• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.1-12
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• 1999

This study aims to find basic data for using the quantitative assessment of the sustainability and establishing the systematic index of the planning for local cities to consider the environmentally sound and sustainable development. The research designs to review professional responding to surveys preceded by separate questionnaires and interviews from book reviews, and suggests to make an assessment model of the sustainability for local cities. The research found consequently as follows. Firstly, the research survey items were decides totally 52, grouped 9 assessmental issues and distributed under 4 assessmental domains for the sustainability from the references of book reviews. Secondly, the research result concentrated on the followings from the professional responding to surveys. 1. A most influent factor is the distribution of animals and plants in a nature domain. The next influent factors are the ratio of mass-transportation systems, the numbers of the species of animals and plants, the acreage of conservative forestry, the numbers of reused water resources, and the usage number of water supply, orderly in the nature domain. 2. A most influent factor is the usage number of synthetic detergents in a pollution domain. The next influent factors are the volume of waste water, the number of registered vehicles, the degree of soil pollution, and the charge of development imposition, orderly in the pollution domain. 3. A most influent factor is the acreage of athletic facilities, in an urban domain. the next influent factors are the acreage of recreational facilities, the number and acreage of cultural assets, the number of cultural facilities, the acreage of landscape conservation area, the charge of cultural asset management, orderly in the urban domain. 4. A most influent factor is the number of waste disposal facilities in a participation domain. The next influent factors are the capacity of reused waste, the usage of synthetic detergents, the ratio of waste water disposal, orderly in the participation domain. 5. A most contributed influent domain to the assessment of the sustainability for local cities is the urban domain. The next influent domains are nature domain, participation domain, and pollution domain, orderly in the contribution of the assessment of the sustainability. But, the pollution domain is little relationship with the sustainability. Therefore, it is clear that the abundant greens and the improved level of culture are dominant influences on the sustainabiligy, as like improving the ratio of roadside trees, the acreage of parks, and enlarging the number of cultural facilities.

• Spatial Information Research
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• v.16 no.1
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• pp.19-32
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• 2008

Usually in South Korea, land cover type and topographic undulation are frequently changed even in a narrow area. However, most of researches using aerial LIDAR(LIght Detection And Ranging) data in abroad had been acquired in the study areas to be changed infrequently. This research was performed to explore reconstruction methodologies of 3D surface models considering the distribution of land cover type and topographic undulation. Composed of variously undulatory forests, rocky river beds and man-made land cover such as streets, trees, buildings, parking lots and so on, an area was selected for the research. First of all, the area was divided into three zones based on land cover type and topographic undulation using its aerial ortho-photo. Then, aerial LIDAR data was clipped by each zone and different 3D modeling processes were applied to each clipped data before integration of each models and reconstruction of overall model. These kinds of processes might be effectively applied to landscape management, forest inventory and digital map composition. Besides, they would be useful to resolve less- or over-extracted problems caused by simple rectangle zoning when an usual data processing of aerial LIDAR.

• Journal of Korean Society of Forest Science
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• v.103 no.1
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• pp.105-112
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• 2014

The main purpose of this study is to measure spatio-temporal variation of forest tree volume based on the RCP(Representative Concentration Pathway) 8.5 scenario, targeting on Pinus densiflora forests which is the main tree species in South Korea. To estimate nationwide scale, $5^{th}$ forest type map and National Forest Inventory data were used. Also, to reflect the impact of change in place and climate on growth of forest trees, growth model reflecting the climate and topography features were applied. The result of the model validation, which compared the result of the model with the forest statistics of different cities and provinces, showed a high suitability. Considering the continuous climate change, volume of Pinus densiflora forest is predicted to increase from $131m^3/ha$ at present to $212.42m^3/ha$ in the year of 2050. If the climate maintains as the present, volume is predicted to increase to $221.92m^3/ha$. With the climate change, it is predicted that most of the region, except for some of the alpine region, will have a decrease in growth rate of Pinus densiflora forest. The growth rate of Pinus densiflora forest will have a greater decline, especially in the coastal area and the southern area. With the result of this study, it will be possible to quantify the effect of climate change on the growth of Pinus densiflora forest according to spatio-temporal is possible. The result of the study can be useful in establishing the forest management practices, considering the adaptation of climate change.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.415-424
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• 2017

