• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.392-396
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• 2011

The purpose of this study was to develop the basic wood density (Abbreviated BWD) for Pinus densiflora and to evaluate the applicability of bootstrap simulation method. The data sets were divided into two groups based on eco-types in Korea, one from Gangwon type and the other from Jungbu type. The estimated BWDs derived from bootstrap simulation, which is one of the non-parametric statistics, were 0.418 ($g/cm^3$) in the Pinus densiflora in Gangwon while 0.464 ($g/cm^3$) in the Pinus densiflora in Jungbu. To evaluate the bootstrap simulation, the mean BWD, standard error and 95% confidence interval of probability density were estimated. The number of replication were 100, 500, 1,000, and 5,000 times that showed constant 95% confidence interval, while tended to decrease in terms of standard errors. The results of this study could be very useful to apply basic wood density values to calculate reliable carbon stocks for Pinus densiflora in Korea.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.155-158
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• 2008

Site index is the essential tool for forest management to estimate the productivity of forest land Generally, site index equation is developed and used by relationship between stand age and dominant tree heights. However, there is a limit to use the site index equation in the application of variable ages, environmental influence, and estimation of site index for unstocked land. Therefore, it was attempted to develop a new site index equations based on various environmental factors including site and topographical variables. This study was conducted to develop regional site index equations based on the relationship between site index and soil factors for Pinus densiflora. Environmental factors that obtained from GIS application, were selected by stepwise-regression. Site index Equation was estimated by multiple regression from selected factors. Four environmental factors were selected in the final site index equations by stepwise regression. It was observed that coefficients of determination for site index equations were ranged from 0.34 which seem to be relatively low but good enough for estimation of forest stand productivity. The site index equations developed in this study were also verified to be useful by three evaluation statistics such as model's estimation bias, model's precision and mean square error type of measure.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1119-1126
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• 2002

In this paper, we propose two predictive spatial data mining based on spatial statistics and apply for predicting the forest fire hazardous area. These are conditional probability and likelihood ratio methods. In these approaches, the prediction models and estimation procedures are depending un the basic quantitative relationships of spatial data sets relevant forest fire with respect to selected the past forest fire ignition areas. To make forest fire hazardous area prediction map using the two proposed methods and evaluate the performance of prediction power, we applied a FHR (Forest Fire Hazard Rate) and a PRC (Prediction Rate Curve) respectively. In comparison of the prediction power of the two proposed prediction model, the likelihood ratio method is mort powerful than conditional probability method. The proposed model for prediction of forest fire hazardous area would be helpful to increase the efficiency of forest fire management such as prevention of forest fire occurrence and effective placement of forest fire monitoring equipment and manpower.

• Journal of Environmental Impact Assessment
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• v.20 no.4
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• pp.523-538
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• 2011

This study analyzes the changes in the surface area of each forest cover, based on temperature data analysis and satellite imagery as the basic methods for the impact assessment of climate change on regional units. Furthermore, future changes in the forest cover are predicted using the double exponential smoothing method. The results of the study have shown an overall increase in annual mean temperature in the studied region since 1990, and an especially increased rate in winter and autumn compared to other seasons. The multi-temporal analysis of the changes in the forest cover using satellite images showed a large decrease of coniferous forests, and a continual increase in deciduous forests and mixed forests. Such changes are attributed to the increase in annual mean temperature of the studied regions. The analysis of changes in the surface area of each forest cover using the statistical data displayed similar tendencies as that of the forest cover categorizing results from the satellite images. Accordingly, rapid changes in forest cover following the increase of temperature in the studied regions could be expected. The results of the study of the forest cover surface using the double exponential smoothing method predict a continual decrease in coniferous forests until 2050. On the contrary, deciduous forests and mixed forests are predicted to show continually increasing tendencies. Deciduous forests have been predicted to increase the most in the future. With these results, the data on forest cover can be usefully applied as the main index for climate change. Further qualitative results are expected to be deduced from these data in the future, compared to the analyses of the relationship between tree species of forest and climate factors.

