• Journal of Korean Society of Forest Science
• /
• v.110 no.4
• /
• pp.622-629
• /
• 2021

This study analyzed the running speed of logging trucks (25 tons), depending on the structural state of forest roads, on four main forest roads in the national forest management offices in Chuncheon and Hongcheon for trafficability. The speeds for the curved and straight sections were 7.6 km/h and 8.7 km/h, respectively, which were less than the designed speed (20 km/h). Thus, it would be necessary to improve the forest road's structure to fulfill minimum running speed. No significant difference was observed in the running speed by the longitudinal gradient up to 13%, while it was increased at more than 100 m by the distance in the straight section. By the facility's location in the curved section, the running speed was 6.2%-9.3% lower in a ridge than a valley. The running speed was lowest at the internal angles of <90° and at the curved radius of <15 m, respectively. When this radius was less than 15 m, the substandard sections for widening amounts were more than 50%; thus, sufficient widening was not achieved.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2016.09a
• /
• pp.41-43
• /
• 2016

• Journal of Korean Society of Forest Science
• /
• v.100 no.1
• /
• pp.70-78
• /
• 2011

In this study, we develop a fire stochastic simulation model by season based on the historical fire data in Korea. The model is utilized to generate sequences of fire events that are consistent with Korean fire history. We employ a three-stage approach. First, a random draw from a Bernoulli distribution is used to determine if any fire occurs for each day of a simulated fire season. Second, if a fire does occur, a random draw from a geometric multiplicity distribution determines their number. Last, ignition times for each fire are randomly drawn from a Poisson distribution. This specific distributional forms are chosen after analysis of Korean historical fire data. Maximum Likelihood Estimation (MLE) is used to estimate the primary parameters of the stochastic models. Fire sequences generated with the model appear to follow historical patterns with respect to diurnal distribution and total number of fires per year. We expect that the results of this study will assist a fire manager for planning fire suppression policies and suppression resource allocations.

• Journal of Korean Society of Forest Science
• /
• v.87 no.2
• /
• pp.179-187
• /
• 1998

This study was conducted to get local residents' attitudes information and management information toward tourism impacts in Black Hills of South Dakota, U.S.A. It used Importance-Performance analysis to evaluate local residents' attitudes about the impacts of tourism. A total of 184 respondent data were used in this study. The return rate was 54%. 184 out of 340 questionnaires. Most respondents expressed high positive about the local economic impacts of tourism and environment impacts of tourism had not obvious negative on them. In 23 variables of tourism impacts there were a few significant differences in certain socioeconomic characteristics of the respondents as residence length and income. The results of Importance-Performance evaluation indicated useful future management decision information.

• Journal of Ecology and Environment
• /
• v.38 no.4
• /
• pp.485-491
• /
• 2015

This study was conducted to develop stem volume models for the volume estimation of Quercus glauca Thunb. in Jeju Island, Republic of Korea. Furthermore, this study validated the developed stem volume models using an independent dataset. A total of 167 trees were measured for their diameter at breast height (DBH), total height and stem volume using non-destructive sampling methods. Eighty percent of the dataset was used for the initial model development while the remaining 20% was used for model validation. The performance of the different models was evaluated using the following fit statistics: standard error of estimate (SEE), mean bias absolute mean deviation (AMD), coefficient of determination (R²), and root mean square error (RMSE). The AMD of the five models from the different DBH classes were determined using the validation dataset. Model 5 (V = aD^bH^c), which estimates volume using DBH and total height as predicting variables, had the best SEE (0.02745), AMD (0.01538), R² (0.97603) and RMSE (0.02746). Overall, volume models with two independent variables (DBH and total height) performed better than those with only one (DBH) based on the model evaluation and validation. The models developed in this study can provide forest managers with accurate estimations for the stem volumes of Quercus glauca in the subtropical forests of Jeju Island, Korea.

