• Journal of Korean Society of Forest Science
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• v.99 no.3
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• pp.391-396
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• 2010

To analyze the characteristics of canopy fuel in Pinus densiflora stand, which is essential to assess the crown fire hazard, allometric equations for estimation of crown fuel biomass were developed by subjectively categorized crown fuel component and crown bulk density was analyzed by available fuel component categories. Ten trees were destructively sampled at Pinus densiflora stand in Mt. Palgong in Daegu and their crown fuels were weighed separately for each fuel category by size classes and by living and dead. Regression equations that estimate crown fuel load by diameter at breast height(D) or additional total height(H) were derived. The adjusted coefficient of determination values were the highest (${R^2}_{adj}$=0.835-0.996) and standard error of estimate were the lowest (SEE=0.074-0.638) in the allometric equation lnWt=${\alpha}+{\beta}lnD+{\gamma}lnH$ in average. However, in needles and small branches categories, the differences in ${R^2}_{adj}$ and SEE between equations were not significant. Crown bulk density (CBD), which was calculated by crown fuel load divided by crown volume, was 0.067 kg/$m^3$ in average when only needles were considered as available crown fuel and 0.097 kg/$m^3$ when needles and branches (0-0.5 cm diameter) were considered. The increments of CBD of needles and small branches were little even when diameter at breast height increased.

• Journal of Korean Society of Forest Science
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• v.108 no.2
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• pp.208-215
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• 2019

The goal of this study was to analyze the reactivity of a volumetric water content sensor (soil moisture sensor) and tensiometer and to review their use in the early detection of a shallow landslide. We attempted to demonstrate shallow and rapid slope collapses using three different soil ratios under artificial rainfall at 120 mm/h. Our results showed that the measured value of the volumetric water-content sensor converged to 30~37%, and that of the tensiometer reached -3~-5 kPa immediately before the collapse of the soil under all three conditions. Based on these results, we discussed a temporal range for early warnings of landslides using measurements of the volumetric water content sensors installed at the bottom of the soil slope, but could not generalize and clarify the exact timing for these early warnings. Further experiments under various conditions are needed to determine how to use both sensors for the early detection of shallow landslides.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.150-162
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• 2011

For the period between 1991 and 2009, the annual average of 448 forest fires occurred in Korea. Above all, approximately 94% of the total fires frequently occurred during the spring and fall seasons. Therefore, we need to minimize the damage of forest fire and manage them systematically. In this study, we analyzed the spatio-temporal distribution patterns for the frequency of forest fire occurrences by each city and gun during dry season between 1990s and 2000s using GIS. Then we compared to analyze the frequency of forest fire occurrence by ten-day intervals in 2000s with that in 1990s. As a result of analysis, early April showed the highest frequency of forest fire occurrence in both 1990s and 2000s. Compared to the 1990s and 2000s, the regional change of forest fire showed the most frequent fire events around Chungcheong province. Especially extra 27 fires increased in Daejeon city, and the second most frequent fire had more than 10 fires in Jeolla province and Incheon. However, the number of fire frequency decreased by 12 fires at the end of April in Hongcheon-gun(the province of Gangwon). This is the largest drop over the study period. We consider that this paper will utilize usefully to establish regional counterplan for forest fire prevention by understanding regional forest fire patterns from seasonal change.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.28 no.1
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• pp.59-65
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• 2010

The purpose of this study is to analyze the risk of the forest fire, considering the topography and the forest, for establishing disaster prevention measures of cultural heritage, Uireung, over in Cheonjang-mountain. To do that, we estimate the occurrence and spread of the forest fire over in Cheonjang-mountain through a forest fire probability model(logistic regression), using the space characteristic data($100m{\times}100m$). The factor, occurrence of the forest fire, are diameter class, southeast, southwest, south, coniferous, deciduous, and mixed forest. We assume the probability of the fire forest in each point as follow : [1+exp{-(-4.8081-(0.02453*diameter class)+(0.6608*southeast)+(0.507*southwest)+(0.7943*south)+(0.29498*coniferous forest)+(0.28897*deciduous forest)+(0.17788*mixed forest))}]$^{-1}$. To divide dangerous zone of the big forest fire, we make the basic materials for disaster prevention measures, through the map of coniferous forests, deciduous forests, and mixed forest. The damage of cultural heritage caused by a forest fire will be reduced through the effective preventive measures, by forecast a forest fire to using this study.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.301-306
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• 2020

In this study, analyzed national forest fire statistics by cause, year, region, and damage scale based on the National Fire Data System. as a result, the main cause of forest fires was the most frequent human error. forest fires occurred in areas with high population density. and it was confirmed that the Widest area of forest damage was Gang-Won province, which is rich in forestry resources. by season, it occurred a lot in spring because of the warm temperature and strong wind and low humidity. such disasters directly damage forest facilities such as house and cultural properties as well as destruction of natural resources. therefore in this study, made a suggestion plan for prevention from forest fire with forest fire prevention comprehensive plan of MFOA.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.431-440
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• 2017

