• 한국산림과학회지
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• 제113권1호
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• pp.1-13
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• 2024

본 연구는 산림복지시설과 이용객 특성 간 연관성 및 결합 양상을 파악하기 위해 「2022 산림복지 시설·공간 이용객 실태조사」 결과를 활용하여 국립자연휴양림, 국립숲체원, 국가숲길, 국립치유의숲 등 4개 시설을 대상으로 범주형 자료분석인 대응분석을 실시하였다. 교차분석 결과, 산림복지시설별 연령대, 월평균 가구소득, 교통수단, 동반유형, 정보습득 경로, 방문목적은 고도로 유의한 차이를 보였다(p<.001). 대응분석 결과를 요약하면, 숲체원과 치유의숲이 연령대, 월평균 가구소득 등 인구통계학 특성에 따라 그 외 산림복지시설과 구별된 이용 양상으로 나타났다. 그리고 숲길 이용객의 교통수단은 그 외 산림복지시설과 차이점을 보였으며, 숲체원은 공적인 성격의 단체방문 유형과 관련기관 및 시설 홈페이지 및 온라인 포털사이트로부터 정보 습득, 그리고 교육 및 학습·체험교육 프로그램 참여 목적과 연관성을 보이는 등 동반유형, 정보습득 경로, 방문목적이 그 외 산림복지시설과 구별된 양상으로 나타났다. 본 연구를 통해 산림복지시설과 이용객 특성 간 연관성과 결합 양상이 확인되었으며, 대응분석을 통해 산림복지시설 이용객 자료 활용성의 범위를 확장하였다고 판단된다.

• Journal of Forest and Environmental Science
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• 제36권2호
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• pp.122-132
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• 2020

The study examined revenue generation trend and perception of challenges facing it by forestry personnel in Akwa Ibom State, Nigeria. Data for the study was generated through primary and secondary sources. Primary sources involved the use of questionnaire which was administered to all Forest Officers and Uniformed Field Staff in all the 31 Forest Division and Headquarter in the state. Secondary sources involved collation of generated revenue from all the divisions for the study period. Data obtained were analyzed using descriptive and inferential statistics including Least square regression. The results indicated an increasing trend in forest revenue for the state statistically defined by the function y=45631x-900000000＋e (p>0.05) with a coefficient of determination of 0.7492 or 74.92%. There was also a positive correlation (r=0.866) between generated revenue and year for the 20 years under review. The mean revenue was ₦4776247.00 with the highest generated revenue (₦9823550.00) in 2014. However, majority (55.13%) of the respondents perceived revenue generation in the state to be decreasing and attributed the decline majorly to lack of mobility (16.84%) and insufficient man power (15.79%). Attitude and level of offence in the study area was perceived to be fairly cooperative (62.81%) and high (43.80%), while recruitment of more personnel (11.05%) and provision of mobility (10.03%) was considered an effective means of improving revenue generation in the state. Also, educating the people and regular patrol by forest personnel was considered as the best ways of curtailing forest offences in the area. The study recommended increased allocation of funds to the sector in addition to tackling the challenges faced by the personnel.

• Journal of Forest and Environmental Science
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• 제33권4호
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• pp.315-321
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• 2017

This study was carried out to estimate the parameters of stem taper functions, to figure out the best taper model by species, and to compare with previous studies by species, targeting on the stemmed tree samples collected from the Korean red pine (Pinus densiflora), Korean white pine (Pinus koraiensis), and Japanese larch (Larix kaempferi ) stands in Gangwon and North Gyeongsang provinces of South Korea. The seven widely used models were applied in this study, and Muhairwe 1999 model for Korean red pine and Korean white pine and Kozak 2002 model for Japanese larch were evaluated as the best model for each species according to the fit statistics and the predicted stem form comparison. In addition, the predicted diameter was suitably fitted when comparing the previous studies, and the values were more appropriate following stem taper according to neiloid, paraboloid, and cone parts by species. Consequently, the estimation of this study was considered to represent the stem taper well. When comparing stem taper of three species, the diameter was largest in Korean white pine. Overall, the taper models of this study are judged to be useful for estimating stem form and volume computation of Korean red pine, Korean white pine, and Japanese larch.

