• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.63-79
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• 2008

With the recent development of advanced GIS and complex spatial analysis technologies, the more sophisticated technologies are being required to support the advanced knowledge for solving geographical or spatial problems in various decision support systems. In addition, necessity for research on scientific crime investigation and forensic science is increasing particularly at law enforcement agencies and investigation institutions for efficient investigation and the prevention of crimes. There are active researches on geographic profiling to predict the base location such as criminals' residence by analyzing the spatial patterns of serial crimes. However, as previous researches on geographic profiling use simply statistical methods for spatial pattern analysis and do not apply a variety of spatial and temporal analysis technologies on serial crimes, they have the low prediction accuracy. Therefore, this paper identifies the typology the spatio-temporal patterns of serial crimes according to spatial distribution of crime sites and temporal distribution on occurrence of crimes and proposes STA-BLP(Spatio-Temporal Analysis based Base Location Prediction) algorithm which predicts the base location of serial crimes more accurately based on the patterns. STA-BLP improves the prediction accuracy by considering of the anisotropic pattern of serial crimes committed by criminals who prefer specific directions on a crime trip and the learning effect of criminals through repeated movement along the same route. In addition, it can predict base location more accurately in the serial crimes from multiple bases with the local prediction for some crime sites included in a cluster and the global prediction for all crime sites. Through a variety of experiments, we proved the superiority of the STA-BLP by comparing it with previous algorithms in terms of prediction accuracy.

• Journal of Environmental Health Sciences
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• v.46 no.4
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• pp.376-387
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• 2020

Objectives: This study is aimed at offering basic data for making plans for offensive odor management after researching offensive odor occurrence and characteristics in Gangwon Province. Methods: The data used in the study is based on offensive odor data analyzed by the Gangwon Institute of Health and Environment from 2012 to 2019. The data were reclassified by year, month, facility, and region to identify characteristics of occurrence. Finally, a distribution map of offensive odors was created using ArcGIS. Results: The highest monthly frequency of offensive odor occurrence falls in June, August, and July, and the summer season and third quarter are the highest. According to the latest eight-year data for Gangwon Province, complaints about offensive odors in county areas are more frequent than those in city areas. There are many offensive odor complaints in Wonju, Cheorwon, and Heongsung. The main offensive odor emission facilities are livestock and waste treatment (recycling) facilities. Complaints about offensive odors are relatively lower the Yeongdong area than Yeongseo area, which is considered to be the result of characteristics of land-sea breezes and geographical factors. Offensive odors from livestock facilities count for an average of 53.9% of the total, and the inadequacy rate of livestock facilities averages 36.9%. Conclusions: To maintain a clean environment in Gangwon Province, it is strongly recommended that an offensive odor reduction plan for livestock facilities be established. Areas with a high density of offensive odor occurrence should be identified and systematically managed with short- and mid-term measures. If offensive odors is managed using GIS, it is possible to identify the characteristics of occurrence by time and space and also by facility. In addition, since systematic data management is possible, it is believed that a rapid response to offensive odors, prediction of their spread, and efficient management are possible.

• Journal of Conservation Science
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• v.37 no.3
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• pp.191-208
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• 2021

In this study, the status of damage by subterranean termites and their management according to the region and type of domestic wooden cultural properties were identified. This was based on the survey reports of agencies conducting regular nationwide and regional monitoring of subterranean termites. In addition, using geographical information system (GIS) based on the survey contents, a map was constructed of termite infestation and its progress on 2,805 wooden cultural properties that were surveyed nationwide. Based on the map produced, a total of 486 cases of termite infestation were confirmed in wooden cultural properties during 2018-2019, of which 143 cases (approximately 29.4%) were confirmed to be owing to the invasion of termites in the ground and infestation of wood materials. A web platform and an application using a mapping application program interface were created to increase accessibility to the investigated damage status data. The methods employed by each institution for investigating and monitoring the invasion of termites in the ground included the use of detection dogs, visual observation, installation of wood specimens made of pine, and microwave equipment. However, it was confirmed that monitoring and survey methods were not applied to determine the territorial range of the subterranean termite colonies. Accordingly, the use of dyeing and mark-release-recapture methods were deemed necessary to understand the current status, such as calculating the scope of the target wooden cultural property, when monitoring subterranean termite colonies.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