The 2016 Gyeongju Earthquake ($M_L$ 5.8) (occurred on September 12, 2016) and the 2017 Pohang Earthquake ($M_L$ 5.4) (occurred on November 15, 2017) caused unprecedented damages in South Korea. It is necessary to establish basic data related to earthquake-induced mountainous sediment-related disasters over worldwide. In this study, we analyzed previous international studies on the earthquake-induced mountainous sediment-related disasters, then classified research areas according to research themes using text-mining and co-word analysis in VOSviewer program, and finally examined spatio-temporal research trends by research area. The result showed that the related-researches have been rapidly increased since 2005, which seems to be affected by recent large-scale earthquakes occurred in China, Taiwan and Japan. In addition, the research area related to mountainous sediment-related disasters induced by earthquakes was classified into four subjects: (i) mechanisms of disaster occurrence; (ii) rainfall parameters controlling disaster occurrence; (iii) prediction of potential disaster area using aerial and satellite photographs; and (iv) disaster risk mapping through the modeling of disaster occurrence. These research areas are considered to have a strong correlation with each other. On the threshold year (i.e., 2012-2013), when cumulative number of research papers was reached 50% of total research papers published since 1987, proportions per unit year of all research areas should increase. Especially, the proportion of the research areas related to prediction of potential disaster area using aerial and satellite photographs is highly increased compared to other three research areas. These trends are responsible for the rapidly increasing research papers with study sites in China, and the research papers examined in Taiwan, Japan, and the United States have also contributed to increases in all research areas. The results are could be used as basic data to present future research direction related to mountainous sediment-related disasters induced by earthquakes in South Korea.

• Journal of Forest and Environmental Science
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• v.34 no.6
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• pp.481-489
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• 2018

In this study, the succession and stand dimension attributes related to the disaster prevention function of Pinus thunbergii coastal forests were examined after damage from Diplodia tip blight. In 2015, 101 years after the Taisho eruption, field investigations were performed on the vegetation, soil thickness, and pH of surface soil of P. thunbergii coastal forests in western Sakurajima (Hakamagoshi plot) and Taisho lava flows in southeastern Sakurajima (Seto plot). The Hakamagoshi plot had more woody plant species with larger basal areas than that in the Seto plot. The mean age and height, maximal age and height of plant species, and H/D ratio were all larger in the Hakamagoshi plot than in the Seto plot. These results may be explained by the relatively smaller effect of volcanic ash and gas on forests in the Hakamagoshi plot compared to the Seto plot, resulting in a more suitable environment for many plant species. Although P. thunbergii coastal forests in Sakurajima are currently recovering from damages owing to Diplodia tip blight, there has not yet been a sufficient recovery compared to the results from a 1997 study. Furthermore, the results of assessment based on the H/D ratio and abundance of trees in P. thunbergii forests indicate that both regions are not yet effective in disaster prevention. Thus, it is necessary to establish Pinus trees, which can adjust to harsh environments like coastal areas and are resistant to volcanic ash and gas, to enhance the disaster prevention function of P. thunbergii coastal forests in volcanic regions. It may also be helpful to establish coastal forests with ectotrophic mycorrhizal fungi and organic matter coverage. Additionally, it is necessary to ensure the continuous maintenance of stand density and soil quality, and further develop efforts to prevent Diplodia tip blight and promote forest recovery.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.69-78
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• 2010

Haines index which include the rating of atmosphere instability and dryness indicated the potential of the forest fire danger. In this study, the relationships between forest fire occurrence and Haines index were analyzed. The probability of forest fire occurrence was the highest in April and HI 5, 6 and the dryness of atmosphere was higher than the atmosphere instability. Therefore, It was proved that HI affected on the forest fire occurrence and propagation.

• Journal of Korean Society of Forest Science
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• v.104 no.3
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• pp.411-420
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• 2015

This study examined methods for stand density control by using shape ratio (tree height/DBH) and its application for effective management of Pinus thunbergii coastal disaster prevention forests. We analyzed the present conditions (height, DBH, and density) of P. thunbergii coastal disaster prevention forests at 123 study sites on Jeju Island and west, south, and east coasts of South Korea and compared them with results from previous studies. The average shape ratio for P. thunbergii showed positive correlations with stand density and was significantly higher on the west coast (66.32) than on the south (49.57) and east (48.19) coasts and Jeju Island (48.29). Stands with shape ratio higher than 70 accounted for 50% of the total study sites on the west coast, indicating a decrease in their disaster prevention function compared to that of other previous studies. The stand density in most coastal areas, except the east coast, was significantly higher than the standards recommended by the Korea Forest Service and the Forestry and Forest Products Research Institute of Japan, indicating the need for stand density control. According to the growth estimation equation for P. thunbergii in the coastal area of South Korea, density control is required for young stands less than 14 years old, which show drastic increase in the shape ratio, to conserve their disaster prevention function. Particularly, the first thinning of P. thunbergii forests should be implemented before the stand age of 8 years that a shape ratio exceeds 70. For disaster-prone young stands (${\leq}20cm$ DBH) of P. thunbergii, the stand density was higher in the standard of Japan considering shape ratio than in that of Korea aiming timber production. Hence, the standard guidelines employed in Japan, which assign higher importance to disaster prevention function based on field surveys, can be applied effectively for controlling the stand density of P. thunbergii coastal forests in South Korea, to improve their disaster prevention function.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.1-7
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• 2022

In this paper, a study was conducted to predict natural disasters in Afghanistan based on machine learning. Natural disasters need to be prepared not only in Korea but also in other vulnerable countries. Every year in Afghanistan, natural disasters(snow, earthquake, drought, flood) cause property and casualties. We decided to conduct research on this phenomenon because we thought that the damage would be small if we were to prepare for it. The Azure Machine Learning Studio used in the study has the advantage of being more visible and easier to use than other Machine Learning tools. Decision Forest is a model for classifying into decision tree types. Decision forest enables intuitive analysis as a model that is easy to analyze results and presents key variables and separation criteria. Also, since it is a nonparametric model, it is free to assume (normality, independence, equal dispersion) required by the statistical model. Finally, linear/non-linear relationships can be searched considering interactions between variables. Therefore, the study used decision forest. The study found that overall accuracy was 89 percent and average accuracy was 97 percent. Although the results of the experiment showed a little high accuracy, items with low natural disaster frequency were less accurate due to lack of learning. By learning and complementing more data, overall accuracy can be improved, and damage can be reduced by predicting natural disasters.