• 한국조경학회지
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• 제13권1호
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• pp.43-66
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• 1985

Korea needs proper and rational public policies on conservation and use of forest land and other natural resources because of the accelerating expansion of national land developments in recent years. Unfortunately, there is no systematic planning system to support the needs. Generally, forest land use planning needs suitability analysis based on efficient land classification system. The goal of this study was to classify a forest land using multivariate satistical methods. A case study was carried out in winter of 1983 on a mountainous area higher than 100m above sea level located at Mt. Kwanak in Anyang -city, Kyung-gi-do (province). The study area was 19.80 km$^2$wide and was divided into 1, 383 Operational Taxonomic Units (OTU's) by a 120m$\times$120m grid. Fourteen descriptors were identified and quantified for each OTU from existing national land data : elevation, slope, aspect, terrain form, geologic material, surface soil permeability, topsoil type, depth of the solum, soil acidity, forest cover type, stand size class, stand age class, stand density class, and simple forest soil capability class. For this study, a FORTRAN IV program was written for input and output map data, and the computer statistics packages, SPSS and BMD, were used to perform the multivariate statistical analysis. Fourteen variables were analyzed to investigate the characteristics of their fire quench distribution and to estimate the correlation coefficients among them. Principal component analysis was executed to find the dimensions of forest land characteristics, and factor scores were used for proper samples of OTU throughout the study area. In order to develop the classes of forest land classification based on 102 surrogates, cluster and discriminant analyses of principal descriptor variable matrix were undertaken. Results obtained through a series of multivariate statistical analyses were as follows ; 1) Principal component analysis was proved to be a useful tool for data selection and identification of principal descriptor variables which represented the characteristics of forest land and facilitated the selection of samples.

• 응용통계연구
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• 제22권1호
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• pp.221-235
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• 2009

This manuscript illustrates the comparative study between ARIMA and Exponential Smoothing modeling to develop forest fire forecasting system using different weather parameters. In this paper, authors have developed the most suitable and closest forecasting models like ARIMA and Exponential Smoothing techniques using different weather parameters. Authors have considered the extremes of the Wind speed, Radiation, Maximum Temperature and Deviation Temperature of the Summer Season form March to June month for the Ranchi Region in Jharkhand. The data is taken by own resource with the help of Automatic Weather Station. This paper consists a deep study of the effect of extreme values of the different parameters on the weather fluctuations which creates forest fires in the region. In this paper, the numerical illustration has been incorporated to support the present study. Comparative study of different suitable models also incorporated and best fitted model has been tested for these parameters.

• Journal of the Korean Data and Information Science Society
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• 제21권2호
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• pp.371-377
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• 2010

In this study, we propose two informal hypothesis tests which may be useful in determining the number of trees in a random forest for use in classification. The first test declares that a case is 'easy' if the hypothesis of the equality of probabilities of two most popular classes is rejected. The second test declares that a case is 'hard' if the hypothesis that the relative difference or the margin of victory between the probabilities of two most popular classes is greater than or equal to some small number, say 0.05, is rejected. We propose to continue generating trees until all (or all but a small fraction) of the training cases are declared easy or hard. The advantage of combining the second test along with the first test is that the number of trees required to stop becomes much smaller than the first test only, where all (or all but a small fraction) of the training cases should be declared easy.

• International Journal of Reliability and Applications
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• 제3권4호
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• pp.155-164
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• 2002

This paper focuses on how modem data mining can be integrated with real-time relational databases and commercial data warehouses to improve reliability in real-time. An important Issue for many manufacturers is the development of relational databases that link key product attributes with real-time process parameters. Helpful data for key product attributes in manufacturing may be derived from destructive reliability testing. Destructive samples are taken at periodic time intervals during manufacturing, which might create a long time-gap between key product attributes and real-time process data. A case study is briefly summarized for the medium density fiberboard (MDF) industry. MDF is a wood composite that is used extensively by the home building and furniture manufacturing industries around the world. The cost of unacceptable MDF was as large as 5% to 10% of total manufacturing costs. Prevention can result In millions of US dollars saved by using better Information systems.

