• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.3
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• pp.209-219
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• 2013

Epidemiological models on disease spread attempt to simulate disease transmission and associated control processes and such models contribute to greater understanding of disease spatial diffusion through of individual's contacts. The objective of this study is to develop an agent-based modeling(ABM) approach that integrates geographic information systems(GIS) to simulate the spread of FMD in spatial environment. This model considered three elements: population, time and space, and assumed that the disease would be transmitted between farms via vehicle along the roads. The model is implemented using FMD outbreak data in Andong city of South Korea in 2010 as a case study. In the model, FMD is described with the mathematical model of transmission probability, the distance of the two individuals, latent period, and other parameters. The results show that the GIS-agent based model designed for this study can be easily customized to study the spread dynamics of FMD by adjusting the disease parameters. In addition, the proposed model is used to measure the effectiveness of different control strategies to intervene the FMD spread.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.137-147
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• 2013

Most of livestock houses are concentrated in certain area with mass rearing system resulting in rapid spread of infectious diseases such as HPAI (highly pathogenic avian influenza). The livestock-related vehicles which frequently travel between farms could be a major factor for disease spread by means of transmission of airborne aerosol including pathogens. This study was focused on the quantitative measurement of aerosol concentration by field experiment while vehicles were passing through the road. The TSP (total suspended particle) and PM10 (particle matter) were measured using air sampler with teflon filter installed downward the road with consideration of weather forecast and the direction of road. And aerosol spectrometer and video recorders were also used to measure the real-time distribution of aerosol concentration by its size. The results showed that PM2.5 was not considerable for transmission of airborne aerosol from the livestock-related vehicle. The mass generated from the road during the vehicle movement was measured and calculated to 241.4 ${\mu}g/m^3$ by means of the difference between TSP and PM2.5. The dispersion distance was predicted by 79.6 m from the trend curve.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.87-97
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• 2020

The livestock infections had been happened seasonally, but they have gradually changed to be irrelevant to seasons and have an aspect to rapidly spread after outbreak. Especially in Korea, proactive disinfection measures are very important because the livestock farms are located densely so high as to accelerate the spread of disease between farms. livestock disease outbreaks like HPAI and FMD occurred with high probability due to vehicles visiting the farms, this study is to evaluate the efficiency of livestock vehicle disinfection systems by investigating the disinfectant coverage according to the type of vehicle disinfection system and the type of vehicle quantitatively. In field experiments, water-sensitive papers (WSPs) were attached to 21 locations on the surface of four vehicles (sedan, SUV, truck, and feed transport), respectively, and exposed to disinfectants while the vehicle was sprayed in two vehicle disinfection systems (tunnel type and simplified type). The WSPs were scanned and image-processed to calculate the disinfectant coverage. The results showed that the tunnel-type vehicle disinfection system had a better disinfection performance with an average coverage of 90.27% for all vehicles compared to 32.62% of the simplified type system. The problem of the simplified system was a wide coefficient of variation (1.05-1.31) of the disinfectant coverage between 21 locations indicating a need for further improvement of nozzle location and arrangement.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.225-225
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• 2019

건물, 차량, 사회인프라시설과 달리 농작물이란 물리적인 시설이 아닌 농업경제 활동의 결과물로서 최종적으로 판매를 통해 수익을 창출하는 행위에서 재난으로 인하여 지장을 받게 되는 경제적 피해가 고려되어야 한다. 이를 위해 본 연구는 홍수로 인한 농작물 피해를 "생산비 매몰비용"과 "순수익 손해"를 농작물 피해추정의 척도로 하였다. 생산비 매몰비용이란 경작시작부터 피해발생까지 투입된 생산비의 회수불가에 따른 피해이며, 순수익 손해란 피해발생에 따른 기대 순수익 하락에 따른 피해를 의미한다. 다양한 작물 가운데 10종의 대표작물을 선택하고, 각 작물의 표준생산비와 표준순수익을 농업생산 및 수익과 관련한 통계자료로부터 결정하였다. 이로부터 생육경과율과 홍수 발생시기(6~9월)를 고려하여 월별 투입생산비 및 기대순수익을 결정하였다. 대상지역 내 재난에 노출된 작물정보를 정의하는 농작물 인벤토리는 농림축산식품부에서 제작된 스마트 팜 맵(농경지 전자지도)을 활용하였고, 다양한 작물이 혼재된 밭의 경우 농업면적조사 결과를 토대로 결정한 밭작물 재배현황비를 고려하였다. 홍수에 따른 취약성을 설명하는 농작물 손상함수는 영향인자는 침수심, 침수기간이며, 이를 기준으로 한 손상함수는 농림부의 농업재해피해조사요령과 일본 치수경제조사메뉴얼을 참고하여 제시하였다. 본 연구에서 제시한 농작물 피해 추정 방법은 기존 방법인 다차원 홍수피해산정법(MD-FDA)과 비교할 때 대표작물의 현실화, 국내 실정을 고려한 손상함수, 그리고 면적 기반의 원단위를 사용함으로써 실무적으로 명확하고 실용적으로 사용될 것으로 기대된다.