• Asian Journal of Atmospheric Environment
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• v.12 no.3
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• pp.232-243
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• 2018

The construction, development and maintenance of an economically, environmentally and socially sustainable campus involves the integration of measuring tools and technical information that invites and encourages the community to know the actual state to generate positive actions for reducing the negative impacts over the local environment. At the Universidad Nacional de Colombia - Campus $Bogot{\acute{a}}$, a public area with daily traffic of more than 25000 people, the Environmental Management Bureau has committed with the monitoring of the noise pollution and air quality, as support to the campaigns aiming to reduce the pollutant emissions associated to the student's activities and campus operation. The target of this study is based in the implementation of mobile air quality and sonometry monitoring equipment, the mapping of the actual air quality and noise pollution inside the university campus as a novel methodology for a sub-area inside a megacity. This results and mapping are proposed as planning tool for the institution administrative sections. A mobile Kunak$^{(R)}$ Air & OPC air monitoring station with the capability to measure particulate matter $PM_{10}$, $PM_{2.5}$, Ozone ($O_3$), Sulfur Oxide ($SO_2$), Carbon Monoxide (CO) and Nitrogen Oxide ($NO_2$) as well as Temperature, Relative Humidity and Latitude and Longitude coordinates for the data georeferenciation; and a sonometer Cirrus$^{(R)}$ 162B Class 2 were used to perform the measurements. The measurements took place in conditions of academic activity and without it, with the aim of identify the impacts generated by the campus operation. Using the free code geographical information software QGIS$^{(R)}$ 2.18, the maps of each variable measured were developed, and the impacts generated by the operation of the campus were identified qualitative and quantitively. For the measured variables, an increase of around 21% for the $L_{Aeq}$ noise level and around 80% to 90% for air pollution were detected during the operation period.

• Environmental Analysis Health and Toxicology
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• v.30
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• pp.10.1-10.14
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• 2015

Recent cohort studies have relied on exposure prediction models to estimate individual-level air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study provided practical knowledge on the computation process of geographic variables in South Korea, which will improve air pollution prediction models and contribute to subsequent health analyses.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2007.10a
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• pp.169-175
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• 2007

고리, 월성, 울진, 영광 등4개 원전부지와 하나로 연구용 원자로 부지에 대해 방사성물질의 대기 중 누출사고 발생 시 대축척 전자지도와 연계한 사고정보 파악, 예상피해분석, 방재시설 및 소개정보 활용 등을 통해 중앙정부 및 지방자치단체가 방사능 물질 피해지역관리 및 신속하고 효율적인 주민대응조치 수립을 위한 의사 결정 지원할 수 있는 방사능방재 지리정보시스템 구축이 필요하다. 본 연구에서는 고리, 월성, 울진, 영광, 대전지역의 원자력 발전소 및 연구용 원자로 반경 40km이내 지역의 행정경계, 도로, 등고, 수계, 건물 등의 일반지형지물정보와, 비상계획구역 내 마을의 상세정보, 집결지, 대피소, 교통통제소, 환경방사능감시기, TLD등의 방재시설물 위치 및 관련 상세정보, 관공서, 경찰서, 소방서, 보건소, 학교, 병원 등의 방재관련 지형지물 위치 및 관련 상세정보, 원전부지 내 인구분포, 보유 차량 분포, 농작물 재배 현황, 축산물 재배현황 등의 방재관련 사회통계정보를 포함하는 공간 및 속성 데이터베이스는 구축하였다. 이를 기반으로 방사선 피폭영향 평가시스템(FADAS)의 예상평가결과를 전자지도 상에 표출하고, 이에 근거한 예상피해를 분석하며, 소개단계 대상 마을 검색 및 바람장 분석을 활용한 소개경로 제시 등을 통해 주민보호조치 의사결정을 지원하며, 사고대응 및 소개현황 정보를 관리하는 웹 기반의 원자력방재 지리정보시스템을 확대 개발하였다. 방재시설물 및 방재관련 지형지물, 방재관련 사회통계자료의 검색기능 및 실시간 원전 바람장 정보조회, 실시간 ERMS 수집정보 조회, 수치예보 정보 조회, 온라인DB관리 등의 확대 구현을 통해 사고대응조치 및 피해분석업무를 지원하였다. 본 연구를 통한 원자력방재 지리정보시스템 완성을 통해 방사능 비상시 중앙본부와 지역본부 및 유관기관 간에 지리정보와 연계한 정확한 사고정보 및 방재정보의 신속한 공유를 제공하고, 적절한 비상대응조치 의사결정 및 주민보조조치 수행을 지원하여 효율적인 사고지역 관리 및 인적 물적 자원의 피해를 최소화하는데 기여할 것으로 기대된다.