• Journal of Korean Society of Forest Science
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• v.90 no.5
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• pp.619-631
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• 2001

Since the development of a new paradigm of sustainable forest management, concerns have been focused on how the sustainability of forests will be assessed and measured objectively. This study examined the conceptual displacement on what is sustainability of forests, and analyzed the progress made by international and regional initiatives on criteria and indicators for sustainable forest management in terms of comparability and compatibility. Regarding data availability and applicability of criteria and indicators for sustainable forest management, the data reports gathered from Montreal Process member countries were analyzed. Within this context, Korean case were examined, using all possible existing information sources such as Forest Statistics, on 6 items of concepts of criteria and indicators, degree of difficulties, measurement units, data availabilities, problems and needs of future improvements for data gathering. The study also analyzed the applicability of criteria and indicators for sustainable forest management.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.329-337
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• 2017

In this study, land-use changes from 1990 to 2010 in Jeju Island by different approaches were produced and compared to suggest a more efficient approach. In a sample-based method, land-use changes were analyzed with different sampling intensities of 2 km and 4 km grids, which were distributed by the fifth National Forest Inventory (NFI5), and their uncertainty was assessed. When comparing the uncertainty for different sampling intensities, the one with the grid of 2 km provided more precise information; ranged from 6.6 to 31.3% of the relative standard error for remaining land-use categories for 20 years. On the other hand, land-cover maps by a wall-to-wall approach were produced by using time-series Landsat imageries. Forest land increased from 34,194 ha to 44,154 ha for 20 years, where about 69% of total forest land were remained as forest land and 19% and 8% within forest lands were converted to grassland and cropland, respectively. In the case of grassland, only about 40% of which were remained as grassland and most of the area were converted to forest land and cropland. When comparing land-cover area by land-use categories with land-use statistics, forest areas were underestimated while areas of cropland and grassland were overestimated. In order to analyze land use change, it is necessary to establish a clear and consistent definition on the six land use classification.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.343-351
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• 2008

By supervised learning with p predictors, we frequently obtain a prediction function of the form $y\;=\;f(x_1,...,x_p)$. When $p\;{\geq}\;3$, it is not easy to understand the inner structure of f, except for the case the function is formulated as additive. In this study, we propose to use p simple graphs for visual understanding of complex prediction functions produced by several supervised learning engines such as LOESS, neural networks, support vector machines and random forests.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.855-863
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• 2016

In this study, a simple diagnostic statistic for determining the size of random forest is proposed. This method is based on MV (margin of victory), a scaled difference in the votes at the infinite forest between the first and second most popular categories of the current random forest. We can note that if MV is negative then there is discrepancy between the current and infinite forests. More precisely, our method is based on the proportion of cases that -MV is greater than a fixed small positive number (say, 0.03). We derive an appropriate diagnostic statistic for our method and then calculate the distribution of the statistic. A simulation study is performed to compare our method with a recently proposed diagnostic statistic.

• Journal of Environmental Science International
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• v.27 no.12
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• pp.1249-1260
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• 2018

The present study aimed to examine participants' perception regarding improvements in education for their return to a mountain village, based on "satisfaction, motivation's achievement, and effectiveness." Survey was conducted with 80 participants in 2017, of which 64 valid responses were used for statistical analysis. SPSS 21.0 program was used to conduct descriptive statistics, reliability analysis, factor analysis, and multiple regression analysis. The major findings were that a higher level of "satisfaction regarding the instructor and teaching materials" resulted in a higher level of motivation's achievement of technology skills, social skills and effectiveness in interpersonal exchange. The findings also revealed that if "the content of education" were satisfactory, there was effective self development. In addition, the higher the motivation's achievement of social skill, the higher the perception in effectiveness of self development and interpersonal exchange. The study can contribute to provide baseline data for improvement of education on return of people to their mountain villages, which are collaborating with civic groups, governments, research institutions and enterprises.

• Journal of Forest and Environmental Science
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• v.34 no.6
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• pp.419-428
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• 2018

Spatial point-patterns analyses were conducted to provide insight into the ecological process behind competition and mortality in two lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands, one in the Lower Foothills, and the other in the Upper Foothills natural subregions in the boreal forest of Alberta, Canada. Spatial statistical tests were applied to live and dead trees and included Clark-Evans nearest neighbor statistic (R), nearest neighbor distribution function (G(r)), and a variant of Ripley's K function (L(r)). In both lodgepole pine plots, the results indicated that there was significant regularity in the spatial point-pattern of the surviving trees which indicates that competition has been a key driver of mortality and forest dynamics in these plots. Dead trees generally showed a clumping pattern in higher density patches. There were also significant bivariate relationships between live and dead trees, but the relationships differed by natural subregion. In the Lower Foothills plot there was significant attraction between live and dead tees which suggests mainly one-sided competition for light. In contrast, in the Upper Foothills plot, there was significant repulsion between live and dead trees which suggests two-sided competition for soil nutrients and soil moisture.