• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.6
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• pp.63-76
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• 2019

UAVs are unmanned, autonomous or remotely piloted aircraft. As UAVs become smaller, lighter and more economical, their applications continue to expand. Researches on UAVs in the field of remote sensing show development methods and purposes similar to those on satellite images, and they are widely used in studies such as 3D image composition and monitoring. In the field of environmental impact assessment(EIA), satellite information and data are mainly used. However, only low-resolution images covering long distances and large-scale data allowing for rough examination are being provided, so their uses are seriously limited. Therefore, in this paper, we construct spatial information of forest area by using unmanned aerial vehicle and seek efficient utilization and policy improvement in the field of environmental impact assessment. As a result, high-resolution images and data from UAVs can be used to identify the location status of SEIA, EIA, and small scale EIA project plans and to evaluate detailed environmental impact analysis. In addition, when provided together with infographics about Post-environmental impact investigation, it was confirmed that the possibility of periodic spatial information construction and evaluation can be used throughout the entire project contents and project post-process.In order to provide sophisticated infographics for the EIA, drone photography and GCP surveying methods were derived.The results of this study will be used as a basis for improving high-resolution monitoring and environmental impact assessment in the forest sector.

• Journal of the Korean Wood Science and Technology
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• v.45 no.5
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• pp.650-660
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• 2017

In this study, simplified LCA (life cycle assessment) tool was developed to increase accessibility and availability on LCA timber construction. The result of simplified LCA was compared with commercial program on LCA (Simapro.7) to verify its availability. As a result of evaluating environmental impacts with the Life Cycle Inventory of all processes, gap between LCA and simplified LCA tools of timber construction was about 1%. Therefore, the simplified LCA tool could analyse greenhouse gas emissions of timber construction and to expand number of data set through improved conveniency of users for developing database of timber construction in Korea. The reduction effects of greenhouse gas emissions of timber construction was about 53% of total emission offset up to construction phase. The results of this study would support decision making process to expand to timber construction policy to showcase environmental friendliness of timber construction. It was expected to contribute to response to the New climate regime in forestry.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.499-510
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• 2022

This study examines the reporting factors of crime against business in Korea and proposes a corresponding predictive model using machine learning. While many previous studies focused on the individual factors of theft victims, there is a lack of evidence on the reporting factors of crime against a business that serves the public good as opposed to those that protect private property. Therefore, we proposed a crime prevention model for the willingness factor of theft reporting in businesses. This study used data collected through the 2015 Commercial Crime Damage Survey conducted by the Korea Institute for Criminal Policy. It analyzed data from 834 businesses that had experienced theft during a 2016 crime investigation. The data showed a problem with unbalanced classes. To solve this problem, we jointly applied the Synthetic Minority Over Sampling Technique and the Tomek link techniques to the training data. Two prediction models were implemented. One was a statistical model using logistic regression and elastic net. The other involved a support vector machine model, tree-based machine learning models (e.g., random forest, extreme gradient boosting), and a stacking model. As a result, the features of theft price, invasion, and remedy, which are known to have significant effects on reporting theft offences, can be predicted as determinants of such offences in companies. Finally, we verified and compared the proposed predictive models using several popular metrics. Based on our evaluation of the importance of the features used in each model, we suggest a more accurate criterion for predicting var.

• Ocean and Polar Research
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• v.45 no.3
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• pp.173-183
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• 2023

The barren ground phenomenon in Korea began to occur and spread in the southern coast region and in Jeju Island in the 1980s, and since the 1990s, the damage has become serious in the east coast region as well. Korea has enacted the fisheries resource management act to manage such barren ground through the installation of sea forests among projects for the creation of fishery resources. Until now, projects related to the identification of the cause of barren ground have focused on the density of crustose coralline algae, sea urchins and seaweed, so the original cause of barren ground has not yet been identified. In order to manage barren ground, it is necessary to identify the cause of barren ground. To identify these causes, it is necessary to comprehensively consider i) studies on spatial characteristics such as rock mass distribution, slope and water depth, ii) studies on ecological and oceanographic characteristics such as water temperature, salinity, El Niño, and typhoons etc, iii) studies on organisms such as crustose coralline algae, macroalgae, and sea urchins, and iv) studies on coastal use such as living and industrial sewage inflow. Next, as with regard to legislative policy proposals , it is necessary to prepare self-management measures by the government, local governments, and fishermen as well as address management problems related to the use of sea forests by fishermen after their creation . In addition, when creating a sea forest, a management model for each resource management plan is required, and evaluation indicators and indexes that can diagnose the cause of barren ground and guidelines for barren ground measures should be developed.

