• Journal of The Geomorphological Association of Korea
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• v.26 no.3
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

• Journal of Environmental Impact Assessment
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• v.4 no.3
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• pp.31-39
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• 1995

Environmental Impact Assessment (EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, alternative assessment, mitigation measures, and post management. Environmental monitoring data for air quality or water quality, etc. is applied in the EIA process, especially in prediction and post management. As an effective tool of environmental monitoring, the remote sensing method, introduced recently, was used in collecting nationwide data concerning ecosystem and land use. This article explains the current monitoring status in Korea. Monitoring factors include air quality, water quality, soil, ocean, odor, noise, and ecosystems. This report explains the organization of the environmental monitoring system managed by the Ministry of Environment in Korea. Furthermore, it shows the environmental criteria and environmental policies applied to EIA in Korea.

• Journal of Wetlands Research
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• v.20 no.1
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• pp.20-26
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• 2018

The purpose of this study is to construct a GIS / DB by grasping a small but ecologically valuable village wetland distribution, and to propose conservation management and wise use plan. The study area is Seocheon-gun, a typical farming village. Firstly, based on the digital topographical map (1:5,000), the Arc-GIS tool was used to identify the provisional(draft) village wetlands. In addition, for the management of village wetlands, wetlands with an area of more or less than $625m^2$ each were derived and according to ecological regions study area was classified into urban areas, inland areas and coastal areas. And finally, according to the wetland identifying indicators, the village wetlands were identified as the final village wetlands through indoor and field trips. The results of the study show that there are 570 village wetlands in Seocheon - gun province, which are 74 in urban areas, 220 in inland areas, and 276 in coastal areas. The case study for village wetland identification was conducted in one out of two urban areas (Seocheon - eup), two of four coastal areas (Biin - myeon and Seo - myeon), and three of seven inland areas (Masan - myeon, Hansan - myeon, and Sicho - myeon). The distribution of village wetlands was found mainly to be a village wetland with an area of less than $625m^2$. In addition, compared with inland areas, the discrimination rate of village wetlands in coastal areas and urban areas was relatively low, indicating that inland areas were still less disturbed, and land use in urban areas and coastal areas is changing rapidly. Especially, land with less awareness such as village wetlands is relatively easily damaged, and management strategy is urgent.

• Journal of Korean Society of Forest Science
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• v.102 no.4
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• pp.491-498
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• 2013

Preliminary feasibility of REDD mechanism to combat forest degradation in North Korea is reviewed as a means of cooperation between South Korea and North Korea. North Korea has not established a national REDD+ strategy and a forest monitoring system which are required to implement REDD+ under the United Nations Framework Convention on Climate Change. Credible statistical data of forest resources is a necessary condition for implementing REDD mechanism in the developing countries. However, other than forest area data using satellite images, statistical data of forest resources of North Korea are mostly estimated based on simple hypothesis rather than transparent and robust results from national forest inventory. The review of statistical data of forest resources of North Korea shows that North Korea is in a pre-stage of REDD readiness. The study suggests that following research and cooperation agendas should be considered to implement REDD mechanism in North Korea: 1) detecting land use change since 2000, measuring carbon stock change, and identifying causes of deforestation and forest degradation; and 2) establishing a national REDD+ strategy' and a national forest inventory system in North Korea.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.4
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• pp.257-267
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• 2023

The grassland section of the greenhouse gas inventory has limitations due to a lack of review and verification of biomass compared to organic carbon in soil while grassland is considered one of the carbon storages in terrestrial ecosystems. Considering the situation at internal and external where the calculation of greenhouse gas inventory is being upgraded to a method with higher scientific accuracy, research on standards and methods for calculating carbon accumulation of grassland biomass is required. The purpose of this study was to identify international trends in the calculation method of the grassland biomass sector that meets the Tier 2 method and to conduct a review of variables applicable to the Republic of Korea. Identify the estimation methods and access levels for grassland biomass through the National Inventory Report in the United Nations Framework Convention on Climate Change and type the main implications derived from overseas cases. And, a field survey was conducted on 28 grasslands in the Republic of Korea to analyse the applicability of major issues. Four major international issues regarding grassland biomass were identified. 1) country-specific coefficients by land use; 2) calculations on woody plants; 3) loss and recovery due to wildfire; 4) amount of change by human activities. As a result of field surveys and analysis of activity data available domestically, it was found that there was a significant difference in the amount of carbon in biomass according to use type classification and climate zone-soil type classification. Therefore, in order to create an inventory of grassland biomass at the Tier 2 level, a policy and institutional system for making activity data should develop country-specific coefficients for climate zones and soil types.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.2
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• pp.123-135
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• 1997