This study was conducted to estimate carbon stocks of Pinus densiflora with drawing volume of trees in each tree height and DBH applying the suitable stem taper equation and tree specific carbon emission factors, using collected growth data from all over the country. Information on distribution area, tree age, tree number per hectare, tree volume and volume stocks were obtained from the $5^{th}$ National Forest Inventory (2006~2010) and Statistical yearbook of forest (2016), and method provided in IPCC GPG was applied to estimate carbon stock and uptake. Performance in predicting stem diameter at a specific point along a stem in Pinus densiflora by applying Kozak's model, $d=a_{1}DBH^{a_2}a_3^{DBH}X^{b_{1}Z^2+b_2ln(Z+0.001)+b_3\sqrt{Z}+b_4e^z+b_5(\frac{DBH}{H})}$, which is well known equation in stem taper estimation, was evaluated with validations statistics, Fitness Index, Bias and Standard Error of Bias. Consequently, Kozak's model turned out to be suitable in all validations statistics. Stem volume table of P. densiflora was derived by applying Kozak's model and carbon stock tables in each tree height and DBH were developed with country-specific carbon emission factors ($WD=0.445t/m^3$, BEF = 1.445, R = 0.255) of P. densiflora. As the results of analysis in carbon uptake for each province, the values were high with Gangwon-do $9.4tCO_2/ha/yr$, Gyeongsandnam-do and Gyeonggi-do $8.7tCO_2/ha/yr$, Chungcheongnam-do $7.9tCO_2/ha/yr$ and Gyeongsangbuk-do $7.8tCO_2/ha/yr$ in order, and Jeju-do was the lowest with $6.8tC/ha/yr$. Total carbon stocks of P. densiflora were 127,677 thousands tC which is 25.5% compared with total percentage of forest and carbon stock per hectare (ha) was $84.5tC/ha/yr$ and $7.8tCO_2/ha/yr$, respectively.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.5
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• pp.27-43
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• 2019

This study applied the LANDIS-II model to the forest vegetation of the study area in Yeongdong-gun, Korea to identify climate effects on ecosystems of forest vegetation. The main purpose of the study is to examine the long-term changes in forest aboveground biomass(AGB) under three different climate change scenarios; The baseline climate scenario is to maintain the current climate condition; the RCP 4.5 scenario is a stabilization scenario to employ of technologies and strategies for reducing greenhouse gas emissions; the RCP 8.5 scenario is increasing greenhouse gas emissions over time representative with 936ppm of $CO_2$ concentration by 2100. The vegetation survey and tree-ring analysis were conducted to work out the initial vegetation maps and data for operation of the LANDIS model. Six types of forest vegetation communities were found including Quercus mongolica - Pinus densiflora community, Quercus mongolica community, Pinus densiflora community, Quercus variabilis-Quercus acutissima community, Larix leptolepis afforestation and Pinus koraiensis afforestation. As for changes in total AGB under three climate change scenarios, it was found that RCP 4.5 scenario featured the highest rate of increase in AGB whereas RCP 8.5 scenario yielded the lowest rate of increase. These results suggest that moderately elevated temperatures and $CO_2$ concentrations helped the biomass flourish as photosynthesis and water use efficiency increased, but huge increase in temperature ($above+4.0^{\circ}C$) has resulted in the increased respiration with increasing temperature. Consequently, Species productivity(Biomass) of trees decrease as the temperature is elevated drastically. It has been confirmed that the dominant species in all scenarios was Quercus mongolica. Like the trends shown in the changes of total AGB, it revealed the biggest increase in the AGB of Quercus mongolica under the RCP 4.5 scenario. AGB of Quercus mongolica and Quercus variabilis decreased in the RCP 4.5 and RCP 8.5 scenarios after 2050 but have much higher growth rates of the AGB starting from 2050 under the baseline scenario. Under all scenarios, the AGB of coniferous species was eventually perished in 2100. In particular they were extinguished in early stages of the RCP 4.5 and RCP 8.5 scenarios. This is because of natural selection of communities by successions and the failure to adapt to climate change. The results of the study could be expected to be effectively utilized to predict changes of the forest ecosystems due to climate change and to be used as basic data for establishing strategies for adaptation climate changes and the management plans for forest vegetation restoration in ecological restoration fields.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.46-54
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• 2021

This study compared and analyzed the effects of forest tending works on the vertical distribution of wildfire fuel loads on Pinus densiflora stands in Gyeongbuk province. The study sites were located in Youngju and Bonghwa in Pinus densiflora stands. A total of 10 sample trees were collected for the development of the crown fuel vertical distribution model. The 6th NFI (National Forest Inventory) selected a sample point that only extracted from managed and unmanaged stands of Pinus densiflora in the Gyeongbuk province. The fitness index (F.I.) of the two models developed was 0.984 to 0.989, with the estimated parameter showing statistical significance (P<0.05). A s a results, the vertical distribution of wildfire fuel loads range of unmanaged stands was from 1m to 11m with the largest distribution at point 5m at the tree height. On the other hand, the vertical distribution of wildfire fuel loads range of the managed stands was from 1m to 15m with the largest distribution at the point of 8m at the tree height. The canopy bulk density was 0.16kg/㎥ for the managed stands and 0.25kg/㎥ for the unmanaged stands, unmanaged stands were about 1.6 times more than managed stands. This result is expected to be available for simulation through the implementation of the 3D model as crown fuel was analyzed in three dimensions.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.65-77
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• 2022

Due to the recent development in electronic financial services, transactions of electronic prepayment are rapidly growing, leading to growing fraud attempts. This paper proposes a methodology that can effectively detect fraud transactions in electronic prepayment by machine learning algorithms, including support vector machines, decision trees, and artificial neural networks. Actual transaction data of electronic prepayment services were collected and preprocessed to extract the most relevant variables from raw data. Two different approaches were explored in the paper. One is a transaction-based approach, and the other is a user ID-based approach. For the transaction-based approach, the first model is primarily based on raw data features, while the second model uses extra features in addition to the first model. The user ID-based approach also used feature engineering to extract and transform the most relevant features. Overall, the user ID-based approach showed a better performance than the transaction-based approach, where the artificial neural networks showed the best performance. The proposed method could be used to reduce the damage caused by financial accidents by detecting and blocking fraud attempts.