• Journal of Korean Society of Forest Science
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• v.64 no.1
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• pp.64-73
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• 1984

As data basic to policy in nature conservation, the Degree of Green Naturality (DGN) survey was usually carried out. This also explains the impact of human interference to natural environment. Gongju gun and Yeongi gun were surveyed in the summer of 1983 to determine the DGN of these districts. Then, the surveyed DGN was compared to the existing standard. The results obtained appeared that the average DGN of these districts ranged about 5.1 to 5.9 and especially the ratio of DGN 7-graded area was high. Because of difficulties in applying the existing standard directly to middle part of Korea, further improvement on the existing standard for ranking or surveying the DGN should be reconsidered.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.47-56
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• 2016

This study is on the actual analysis of R&D investment effect through DEA in terms of efficiency resulted from forestry sector climate change response R&D project. Namely, it is clarifying the mechanism of the scientific, technological, social performance result and output, depending on research development cost, employment size as same input. Also, it is in-depth analysis on which performance operates more efficiently in any detailed business. With the study result, we seek political implications to enhance investment effect and core element to consider R&D business project in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.265-268
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• 2012

There are increasing number of allergic patients due to the increasing outdoor activities and allergenic pollens by local climate changes. Korea Meteorological Administration provides daily forecasts for pollen allergy warnings on the Internet. The forecast models are composed of pollen concentration models and risk grade levels. The accuracy of the models was determined in terms of risk grade. Pollen concentration models were developed using the observed data during from 2001 to 2006 and accuracy was validated against the data during from 2010 to 2011. The accuracy was different from location to location. The accuracy for most tree species was higher in April than that in May. The accuracy for weed species was higher in October than in September. Our result suggest that the models presented in this study can be used to estimate daily number and risk grade of pollens.

• The Journal of Industrial Distribution & Business
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• v.11 no.7
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• pp.29-40
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• 2020

Purpose: In modern society, many urban problems are occurring, such as aging, hollowing out old city centers and polarization within cities. In this study, we intend to apply big data and machine learning methodologies to predict depression symptoms in the elderly population early on, thus contributing to solving the problem of elderly depression. Research design, data and methodology: Machine learning techniques used random forest and analyzed the correlation between CES-D10 and other variables, which are widely used worldwide, to estimate important variables. Dependent variables were set up as two variables that distinguish normal/depression from moderate/severe depression, and a total of 106 independent variables were included, including subjective health conditions, cognitive abilities, and daily life quality surveys, as well as the objective characteristics of the elderly as well as the subjective health, health, employment, household background, income, consumption, assets, subjective expectations, and quality of life surveys. Results: Studies have shown that satisfaction with residential areas and quality of life and cognitive ability scores have important effects in classifying elderly depression, satisfaction with living quality and economic conditions, and number of outpatient care in living areas and clinics have been important variables. In addition, the results of a random forest performance evaluation, the accuracy of classification model that classify whether elderly depression or not was 86.3%, the sensitivity 79.5%, and the specificity 93.3%. And the accuracy of classification model the degree of elderly depression was 86.1%, sensitivity 93.9% and specificity 74.7%. Conclusions: In this study, the important variables of the estimated predictive model were identified using the random forest technique and the study was conducted with a focus on the predictive performance itself. Although there are limitations in research, such as the lack of clear criteria for the classification of depression levels and the failure to reflect variables other than KLoSA data, it is expected that if additional variables are secured in the future and high-performance predictive models are estimated and utilized through various machine learning techniques, it will be able to consider ways to improve the quality of life of senior citizens through early detection of depression and thus help them make public policy decisions.

• Journal of Environmental Science International
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• v.15 no.5
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• pp.461-469
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• 2006

As a frontier of Sustainable Basin Research Initiative, we commenced a scenario-driven planning and evaluation research project which is to identify the strategic policy scenarios. As a part of the project, this study attempts to estimate the ecological impacts of land cover changes using landscape indices at the whole basin level. We analyzed spatio-temporal characteristics of natural area including forest, agricultural land, water area, barren which play an important role in nature-friendly sustainable watershed management. The results of analysis shelved that the size and diversity of natural area have been reduced, while patch number and isolation have been increased in proportion to urbanization in 1974, 1995 and four future scenarios in the Ara River Basin. Also, we estimated that the natural area could be conserved to some degree in the SD or DE scenarios with a concept of environment-friendly development and lifestyle. Various strategic environment policies may be evaluated and designed on the basis of the method, that is, scenario approach and landscape ecological analysis suggested in this study.

• Journal of Environmental Impact Assessment
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• v.8 no.3
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• pp.23-34
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• 1999

The purpose of this research is to establish a green space conservation grade for sustainable urban development of Taegu metropolitan city using GIS and RS methods, together with the valuation items of green spaces centered around ecological, useful, and socio-cultural factors. The results of this study are as follows: 1. According to the ecological factor, the first grade is $81.4km^2$ and then Kachag-myun, Dong-gu in order, have needs of sustaining conservation policy of urban environment improvement and protection of the wild habitats. 2. According to the usefulness of urban parks, the first and second grade which is over 150 $persons/km^2$ in population density of the catchment areas, were Talsung park, Sinam park, Yongsan park and etc., the areas of those parks consists of 0.7% of the whole urban parks. 3. According to the socio-cultural factor, the first grade is located in urban natural parks, and the second grade is which are composed of Green Belt and agriculture in Talsung-gun. 4. Analyzing these results synthetically, the first grade conservation is 18%, as the forest in the upper zone of Mt. Palgongsan, Mt. Bisul, and Mt. Daeduck, these regions needed to preserve absolutely. This research is a basic step to show the methodology for all-round evaluation of green space using GIS and RS. Hereafter, it is necessary to consider general evaluation index of green spaces, and to consider the quantitative and qualitative aspect.