• Journal of Climate Change Research
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• v.8 no.4
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• pp.385-391
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• 2017

This study was conducted to estimate litter carbon stock change from the National Forest Inventory (NFI) data for national greenhouse gas inventory report. Litter carbon stocks were calculated from the NFI dataset in NFI5 (2008) and NFI6 (2013) in Gangwon province. Total carbon stock change of litter was $0.68{\pm}0.71\;t\;C/ha$ from NFI5 (2008) to NFI6 (2013), however, there was no significant difference between the both dataset at 2008 and 2013 year. Litter carbon stock of coniferous stands was higher than deciduous stands in NFI5 (2008) and NFI6 (2013) (P<0.05). This study was limited to pilot study, so we will assess litter carbon stock using more complete data from NFI systems. It can be used as data sources for national greenhouse gas inventory report on forest sector.

• Korean Journal of Agricultural Science
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• v.43 no.3
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• pp.299-319
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• 2016

The National Forest Inventory (NFI) is important for providing fundamental data for basic forest planning and the establishment of forest policies for the purpose of implementing sustainable forest management. The purpose of this study is to present the development of Korea's NFI including legal basis, sampling design, and measured variables and to review the usage of NFI data. The survey methods and forestry statistics among the Unites States, Canada, Japan, China, and European countries were briefly compared. Total 140 publications utilizing NFI data between 2008 and 2015 were categorized with 15 subjects. Korea has conducted the NFI 6 times since 1971, but only the $6^{th}$ NFI is comparable with the fifth, the previous NFI, because the permanent sampling plots have been shared between the periods. The Korean Forestry Statistics contains only half as many variables as that of advanced countries in Forestry. More researches were needed to improve consistent measurement of diverse variables through implementation of advanced technologies. Additional data for Forest Health Monitoring since the NFI $6^{th}$ must be under quality control which will be an essential part of the inventories for providing the chronological change of forest health.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.233-243
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• 2021

Considering worldwide efforts to mitigate repercussions of climate change, the South Korean government has declared to reach net zero by 2050 to achieve a carbon-neutral sustainable society. For full implementation of NDCs, the government has actively reflected its forestry sector into these strategies. Since coarse woody debris (CWD) in forests represents an enduring carbon storage, it is of particular significance to determine characteristics of changes in carbon stocks of CWD by utilizing data on dead trees monitored in permanent sample plots within national forest inventories (NFIs). In this study, therefore, both occurrence and carbon stocks of CWD were estimated in such plots using data on CWD from the 5^th, 6^th, and 7^th NFIs. Subsequently, characteristics of changes in carbon stocks over time were analyzed. Based on the analysis of 2,021 plots available for monitoring in each NFI of Gangwon Province, the volume of CWD (m³ ha^-1) was found to be 4.71 in the 5^th NFI and 4.09 in the 6^th NFI. However, the volume of CWD declined to 3.09 in the 7^th NFI. Moreover, the annual carbon stocks of CWD (ton C ha^-1) were estimated to be 0.67 in 2009, 0.64 in 2014, and 0.41 in 2019, showing a downward trend over time. This study provides a basis for future research to investigate long-term changes and estimate carbon stocks of CWD in South Korea forests.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.159-164
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• 2008

Forest inventory is a commercial term meaning the preparation of detailed descriptive list of articles with number, quantity and value of each item included. Forest inventory deals with the measurement of trees and stands, the estimation of their volume, growth prediction, biomass, carbon stocks and the description tree characteristics, as well as the land upon which they are growing. National Forest Inventory Center (NFIC) in Korea conducts national forest inventory every 5 years to obtain accurate baseline data for national forest policy. The permanent sample plot data used in were collected by NFI. The objective of this study was to develop methods for quantifying forest resources at national scale based on $5^{th}$ National Forest Inventory (NFI) data in Korea. Forest land area decreased from 6.44 to 6.38 million ha between 1997 and 2007, continuing a slight downward trend in area beginning in the late 1990s. However forest resources of the Korea have continued improving in general condition and quality, as measured by increased average size and volume of trees. Growing-stock volume of the Korea increased from 17 to 123.79 cubic meter per ha between 1976 and 2007. The biomass in Korea was estimated to be 153.81 tons per hectare and carbon stocks in Korea was estimated to be 84.36 tons per hectare by NFI data. This information is important for government officials, public administration, the private business sector, and the researcher. Forest Inventory should be implemented in a way to be able to monitor and assess the forests continuously.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.71-82
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• 2023

