 3.8(%) for Pinus densiflora in Jungbu. The values of the BWD uncertainty for Pinus densiflora were more precised than the values given by the IPCC guideline.

• Journal of Forest and Environmental Science
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• v.37 no.2
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• pp.104-115
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• 2021

The research attempted to analyze the medicinal plant species richness in the vertical gradient from lower to the highest elevation of Makawanpur, focusing on the relationship between species richness and elevation which is very important for conservation and management of species diversity. Inventory was carried out in the study area by taking sampling intensity of 0.5% in the effective area. Altogether, 42 sample plots were laid in the field with the help of GIS software maintaining 50 m altitude difference. High species diversity was found in the herbs species whereas shrubs have comparatively low species diversity. The maximum species richness is found in herbs and poles whereas shrubs and trees have relatively low species richness. Research showed that species richness of medicinal plants increased with altitudinal gradient. While analyzing the species richness from 350 to 2,550 m (msl), the highest species richness was received with the elevation ranges from 1,800 m to 2,300 m. There was a positive relationship between species richness and altitudinal gradient in the study area. In addition, we have recorded the high value medicinal plants after 1,800 m altitude and rarely within 1,000 m. Medicinal plants correlated both positive and negative relationships with the increased altitude. The altitudinal response has positively seen except density (n/ha) of Shrubs. Domestication and cultivation of high value medicinal plants should be promoted in community forest including private lands. Training, workshops and awareness programs should be conducted to make people aware about medicinal plants resource utilization, conservation and commercialization of available medicinal plants.

• Journal of Korean Society of Forest Science
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• v.30 no.1
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• pp.1-7
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• 1976

This study was performed in Bo-Eun Gun, Chung-Cheong Buk Do. The forest types having been classified, the each area was measured by dot-grid method. The 820 sample points having been obtained by systematic sampling method, the tree heights, crown densities, crown diameters in the points were measured on the aerial photography, and the volumes per hectare were estimated by the comparison with stereogram. Thirty eight plots, which amounted to about 4.5% of all the sample points, were sampled with double sampling method and volume were measured by the ground survey method. the results were summarized as follows; 1. There is no significant differentia between the values measure by dot-grid method and the statistical values obtained by the authority for the area. 2. There is no significant differentia between the estimated values and the measured values for the volume. And the coefficient (b) was 1.18. 3. The heights of conifer trees were easily measured more or less, but it was some difficult for the deciduous trees, because the tops of trees were not observed easily. 4. All the values had a tendencies to be overestimated in the low stocked stand and to be underestimated in the high stocked stand. 5. When the aerial volume table method by ground checking needs to be used together, the work should be performed by the experienced technician and the photgraphic volume table should be made in advanced of the work.

• Journal of agriculture & life science
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• v.43 no.6
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• pp.1-6
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• 2009

The purpose of this study was to analyze annual tree ring growth characteristics for major tree species distributed in Chungbuk province. A total of 800 sample trees from 56 permanent sampling plots measured by the 5th Korean National Forest Inventory Program in 2007 was used for the calculation of annual growth rates. According to the results of this study, the species of Robinia pseudoacacia(2.30mm/yr) showed the best annual tree ring growth rates and the others are Quercus serrata(2.27mm/yr)>Prunus sargentii(1.98mm/yr)> and Larix leptolepis(1.98mm/yr) in order. Most of the major tree species in Chungbuk province, as tree age and stand density increased, annual tree ring growth rates tended to decreased. This information could be very useful for forest managers to understand annual tree ring growth characteristics in Chungbuk province.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.181-194
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• 2017

This study aims to develop a regression model for forest volume estimation using field-collected forest inventory information and airborne LiDAR data. The response variable of the model is forest stem volume, was measured by random sampling from each individual plot of the 30 circular sample plots collected in Bonghwa-gun, Gyeong sangbuk-do, while the predictor variables for the model are Height Percentiles(HP) and Height Bin(HB), which are metrics extracted from raw LiDAR data. In order to find the most appropriate model, the candidate models are constructed from simple linear regression, quadratic polynomial regression and multiple regression analysis and the cross-validation tests were conducted for verification purposes. As a result, $R^2$ of the multiple regression models of $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}$ among the estimated models was the highest at 0.509, and the PRESS statistic of the simple linear regression model of $HP_{25}$ was the lowest at 122.352. $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}-based$ models, thus, are comparatively considered more appropriate for Korean forests with complicated vertical structures.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.