• Journal of Animal Environmental Science
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• v.8 no.3
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• pp.135-144
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• 2002

A computer simulation was carried out to investigate the optimum capacity of liquid manure tank spreader which is used as a tractor attachment. Soil physical properties, such as soil moisture content, bulk density, soil hardness and soil types were measured in the 10 major rice production area for computer simulation. Mathematical model which include soil physical properties and vehicle factor was used for computer simulation. Most of the soil type of the investigated area was sandy clay loam. Soil moisture content ranged between 30 and 40% mostly. Soil bulk density was in the range of 1,500 to 1,700 kg/$m^3$. Soil hardness ranged between 1 to 18 $cm^2$. Soil hardness incorporate the effects of many soil physical properties such as soil moisture content, soil type and soil bulk density, and so the range of soil hardness is greater than any other physical properties. The capacity of liquid manure tank spreader was above 3,000 kg$_{f}$ for the most of the investigated areas, and mostly in the range of 4,000 to 6,000 $kg_f$ depending upon the slip. But for the soft soil area such as Andong and Asan, the tractor itself has mobility problem and shows no pulling force for some places. For this area, the capacity of liquid manure tank spreader ranged between 1,000 and 2,000 $kg_f$ mostly, so the capacity of liquid manure tank spreader should be designed as a small capacity trailer compared to the other area.mpared to the other area.

• Korean journal of food and cookery science
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• v.23 no.5
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• pp.650-663
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• 2007

The purpose of this study was to identify the sanitation management items of school foodservice suppliers that require improvement, by assessing their sanitation practices with food commodities. Our field assessment was performed using a total of 20 vendors supplying agricultural products, meat products, seafoods and processed products; all were located in the Seoul and Gyeonggi areas. The assessment tool for sanitation management was composed of 93 checklist items and was used to evaluate seven different categories; the facility and environment, management of the facility and equipment, food materials management, process control, water management, personal hygiene management, and laboratory instrument management. A score of two was given for "satisfactory", one for "fair", and zero for "unsatisfactory". The overall average supplier score was 1.7/2.0 (85.8%). The score of the seafood vendors was highest at 1.9 (95.4%), while the lowest score of 1.3 (65.7%) occurred with the processed product suppliers. Among the sanitation management categories, water management was scored at 2.0, while inspection management was lowest at 1.4. The subcategories indicating needed improvements for the processed product suppliers were raw materials, storage, transport and recall. For the agricultural product suppliers it was preparation management. furthermore, one item within the laboratory instrument management category was unsatisfactory for both the agricultural and processed product suppliers. In conclusion, these results can be used to develop sanitation management procedures for suppliers, as well as by administration agencies to evaluate and guide those suppliers.

• Journal of Animal Environmental Science
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• v.16 no.1
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• pp.1-12
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• 2010

This survey was conducted to investigate the status and strategy of swine manure utilization of 109 swine farms in the Gyeongnam, Korea. The personal properties of owner, types of swine buildings, facilities and equipment for manure management, conditions for manure recycling and farming for recycling resources were surveyed. Age of farm owners were occupied as 44.1% for 50s followed by the 60s with one-forth and 40s with 22.9%. Educational background of farm owners, a high school graduate makes up the largest proportion of farm owners followed by a college graduation with 35.8%. The swine manure collection methods were occupied as 34.9% with totally slurry system and more than 50% slurry system with 34.9% of farms. The manure management cost per ton were occupied as more than two-third with 10,000 won~15,000 won. The cost will pay for manure management, 10,000 won~15,000 won per ton makes up the largest proportion of farm owners. Separator, loader and vehicle to collection, transportation of liquid manure were occupied as 72.5%, 44% and 10.1%, respectively. Recognition of the farming for recycling resources were occupied as 37.6%, however, 25.8% of swine farm owners don't know that. More than sixty percent of swine farms will take a recycling system according to the farming for recycling resources. Conclusively, we have a suggestion in order to promotion of the farming for recycling resources in the Gyeongnam with increasing the portion of recycling of swine manure in each county and revitalizing the marketing of the liquid and solid swine manure fertilizers.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.60-74
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• 2017

To facilitate prevention of highly pathogenic avian influenza (HPAI), a GIS is widely used for monitoring, investigating epidemics, managing HPAI-infected farms, and eradicating the disease. After the outbreak of foot-and-mouth disease in 2010 and 2011, the government of the Republic of Korea (ROK) established the GIS-based Korean Animal Health Integrated System (KAHIS) to avert livestock epidemics, including HPAI. However, the KAHIS is not sufficient for controlling HPAI outbreaks due to lack of responsibility in fieldwork, such as sterilization of HPAI-infected poultry farms and regions, control of infected animal movement, and implementation of an eradication strategy. An outbreak prediction model to support efficient HPAI control in the ROK is proposed here, constructed via analysis of HPAI outbreak patterns in the ROK. The results show that 82% of HPAI outbreaks occurred in Jeolla and Chungcheong Provinces. The density of poultry farms in these regions were $2.2{\pm}1.1/km^2$ and $4.2{\pm}5.6/km^2$, respectively. In addition, reared animal numbers ranged between 6,537 and 24,250 individuals in poultry farms located in HPAI outbreak regions. Following identification of poultry farms in HPAI outbreak regions, an HPAI outbreak prediction model was designed using factors such as the habitat range for migratory birds(HMB), freshwater system characteristics, and local road networks. Using these factors, poultry farms which reared 6,500-25,000 individuals were filtered and compared with number of farms actually affected by HPAI outbreaks in the ROK. The HPAI prediction model shows that 90.0% of the number of poultry farms and 54.8% of the locations of poultry farms overlapped between an actual HPAI outbreak poultry farms reported in 2014 and poultry farms estimated by HPAI outbreak prediction model in the present study. These results clearly show that the HPAI outbreak prediction model is applicable for estimating HPAI outbreak regions in ROK.