• 한국산림과학회지
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• 제96권2호
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• pp.222-226
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• 2007

This study developed the Korean roundwood import prediction model using vector autoregressive (VAR) method. The roundwood was divided into softwood and hardwood by species. The VAR model of roundwood import was specified with two lagged endogenous variables, that is, roundwood import volume and roundwood import price. The results showed that the significance levels of F-statistics in the softwood and hardwood roundwood import equations rejected the hypothesis that all coefficients are zero. So, we concluded that roundwood import volume can be explained by lagged import volume and lagged import price in Korea. The coefficient signs of all variables were as expected. Also, the model has good explanatory power, and there is no autocorrelation.

• 한국자원식물학회지
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• 제27권6호
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• pp.660-670
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• 2014

The Korean plum yew (Cephalotaxus koreana Nakai) is a shade-tolerant, coniferous shrub. The seeds have been used as a folk medicine in Korea, and an alkaloid extract (HTT) is known to have anticancer properties. We estimated the genetic diversity of 429 trees in 16 populations in South Korea using 194 polymorphic amplicons from seven combinations of AFLP primer-restriction enzymes. The average number of effective alleles and the percentage of polymorphic loci were 1.37 and 79.4%, respectively. Shannon's diversity index and the expected heterozygosity were 0.344 and 0.244, respectively. We divided 16 populations into four groups on the UPGMA dendrogram and the PCA biplot. The first two principal components explained 84% of the total genetic variation. Genetic differentiation between populations explained 14% of total genetic variation, and the remaining 86% came from difference between individuals within populations, as determined by an analysis of molecular variance (AMOVA). However, the genetic differentiation did not correlate with the geographic distance between populations from the Mantel test. The Bayesian statistics, which are comparable to Wright's $F_{ST}$ and Nei's $G_{ST}$, were ${\theta}^I=0.406$ and ${\theta}^{II}=0.172$, respectively. The population genetic diversity was slightly lower, and the strength of genetic differentiation was much weaker, than the average of those plants having similar life histories, as assessed using arbitrary marker systems. We discuss strategies for the genetic conservation of the plum yew in Korea.

• 한국지형학회지
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• 제28권1호
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• pp.83-99
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• 2021

Burn severity analysis using satellite imagery has high capabilities for research and management in inaccessible areas. We extracted the forest fire area of the DMZ (Demilitarized Zone) in the western Imjin Estuary which is restricted to access due to the confrontation between South and North Korea. Then we analyzed the forest fire severity and recoverability using atmospheric corrected Surface Reflectance Level-2 data collected from Landsat-8 OLI (Operational Land Imagery) / TIRS (Thermal Infrared Sensor). Normalized Burn Ratio (NBR), differenced NBR (dNBR), and Relative dNBR (RdNBR) were analyzed based on changes in the spectral pattern of satellite images to estimate burn severity area and intensity. Also, we evaluated the recoverability after a forest fire using a land cover map which is constructed from the NBR, dNBR, and RdNBR analyzed results. The results of dNBR and RdNBR analysis for the six years (during May 30, 2014 - May 30, 2020) showed that the intensity of monthly burn severity was affected by seasonal changes after the outbreak and the intensity of annual burn severity gradually decreased after the fire events. The regrowth of vegetation was detected in most of the affected areas for three years (until May 2020) after the forest fire reoccurred in May 2017. The monthly recoverability (from April 2014 to December 2015) of forests and grass fields was increased and decreased per month depending on the vegetation growth rate of each season. In the case of annual recoverability, the growth of forest and grass field was reset caused by the recurrence of a forest fire in 2017, then gradually recovered with grass fields from 2017 to 2020. We confirmed that remote sensing was effectively applied to research of the burn severity and recoverability in the DMZ. This study would also provide implications for the management and construction statistics database of the forest fire in the DMZ.