Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

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Animal Infectious Disease Preventive Zone Based on Livestock Vehicle Movement Network

축산차량 이동 네트워크에 기반한 가축 전염병 방역권역 설정

  • Lee, Gyoung-Ju (Dept. of Urban & Transportation Engineering, Korea National University of Transportation) ;
  • Pak, Son-Il (College of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University) ;
  • Lee, Kwang-Nyeong (Veterinary Epidemiology Division, Animal and Plant Quarantine Agency) ;
  • Park, Jin-Ho (Dept. of Urban & Transportation Engineering, Korea National University of Transportation) ;
  • Hong, Sungjo (Dept. of Urban Engineering, Chungbuk National University)
  • 이경주 (한국교통대학교 도시.교통공학전공) ;
  • 박선일 (강원대학교 수의과대학) ;
  • 이광녕 (농림축산검역본부 역학조사과) ;
  • 박진호 (한국교통대학교 도시.교통공학전공) ;
  • 홍성조 (충북대학교 도시공학과)
  • Received : 2018.09.11
  • Accepted : 2019.01.04
  • Published : 2019.01.31
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Abstract

The purpose of this study is to derive spatial area(preventive zone) where the movement of livestock vehicles occurs frequently. For this purpose, this study used 6 periods facility entrance data provided by KAHIS. This data was converted into vehicle movement data between livestock facilities and aggregated into administrative district units. The R-mode factor analysis was performed on the constructed OD data, and the region extracted by the same factor was judged as one region. The results of the analysis are summarized as follows. First, the factor analysis of 6 periods data showed 16 ~ 18 factors, and the derived factors explained 63 ~ 68% of the total variance. Second, based on the factors that were derived, Jeonam coastal area, Jeonnam area, Jeonbuk area, Chungnam coastal area, Gyeongnam area, northern Gyeongbuk area, Yeongnam costal area were found to be stable, with little change over time. On the other hand, Chungbuk area, Gangwon area, Seoul metropolitan area are relatively volatile areas. Third, 13 areas were derived by combining data from six periods.

본 연구의 목적은 축산차량의 이동이 빈번하게 일어나는 공간적 범위(방역권역)를 도출하는 것을 목적으로 한다. 이를 위하여 본 연구는 KAHIS에서 제공하는 축산차량의 시설 진입자료 중에서 6개 시점의 자료를 활용하였다. 이 자료를 축산시설간의 차량이동자료로 변환하고, 이를 행정구역단위로 취합하여 행정구역간의 OD자료를 구축하였다. 구축된 OD 자료를 활용한 R-mode 요인분석을 실시하여 동일요인으로 추출된 지역을 하나의 권역으로 판단하였다. 분석결과를 정리하면 다음과 같다. 첫째, 6개 시점 자료의 요인분석을 실시한 결과 16개~18개의 요인이 도출되었으며, 도출된 요인은 전체 분산의 63~68%를 설명하였다. 두 번째, 도출된 요인을 바탕으로 지역을 구분한 결과, 전남남해안지역, 전남지역, 전북지역, 충남서해안지역, 경남지역, 경북북부지역, 영남동해안지역은 시점에 따른 변화가 적은 안정적인 지역으로 나타났다. 반면, 충북지역, 강원도지역, 수도권지역은 상대적으로 변화가 큰 지역이다. 세 번째, 6개 시점의 자료를 종합하여 강원권역, 경기남부권역, 경기북부권역, 경남권역, 경북남부권역, 경북북부권역, 남해안권역, 대전권역, 동해안권역, 전남권역, 전북권역, 충남권역, 충북권역의 13개 권역을 도출하였다.

Keywords

SHGSCZ_2019_v20n1_189_f0001.png 이미지

Fig. 1. R-mode & Q-mode Factor analysis (a) R-mode (b) Q-mode

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Fig. 2. Scree Test Plot

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Fig. 3. Classification of Zone (2013 winter)

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Fig. 4. Classification of Zone (2014 summer)

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Fig. 5. Classification of Zone (2014 winter)

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Fig. 6. Classification of Zone (2015 summer)

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Fig. 9. Gangwon Zone

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Fig. 10. Southern Gyeonggi Zone

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Fig. 11. Northern Gyeonggi Zone

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Fig. 7. Classification of Zone (2015 winter)

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Fig. 8. Classification of Zone (2016 summer)

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Fig. 12. Gyeongnam Zone

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Fig. 13. Southern Gyeongbuk Zone

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Fig. 14. Northern Gyeongbuk Zone

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Fig. 15. Namhaean Zone

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Fig. 16. Daejeon Zone

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Fig. 17. Donghaean Zone

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Fig. 18. Jeonnam Zone

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Fig. 19. Jeonbuk Zone

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Fig. 20. Chungnam Zone

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Fig. 21. Chungbuk Zone

Table 1. Data Set Used for Analysis

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Table 2. Result of Factor Analysis

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Table 3. Animal Infectious Disease Preventive Zone

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