• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.78-87
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• 2018

This study constructed a structural model and examined the fit and significance of the model to identify the influencing factors on the organizational commitment of ROTC cadets. The subjects of this study were 209 male students in grades 3 and 4 ROTC cadets of eight universities located in D, P, and G cities. Data were collected from April 13 to May 29, 2018. The data collected were analyzed by SPSS / WIN 20.0 and AMOS 21.0 programs. A positive correlation was observed between the ROTC instructor's leadership, self-efficacy, job satisfaction, and organizational commitment. Six of the six pathways of the hypothetical structural model were statistically significant. The hypothetical model showed a good fit for the data. The model fit indices were ${\chi}^2/df=1.51$, GFI=.98, AGFI=.90, NFI=0.98, NFI=.97, RMR=.02, RMSEA=.05, and TLI=.98. The ROTC Instructor's leadership and self-efficacy had direct and indirect effects on the organizational commitment. Job satisfaction had the strongest direct influence on organizational commitment. This model explained 73% of the variance in organizational commitment. Therefore, it is necessary to develop an effective education and intervention program that can enhance the ROTC instructor's leadership, self-efficacy, and job satisfaction to increase the organizational commitment of the ROTC cadets.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.39-48
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• 2011

Global warming causes the climate change and makes severe damage to ecosystem and civilization Carbon dioxide greatly contributes to global warming, thus many studies have been conducted to estimate the forest biomass carbon stock as an important carbon storage. However, more studies are required for the selection and use of technique and remotely sensed data suitable for the carbon stock estimation in Korea In this study, the aboveground forest biomass carbon stocks of Danyang-Gun in South Korea was estimated using $k$NN($k$-Nearest Neighbor) algorithm and regression model, then the results were compared. The Landsat TM and 5th NFI(National Forest Inventory) data were prepared, and ratio images, which are effective in topographic effect correction and distinction of forest biomass, were also used. Consequently, it was found that $k$NN algorithm was better than regression model to estimate the forest carbon stocks in Danyang-Gun, and there was no significant improvement in terms of accuracy for the use of ratio images.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.119-129
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• 2010

The joint use of remotely sensed data and field measurements has been widely used to estimate aboveground carbon stock in many countries. Recently, Korea Forest Research Institute has developed new carbon emission factors for kind of tree, thus more accurate estimate is possible. In this study, the aboveground carbon stock of Danyang area in South Korea was estimated using k-Nearest Neighbor(kNN) algorithm with the 5th National Forest Inventory(NFI) data. Considering the spectral response of forested area under the climate condition in Korea peninsular which has 4 distinct seasons, Landsat TM seasonal satellite images were collected. As a result, the estimated total carbon stock of Danyang area was ranged from 3542768.49tonC to 3329037.51tonC but seasonal trends were not found.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.165-169
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• 2008

This study attempts to analyze the relationship between forest volume and age based on 5th NFI data and spectral characteristics of satellite imagery using ASTER sensor in Korea. Forest stand volume and age had the negative correlation with the spectral reflectance in all of the band (Blue, Green, Red, SWIR). With increasing of stand volume and age, spectral reflectance decrease. The spectral reflectance of band1 showed the highest correlation between stand volume and spectral reflectance among the VNIR wavelength. The spectral reflectance band 1, 2 (visible wavelength) and stand age have high correlation compared to other bands. The correlation coefficients between forest volume and vegetation indices have low relationship. This result indicates that the reflectance of blue band may be important factor to improve the potential of optical remote sensing data to estimate forest volume and age.

• Journal of Environmental Impact Assessment
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• v.19 no.6
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• pp.573-581
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• 2010

Natural ecosystem is an essential part to connect with the plan for biodiversity conservation in response strategy against climate change. For connecting biodiversity conservation with climate change strategy, Europe, America, Japan, and China are making an effort to discuss protection necessity through national biodiversity valuation but precedent studies lack in Korea. In this study, we made biodiversity maps representing biodiversity distribution range using species richness in National Forest Inventory (NFI) and Forest Description data. Using regression tree algorithm, we divided various classes by decision rule and constructed biodiversity maps, which has accuracy level of over 70%. Therefore, the biodiversity maps produced in this study can be used as base information for decision makers and plan for conservation of biodiversity & continuous management. Furthermore, this study can suggest a strategy for increasing efficiency of forest information in national level.