An air pollutant emission inventory system for the input preparations of photochemical dispersion model was developed. Using the system, anthropogenic emissions as well as biogenic emissions in the Seoul metropolitan area were calculated. Anthropogenic emission by fuel combustion using regional cosumption data, and the laundries and so forth was estimated. The biogenic emission was estimated based upon meteorological data and the distribution of land use type in the study area. The anthropogenic emission of pollutants was highest in Seoul, and the second highest in Inchon. TSP and $SO_2$ were found large quantities during the winter due to increased consumption of heating oil. NOx and THC were emitted without seasonal variation. Among biogenic emissions, PAR was very common while NO was the least common. PAR, OLE, and ALD2 were emitted in large volumes in coniferous forest areas, while ISOP was emitted in deciduous forest areas. Generally, most biogenic emissions increased during daytime, and peaked between oen and two o'clock. Because of strong solar radiation, emission during the summer was high. Biogenic NO emissions were found to be lower compared to anthropogenic emissons, and other VOC was indicated relatively high. In the study area, among biogenic emissions PAR was found to be 3 times, OLE 8 times,and ALD2 12 times more common than among anthropogenic emissions.

• Journal of The Geomorphological Association of Korea
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• v.23 no.2
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• pp.109-125
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• 2016

This study aims to identify the landslide susceptible zones of Boeun area and provide reliable landslide susceptibility maps by applying different modeling methods. Aerial photographs and field survey on the Boeun area identified landslide inventory map that consists of 388 landslide locations. A total ofseven landslide causative factors (elevation, slope angle, slope aspect, geology, soil, forest and land-use) were extracted from the database and then converted into raster. Landslide causative factors were provided to investigate about the spatial relationship between each factor and landslide occurrence by using fuzzy set and logistic regression model. Fuzzy membership value and logistic regression coefficient were employed to determine each factor's rating for landslide susceptibility mapping. Then, the landslide susceptibility maps were compared and validated by cross validation technique. In the cross validation process, 50% of observed landslides were selected randomly by Excel and two success rate curves (SRC) were generated for each landslide susceptibility map. The result demonstrates the 84.34% and 83.29% accuracy ratio for logistic regression model and fuzzy set model respectively. It means that both models were very reliable and reasonable methods for landslide susceptibility analysis.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.27-32
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• 2022

As the need for eco-friendly transportation increases due to the deepening climate crisis, many local governments in Korea are introducing shared bicycles. Due to anxiety about public transportation after COVID-19, bicycles have firmly established themselves as the axis of daily transportation. The use of shared bicycles is spread, and the demand for bicycles is increasing by rental offices, but there are operational and management difficulties because the demand is managed under a limited budget. And unfortunately, user behavior results in a spatial imbalance of the bike inventory over time. So, in order to easily operate the maintenance of shared bicycles in Seoul, bicycles should be prepared in large quantities at a time of high demand and withdrawn at a low time. Therefore, in this study, by using machine learning, the linear regression algorithm and MS Azure ML are used to predict and analyze when demand is high. As a result of the analysis, the demand for bicycles in 2018 is on the rise compared to 2017, and the demand is lower in winter than in spring, summer, and fall. It can be judged that this linear regression-based prediction can reduce maintenance and management costs in a shared society and increase user convenience. In a further study, we will focus on shared bike routes by using GPS tracking systems. Through the data found, the route used by most people will be analyzed to derive the optimal route when installing a bicycle-only road.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.52-63
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• 2012

This study empirically investigated some problems with the criteria for subdividing the management zone in a rural area through a case study of Cheongsong-gun, Gyeongbuk and provided some suggestions for their improvement. To do this, the subdivision criteria in the guideline for developing urban management planning were firstly compared with those of Cheongsong-gun. Next, geographic information system(GIS) was used to do the cross-check analysis between the results from land suitability assessment and those from the subdivision in the management zone and to grasp the spatial relationships of a zone with its neighboring zones by analyzing the zoning inventory and comparing the areas. Finally, map analysis and field survey were conducted to examine the relevance to the actual situation of land use and focus interviews were done to analyze the civil complaint cases resulted from the subdivision in the management zone. This study found out three major categories of problems with the criteria for subdividing the management zone in Cheongsong-gun: the incomplete formalization of zoning, the inadequate decision criteria on the availability of land for development, and the biased consulting of the departments concerned. Some suggestions for their improvement were then provided in this study. The empirical results from this study can be used as the preliminary information for suggesting the right direction of the subdivision in the management zone within the rural areas in the near future.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.159-175
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• 2013

Emission reduction targets to respond to climate change have been discussed and set locally, nationally and globally. After Korean government set the national target in 2009, 16 metropolitan cities established voluntary emission reduction targets by 2020. This study review and compare historical greenhouse gas emissions, reduction target by 2020 and strategies in 16 metropolitan cities. Most cities chose a consumption-based inventory approach. Some cities set the reduction target excluding land use change and forestry (LUCF) at 30% against business-as-usual by 2020, while others set the absolute reduction target against past year including LUCF. The stringency of reduction target in metropolitan cities was evaluated differently according to the comparative indicators such as the targets against BAU or past year and per capita emission, etc. Key mitigation sectors were different across metropolitan cities. It is suggested that national government share detailed raw data for metropolitan cities' emission inventory with the local government. Using advanced mitigation model and two types' target based on BAU and historical year and integrating local government's climate change plan with its energy plan are also required.