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      석면노출연구를 위한 공간분석기법 = Spatial Analysis Methods for Asbestos Exposure Research

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      https://www.riss.kr/link?id=A103754485

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      다국어 초록 (Multilingual Abstract)

      Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of experience of authors were conducted to know academic background of spatial analysis, appling methods on epidemiology and asbestos exposure. Results: Spatial analysis based on spatial autocorrelation provides a variety of methods through which to conduct mapping, cluster analysis, diffusion, interpolation, and identification. Cause of disease occurrence can be investigated through spatial analysis. Appropriate methods can be applied according to contagiousness and continuity. Spatial analysis for asbestos exposure source is needed to study asbestos related diseases. Although a great amount of research has used spatial analysis to study exposure assessment and distribution of disease occurrence, these studies tend to focus on the construction of a thematic map without different forms of analysis. Recently, spatial analysis has been advanced by merging with web tools, mobile computing, statistical packages, social network analysis, and big data. Conclusions: Because the trend in spatial analysis has evolved from simple marking into a variety of forms of analyses, environmental researchers including asbestos exposure study are required to be aware of recent trends.
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      Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of...

      Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of experience of authors were conducted to know academic background of spatial analysis, appling methods on epidemiology and asbestos exposure. Results: Spatial analysis based on spatial autocorrelation provides a variety of methods through which to conduct mapping, cluster analysis, diffusion, interpolation, and identification. Cause of disease occurrence can be investigated through spatial analysis. Appropriate methods can be applied according to contagiousness and continuity. Spatial analysis for asbestos exposure source is needed to study asbestos related diseases. Although a great amount of research has used spatial analysis to study exposure assessment and distribution of disease occurrence, these studies tend to focus on the construction of a thematic map without different forms of analysis. Recently, spatial analysis has been advanced by merging with web tools, mobile computing, statistical packages, social network analysis, and big data. Conclusions: Because the trend in spatial analysis has evolved from simple marking into a variety of forms of analyses, environmental researchers including asbestos exposure study are required to be aware of recent trends.

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      참고문헌 (Reference)

      1 강동묵, "환경성 석면노출의 건강영향" 한국환경보건학회 35 (35): 71-77, 2009

      2 한대권, "공간역학과 환경보건: 공간위치정보 활용에 대한 고찰" 한국환경보건학회 37 (37): 1-11, 2011

      3 Gesler W, "The uses of spatial analysis in medical geography" 23 : 963-973, 1986

      4 Yoo EH., "The study of spatal statistical analysis in GIS environment" Seoul National University 1999

      5 Anselin L, "Spatial statistical analysis and geographical information systems" 26 : 19-33, 1992

      6 Petja BM, "Spatial epidemiology risk assessment for rehabilitated former asbestos mining areas in Limpopo Province, South Africa, using remote sensing and conventional analytical methods" 25 (25): 32-39, 2010

      7 Morrill R, "Spatial diffusion" Sage Publications 86-, 1988

      8 Pfeiffer DU, "Spatial Analysis in Epidemiology" Oxford University Press 3-, 2008

      9 Anselin L, "Spatial Analyses of Crime" 4 : 213-262, 2000

      10 Pan XL, "Residential Proximity to Naturally Occurring Asbestos and Mesothelioma Risk in California" 172 : 1019-1025, 2005

      1 강동묵, "환경성 석면노출의 건강영향" 한국환경보건학회 35 (35): 71-77, 2009

      2 한대권, "공간역학과 환경보건: 공간위치정보 활용에 대한 고찰" 한국환경보건학회 37 (37): 1-11, 2011

      3 Gesler W, "The uses of spatial analysis in medical geography" 23 : 963-973, 1986

      4 Yoo EH., "The study of spatal statistical analysis in GIS environment" Seoul National University 1999

      5 Anselin L, "Spatial statistical analysis and geographical information systems" 26 : 19-33, 1992

      6 Petja BM, "Spatial epidemiology risk assessment for rehabilitated former asbestos mining areas in Limpopo Province, South Africa, using remote sensing and conventional analytical methods" 25 (25): 32-39, 2010

      7 Morrill R, "Spatial diffusion" Sage Publications 86-, 1988

      8 Pfeiffer DU, "Spatial Analysis in Epidemiology" Oxford University Press 3-, 2008

      9 Anselin L, "Spatial Analyses of Crime" 4 : 213-262, 2000

      10 Pan XL, "Residential Proximity to Naturally Occurring Asbestos and Mesothelioma Risk in California" 172 : 1019-1025, 2005

      11 Fazzo L, "Pleural Mesothelioma Mortality and Asbestos Exposure Mapping in Italy" 55 : 11-24, 2012

      12 "National GIS portal"

      13 Maule MM, "Modeling Mesothelioma Risk Associated with Environmental Asbestos Exposure" 115 (115): 1066-1071, 2007

      14 김영찬, "GIS를 이용한 석면슬레이트 분포지도 작성" 한국생태환경건축학회 11 (11): 57-62, 2011

      15 최진범, "GIS 기법을 이용한 폐석면 광산의 위해성 평가" 한국광물학회 24 (24): 43-53, 2011

      16 Robinson, TP, "FAO’'s Gridded Livestock of the World" Veterinaria Italiana 43-,

      17 Kim KG, "Exploration of spatial autocorrelation and utilization of spatial regression" 6 : 983-1001, 2003

      18 Newton R, "Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui" 24 : 2012

      19 Hong HP, "Discovery of hotspot areas using a spatial clustering method and echelon analysis" 8 (8): 131-153, 2003

      20 Tobler WA., "Computer movie simulating urban growth in the Detroit region" 46 (46): 234-240, 1970

      21 Wikipedia, "Comparison of geographic information systems software"

      22 Moore DA, "Analytical Methods and Geographic Information Systems: Use in Health Research and Epidemiology" 21 (21): 146-147, 1999

      23 Anselin L, "An Introduction to Spatial Data Analysis" 38 (38): 5-22, 2006

      24 Kim JY., "A study on Geographical Interpolation Analysis of Korean Asbestos Factories" 6 : 2011

      25 Jeong SY., "A spatial statistics application for the study of traffic" 285 : 151-154, 2005

      26 Bailey TC, "A review of statistical spatial analysis in geographical information systems, Spatial Analysis and GIS, In Stewart Fotheringham and Peter Rogerson" Taylor & Francis 18-, 1994

      27 Lee JM, "A Study on the Construction of Asbestos Map Using GIS" 131-134, 2010

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2022 평가예정 계속평가 신청대상 (등재유지)
      2017-01-01 평가 우수등재학술지 선정 (계속평가)
      2013-01-01 평가 등재 1차 FAIL (등재유지) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2008-02-15 학술지명변경 외국어명 : Korean Journal of Environmental Health -> JOURNAL OF ENVIRONMENTAL HEALTH SCIENCES KCI등재
      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2006-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2005-09-13 학술지등록 한글명 : 한국환경보건학회지
      외국어명 : Korean Journal Of Environmental Health
      KCI등재
      2005-06-02 학술지등록 한글명 : 한국환경보건학회지
      외국어명 : Korean Journal of Environmental Health
      KCI등재
      2005-01-27 학회명변경 한글명 : 한국환경위생학회 -> 한국환경보건학회
      영문명 : Korean Society Of Environmental Health -> Korean Society of Environmental Health
      KCI등재
      2003-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2002-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      1999-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.44 0.44 0.4
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.42 0.4 0.605 0.21
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