• Korean Journal of Environment and Ecology
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• v.37 no.5
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• pp.337-346
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• 2023

Although wildlife bridge are built as a way to reduce habitat fragmentation caused by road construction, there is still a lot of debate about their effectiveness. Monitoring methods such as footprint traps and camera traps are used evaluate the effectiveness of wildlife bridge, but there is a limit to evaluate of effectiveness. In this study, the degree of use the wildlfe bridge was surveyed by striped field mouse that is likely use the wildlife bridge and surrounding as a habitat with capture-mark-recapture method.(Apodemus agraius). The distance and route of movement were identified by connecting the capture points, and the environmental factors on the use of the wildlife bridge implemented a generalized linear model(GLM) with the capture number of captured as a dependent variable. Consequently of capture, no individuals crossing the wildlife bridge, striped field mouse use the wildlife bridge as a habitat.The environmental factors affecting the use of mice were vegetation cover(1~2m, 2~8m, over 8m), vegetation construction, maximum diameter at breast height were positively correlated and slope was nagatively correlated. In conclusion, it is expected that the effectiveness of the wildlife bridge will be further improved by planting shrubs and trees and preventing high slope and cut slope increasing the utilization of the rat, such as being used as a food source in the ecosystem.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.208-217
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• 2023

Accurate estimation of dormancy breaking and first bloom dates is crucial for effective fire blight control by disease model such as Maryblyt in apple orchards. The duration from dormancy breaking to first bloom in apple trees was influenced by daily minimum temperatures during the dormant period. The purpose of this study is to investigate the relationship between minimum temperatures during this period and the time taken for flowering to commence. Webcam data from eight apple orchards, equipped by the National Institute of Horticultural and Herbal Science, were observed from 2019 to 2023 to determine the dates of starting bloom (B1). Additionally, the dormancy breaking dates for these eight sites were estimated using an apple chill day model, with a value of -100.5 DD, based on collected weather data. Two regressions were performed to analyze the relationships: the first regression between the number of days under 0℃ (X₁) and the time from calculated dormancy breaking to observed first bloom (Y), resulting in Y = 0.87 × X₁ + 40.76 with R² = 0.84. The second regression examined the starting date of breaking dormancy (X₂) and the duration from dormancy breaking to observed first bloom (Y), resulting in Y = -1.07 × X₂ + 143.62 with R² = 0.92. These findings suggest that apple anti-chill days are significantly affected by minimum temperatures during the period from dormancy breaking to flowering, indicating their importance in fire blight control measures.

• Journal of Korean Society of Forest Science
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• v.83 no.2
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• pp.175-190
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• 1994

In order to get fundamental information for prediction of landslide hazard, both forest and site factors affecting slope stability were investigated in many areas of active landslides. Twelve descriptors were identified and quantified to develop the prediction model by multivariate statistical analysis. The main results obtained could be summarized as follows : The main factors influencing a large scale of landslide were shown in order of precipitation, age group of forest trees, altitude, soil texture, slope gradient, position of slope, vegetation, stream order, vertical slope, bed rock, soil depth and aspect. According to partial correlation coefficient, it was shown in order of age group of forest trees, precipitation, soil texture, bed rock, slope gradient, position of slope, altitude, vertical slope, stream order, vegetation, soil depth and aspect. The main factors influencing a landslide occurrence were shown in order of age group of forest trees, altitude, soil texture, slope gradient, precipitation, vertical slope, stream order, bed rock and soil depth. Two prediction models were developed by magnitude and frequency of landslide. Particularly, a prediction method by magnitude of landslide was changed the score for the convenience of use. If the total store of the various factors mark over 9.1636, it is evaluated as a very dangerous area. The mean score of landslide and non-landslide group was 0.1977 and -0.1977, and variance was 0.1100 and 0.1250, respectively. The boundary value between the two groups related to slope stability was -0.02, and its predicted rate of discrimination was 73%. In the score range of the degree of landslide hazard based on the boundary value of discrimination, class A was 0.3132 over, class B was 0.3132 to -0.1050, class C was -0.1050 to -0.4196, class D was -0.4195 below. The rank of landslide hazard could be divided into classes A, B, C and D by the boundary value. In the number of slope, class A was 68, class B was 115, class C was 65, and class D was 52. The rate of landslide occurrence in class A and class B was shown at the hige prediction of 83%. Therefore, dangerous areas selected by the prediction method of landslide could be mapped for land-use planning and criterion of disaster district. And also, it could be applied to an administration index for disaster prevention.