• Journal of the Korean Geographical Society
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• v.40 no.2 s.107
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• pp.153-171
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• 2005

The newly adopted Korea Geodetic Datum (a.k.a. KGD2002) calls for massive reengineering work on geospatial dataset. The main focus of our study is placed on the strategy and system implementations of the required data reengineering with a keen attention to integrated approaches to interoperability, standardization, and database utilization. Our reengineering strategy includes file-to-file, file-to-DB, DB-to-file, and DB-to-DB conversion for the coordinate transformation of KGD2002. In addition to the map formats of existing standards such as DXF and Shapefile, the newly recommended standards such as GML and SVG are also accommodated in our reengineering environment. These four types of standard format may be imported into and exported from spatial database via KGD2002 transformation component. The DB-to-DB conversion, in particular, includes not only intra-database conversion but also inter-database conversion between SDE/Oracle and Oracle Spatial. All these implementations were carried out in multiple computing environments: desktop and the Web. The feasibility test of our system shows that the coordinate differences between Bessel and GRS80 ellipsoid agree with the criteria presented in the existing researches.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.71-83
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• 2013

Recently frequencies and scales in natural disasters have been significantly increased and enlarged and that leads to increase interests on preventing disasters. As natural disasters occur, it is difficult to fulfill the scale of natural disasters using ordinary stocks in a local government. Thus, it is necessary to establish a system that commonly uses protection resources according to regional characteristics in order to rapidly implement labor mobilization and equipment distribution based on the damage of natural disasters. In this study, regional characteristics in Korea provinces are analyzed and 'a way of composing a local government consortium for common disaster responses' is proposed. First, a disaster map that represents the amount of damage for each local government published in the disaster yearbook from 2002 to 2011 is produced using GIS. Then, the whole land is divided into five different sections according to administrative regions and that are divided into 12 clusters again based on the geographical and humanistic characteristics and the analysis of the scale of damage in typhoons and heavy rainfalls. Finally, disaster protection base stations for each region are selected. The data of analyzing disaster damages may be used as a reference material for establishing disaster prevention plans.

• Journal of Environmental Health Sciences
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• v.38 no.2
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• pp.95-104
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• 2012

Objectives: The goal of this study was to investigate the relationships between proximity to an industrial complex and blood lead levels and urinary cadmium levels. Methods: We conducted a questionnaire survey and analyzed blood lead and urinary cadmium levels using Atomic Absorption Spectrometry (AAs). Data was analyzed using logistic regression analysis. All statistical analyses were conducted with SAS software version 9.2. The distance between the residence and an industrial complex was calculated through a Geographical Information System (GIS). Results: A total of 967 residents living near a large petrochemical complex in Ulsan participated. The geometric mean levels of blood lead and urinary cadmium were $1.70{\mu}g/dl$ (male: $1.77{\mu}g/dl$, female: $1.67{\mu}g/dl$), and $0.72{\mu}g/g$ creatinine (male: $0.49{\mu}g/g$ cr. female: $0.89{\mu}g/g$ cr.), respectively. Blood lead and urinary cadmium levels both increased with age and were higher among smokers compared to never smokers. Both significantly showed a decreasing trend with rising income. Results from multiple logistic regression analysis showed that urinary cadmium levels for subjects aged less than 20 years old were negatively associated with distance from the industrial area to the residence. The results, however, indicated that the blood lead levels were positively associated with the distance. Conclusions: The results of this study support that proximity to an industrial complex is related to urinary cadmium values for children. A positive finding with blood lead can be explained by the ambiguity of lead exposure sources in the general environment.