• Journal of Distribution Science
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• v.13 no.12
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• pp.23-31
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• 2015

Purpose - The purpose of this study is to determine consumers' awareness of hygiene and the perceived risks in the service areas of coffee shops and diners, or simply coffee shops. Research design, data, and methodology - A literature review was conducted on related publications, essays, and periodicals to find correlations among the variables. We developed a research model and hypothesis, and conducted empirical research for statistical data analysis. Results - The results satisfied adequacy standards, with GFI=0.926, AGFI=0.901, RMR=0.020, NFI=0.941, X²=403.197, and p-value=0.120. The results also displayed satisfied adequacy standards for the moderating effects of shop types, with GFI=0.998 (≥0.9 desirable), AGFI=0.998 (≥0.9 desirable), RMR=0.004 (≤0.05 desirable), NFI=0.999 (≥0.9 desirable), X²=1.572, and p-value=0.814 (≥0.05 desirable). Conclusions - A higher consumer hygienic awareness results in a better brand image. Moreover, greater perceived risk results in a worse brand image. Perceived risk is a vital determinant of brand image and it deeply influences customers' decisions to visit. Therefore, perceived risk is a vital determinant of forming a brand image and must be incorporated when devising strategies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.348-357
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• 2015

The main purpose of this study is to understand the potential geographic distribution of P. koraiensis, which is known to be one of major economic tree species, based on the RCP (Representative Concentration Pathway) 8.5 scenarios and current geographic distribution from National Forest Inventory(NFI) data using ecological niche modeling. P. koraiensis abundance data extracted from NFI were utilized to estimate current geographic distribution. Also, GARP (Genetic Algorithm for Rule-set Production) model, one of the ecological niche models, was applied to estimate potential geographic distribution and to project future changes. Environmental explanatory variables showing Area Under Curve (AUC) value bigger than 0.6 were selected and constructed into the final model by running the model for each of the 27 variables. The results of the model validation which was performed based on confusion matrix statistics, showed quite high suitability. Currently P. koraiensis is distributed widely from 300m to 1,200m in altitude and from south to north as a result of national greening project in 1970s although major populations are found in elevated and northern area. The results of this study were successful in showing the current distribution of P. koraiensis and projecting their future changes. Future model for P. koraiensis suggest large areas predicted under current climate conditions may be contracted by 2090s showing dramatic habitat loss. Considering the increasing status of atmospheric $CO_2$ and air temperature in Korea, P. koraiensis seems to experience the significant decrease of potential distribution range in the future. The final model in this study may be used to identify climate change impacts on distribution of P. koraiensis in Korea, and a deeper understanding of its correlation may be helpful when planning afforestation strategies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.219-233
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• 2013

We employed the ecological niche modeling framework using GARP (Genetic Algorithm for Ruleset Production) to model the current and future geographic distribution of Pinus densiflora based on environmental predictor variable datasets such as climate data including the RCP 8.5 emission climate change scenario, geographic and topographic characteristics, soil and geological properties, and MODIS enhanced vegetation index (EVI) at 4 $km^2$ resolution. National Forest Inventory (NFI) derived occurrence and abundance records from about 4,000 survey sites across the whole country were used for response variables. The current and future potential geographic distribution of Pinus densiflora, one of the tree species dominating the present Korean forest was modeled and mapped. Future models under RCP 8.5 scenarios for Pinus densiflora suggest large areas predicted under current climate conditions may be contracted by 2090 showing range shifts northward and to higher altitudes. Area Under Curve (AUC) values of the modeled result was 0.67. Overall, the results of this study were successful in showing the current distribution of major tree species and projecting their future changes. However, there are still many possible limitations and uncertainties arising from the select of the presence-absence data and the environmental predictor variables for model input. Nevertheless, ecological niche modeling can be a useful tool for exploring and mapping the potential response of the tree species to climate change. The final models in this study may be used to identify potential distribution of the tree species based on the future climate scenarios, which can help forest managers to decide where to allocate effort in the management of forest ecosystem under climate change in 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.236-256
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• 2011

Forest carbon stocks change due to land use change is an important data required by UNFCCC(United Nations framework convention on climate change). Spatially explicit estimation of forest carbon stocks based on IPCC GPG(intergovernmental panel on climate change good practice guidance) tier 3 gives high reliability. But a current estimation which was aggregated from NFI data doesn't have detail forest carbon stocks by polygon or cell. In order to improve an estimation remote sensing and GIS have been used especially in Europe and North America. We divided research trends in main countries into 4 categories such as remote sensing, GIS, geostatistics and environmental modeling considering spatial heterogeneity. The easiest way to apply is combination NFI data with forest type map based on GIS. Considering especially complicated forest structure of Korea, geostatistics is useful to estimate local variation of forest carbon. In addition, fine scale image is good for verification of forest carbon stocks and determination of CDM site. Related domestic researches are still on initial status and forest carbon stocks are mainly estimated using k-nearest neighbor(k-NN). In order to select suitable method for forest in Korea, an applicability of diverse spatial data and algorithm must be considered. Also the comparison between methods is required.