Forest biomass is used as a representative indicator of forest size, maturity, and productivity. Therefore, quantitative evaluation is important for management and harvest as well as the evaluation of ecosystem functions and services including CO₂ absorption. The allometric equation is a widely used method for estimating the value of each component through the relative growth rate of plants. Recently, studies indicated that the relative growth of trees is changing because of the increased CO₂ concentration in the atmosphere and the resulting climate change, raising the need to review the previously developed relative growth models and coefficients. In this study, the height-diameter at breast height (DBH) relationships of four major tree species in Korea [(Pinus densiflora (PD), Larix kaempferi (LK), Quercus variabilis (QV), and Quercus mongolica (QM)] were analyzed using the 5th-7th National Forest Inventory (NFI) data. Furthermore, these results were compared with the present yield table from the National Institute for Forest Science. This analysis revealed that the expected height for the same DBH increased as the NFI progressed. For example, in model analysis, the expected heights for PD, LK, QV, and QM for DBH of 25 cm were 12.48, 19.17, 14.47, and 13.19 m, respectively, in the 5th NFI data. In the 7th NFI data, these values were estimated as 13.61 (+9.1%), 21.58 (+12.7%), 15.76 (+8.9%), and 13.93 m (+5.6%), respectively. These results indicate that the major tree species in South Korean forests currently are more vigorous in height growth than in diameter growth when compared to the height-DBH development trends by tree species identified through past survey data.

• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.402-411
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• 2018

This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.

• Research in Community and Public Health Nursing
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• v.15 no.1
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• pp.102-109
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• 2004

Purpose: The purpose of this study was to confirm a structural model for health promotion for industrial workers. Methods: Data was collected by questionnaires from 294 industrial workers at a food manufacturing factory. The data collected were analyzed through SAS 8.1 and Window LISREL 8.12a. Results: 1. The result of the test showed that the measurement of fitness was $x^2$=(삭제) 443.35, $x^2$/df 5.3415, GFI .86, AGFI .75, RMR .060, NFI .95, NNFI .93, CN 77.58, and those other than NFI and NNFI did not well fit into the practical data. 2. 15 out of 29 paths in a constructed model were statistically significant. 3. The measurements for total fitness in the modified model were $x^2$= (삭제) 146.51, $x^2$/df 1.8546, GFI .95, AGFI .91, RMR .042, NFI .98, NNFI .99, CN 223.44, all of which showed fitness in good shape to the practical data. 4. The result of the study for the modified model indicated that perceived self efficacy had the most significant direct effect on health promotion behaviors, and self esteem, perceived benefits of action, interpersonal influences, commitment to a plan of action were important factors having influences on them. Conclusion: The derived model in this study is considered appropriate in explaining and predicting health promoting behavior of industrial workers. Therefore, it can effectively be used as a reference model for further studies and suggested implication in nursing practice.

• Journal of Korean Academy of Nursing
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• v.32 no.1
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• pp.77-88
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• 2002

The purpose of this study was designed to develope and test the structural model that explains alcohol consumption behaviors among university students in Republic of Korea. The hypothetical model was constructed on the basis of the literature review and Pender's Health promotion model. Data was collected from questionnaires from 512 university students in Republic of Korea, from August to September, 2000. The reliability of instruments was adequate (Cronbach's alpha= .69-.90). Data analysis was done with SAS 6.12 for descriptive statistics and LISREL 8.13 program for covariance structural analysis. The results are as follows; 1. The overall fit of the hypothetical model to the data was moderate. Thus it was modified by male and female models. 2. The revised model has become parsimonious and had a better fit to the empirical data (male: χ2=87.21 p=.00, GFI=.97, AGFI= .94, NFI=.99, NNFI=1.0, CN=619.17, female: χ2=49.29 p=.31, GFI=.45, AGFI= .95, NFI=.99, NNFI=1.0, CN=370.02). 3. Self-efficacy was most significant factor and personality of novelty seeking, reward compensation, alcohol expectancy and drinking attitude have significant effects on male alcohol consumption behavior. 4. Personality of novelty seeking was most significant factor and personality of harm avoidance, friend influence, self-efficacies, alcohol expectancy and drinking attitude have significant effects on female alcohol consumption behavior.

• Journal of Korean Academy of Nursing
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• v.30 no.2
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• pp.366-379
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• 2000

The purpose of this study was to identify causal relationships among variables of transtheoretical model for exercise in the elderly A predictivel model explaining the stage of change was constructed based on a transtheoretical model. Empirical data for testing the hypothetical model was collected from 198 old adults over 60 years old in a community setting in Seoul, Korea in April and May,1999. Data were analyzed by descriptive statistics and correlational analysis using pc-SAS program. The Linear Structural Modeling (LISREL) 8.0 program was used to find the best fit model which predicts causal relationship of variables. The fit of the hypothetical model to the data was X2=132.85. (df=22, p=.000). GFI=.88, NNFI=.35, NFI=.77, AGFI=.59 which was not favorable but the fit of modified model to the data was X2=46.90. (df=27, p=.01).GFI= .95, NNFI=.91, NFI=.92, AGFI=.87) which was more than moderate. The predictable variables of stage of change for exercise of the Korean elderly were helping relationship, self cognitive determination, conversion of negative condition in process of change and efficacy for exercise. These variables explained 68% of stage of change for exercise of the Korean elderly.