• Journal of Korean Society of Forest Science
• /
• v.87 no.2
• /
• pp.286-299
• /
• 1998

This study was conducted to do a comparative analysis of hunting system in 16 OECD(Organization for Economic Co-operation and Development) countries. Hunting is one of the most advanced types for developing natural resources, esp. wildlife, which is one of major products from forest. There are two types of hunting system ; Revier and/or License System, around most countries which have traditional advanced hunting and higher hunter population. Licence system, which is chosen in Korea, is less efficient ways of hunting for maximizing economical value and wildlife management than Revier system does. Adopting better system for much more efficient economical condition from hunting in Korea in a future is a ultimate goal in this study. The first step for the goal is an analysis of these two system among 16 OECD countries ; United State, Japan, Germany, France, etc. Comparative researches in hunting regulations such as number of hunters, hunter ratio to population, hunting bags, game species, seasons, ammunition and hunting permit are a next step for adopting developed hunting system in Korea. Korea has a smallest hunter ratio to population (1/2,463) among 16 OECD centuries and economical value lead by hunting is estimated still very low. Revier system is a popular one in most OECD countries except United State, Japan, etc, which is useful for wildlife management and maximizing economical value of hunting. And usually rifles are permitted for big game hunting. Hunting examination and/or insurance are compulsory for achieving hunting permit. Depend on game species, yearly hunting bag and season are constructed in most OECD countries.

• Asia pacific journal of information systems
• /
• v.31 no.2
• /
• pp.185-196
• /
• 2021

The paper aims to analyze and predict sales of liquor in the state of Iowa by applying machine learning algorithms to models built for prediction. We have taken recourse of Azure ML and Spark ML for our predictive analysis, which is legacy machine learning (ML) systems and Big Data ML, respectively. We have worked on the Iowa liquor sales dataset comprising of records from 2012 to 2019 in 24 columns and approximately 1.8 million rows. We have concluded by comparing the models with different algorithms applied and their accuracy in predicting the sales using both Azure ML and Spark ML. We find that the Linear Regression model has the highest precision and Decision Forest Regression has the fastest computing time with the sample data set using the legacy Azure ML systems. Decision Tree Regression model in Spark ML has the highest accuracy with the quickest computing time for the entire data set using the Big Data Spark systems.

• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.3
• /
• pp.49-58
• /
• 2016

Applications of drone in various fields have been increasing in recent years. Drone has great potential for forest management. Therefore this paper is using drone for forest damage areas. Forest damage areas is divided into caused by anthropogenic and occurs naturally, the possibility of disasters, such as slope sliding, slope failures and landslides, sediment runoff exists. Therefore, this research was to utilize the drone photogrammetry to perform the damage analysis of forest damage areas. Geometrical treatment processing results in Drone Photogrammetry, the plane position error RMSE was ${\pm}0.034m$, the elevation error RMSE was ${\pm}0.017m$. The plane position error of orthophoto RMSE was ${\pm}0.083m$, the elevation error of digital elevation model RMSE was ${\pm}0.085m$. In addition, It was possible to current state analysis of damage in forest damage areas of airborne LiDAR data of before forest damage and drone photogrammetry data of after forest damage. and application of drone photogrammetry for production base data for restoration and design in forest damage areas.

• Journal of Korean Society of Forest Science
• /
• v.108 no.1
• /
• pp.127-132
• /
• 2019

This study aimed to investigate the differences in habitat environment and characteristics of small rodent populations with time elapse after thinning in Japanese larch (Larix kaempferi) plantations, Mt. Janggun, Gyeongbuk Province, South Korea. We found that there were significant differences in habitat environment, number of tree, shrub stems, coverage of overstory, midstory, rock and number of coarse woody debris (CWD) between thinned and unthinned forest stands. We captured four small rodent species. Total number of captured small rodent were higher in thinned stands. Male-to-female ratio of Apodemus agrarius, and A. peninsulae were both the highest in forest stand 3 year after thinning. The differences in number of captured and sex ratio of small rodents might be related to habitat environment between thinned and unthinned stands. Thus, thinning can provide good habitat for small rodents by developing understory vegetation and increasing CWD in Japanese larch plantations. These results suggest that forest management through maintenance of CWD and induction of midstory and understory vegetation after thinning is necessary to maintain small rodents diversity.

• Journal of Korean Society of Forest Science
• /
• v.84 no.1
• /
• pp.63-70
• /
• 1995

This paper discusses applications of neural network to stand stocking control problems. The scope of this research was to develop a neural network model for finding optimal stand management regimes and examining the performance of the model for field application. Performance was analyzed in consideration of the number of training examples and structural aspects of neural network. Research on network performance was based on extensive optimization studies for pure longleaf pine(Pinus palustris) stands. For experimental purposes. an existing nonlinear even-aged stand optimization model with a whole-stand growth and yield simulator was used to generate data samples required for the performance analysis.