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      위성영상을 이용한 북한의 농업환경 분석 -I. Landsat TM 영상을 이용한 북한의 지형과 토지피복분류- = Spatial Anaylsis of Agro-Environment of North Korea Using Remote SensingI. Landcover Classification from Landsat TM imagery and Topography Analysis in North Korea

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      https://www.riss.kr/link?id=A103958891

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      다국어 초록 (Multilingual Abstract)

      Remotely sensed images from a satellite can be applied for detecting and quantifying spatial and temporal variations in terms of landuse & landcover, crop growth, and disaster for agricultural applications. The purposes of this study were to analyze t...

      Remotely sensed images from a satellite can be applied for detecting and quantifying spatial and temporal variations in terms of landuse & landcover, crop growth, and disaster for agricultural applications. The purposes of this study were to analyze topography using DEM(digital elevation model) and classify landuse & landcover into 10 classes - paddy field, dry field, forest, bare land, grass & bush, water body, reclaimed land, salt farm, residence & building, and others - using Landsat TM images in North Korea. Elevation was greater than 1,000 meters in the eastern part of North Korea around Ranggang-do where Kaemagowon was located. Pyeongnam and Hwangnam in the western part of North Korea were low in elevation. Topography of North Korea showed typical 'east-high and west-low' landform characteristics. Landcover classification of North Korea using spectral reflectance of multi-temporal Landsat TM images was performed and the statistics of each landcover by administrative district, slope, and agroclimatic zone were calculated in terms of area. Forest areas accounted for 69.6 percent of the whole area while the areas of dry fields and paddy fields were 15.7 percent and 4.2 percent, respectively. Bare land and water body occupied 6.6 percent and 1.6 percent, respectively. Residence & building reached less than 1 percent of the country. Paddy field areas concentrated in the A slope ranged from 0 to 2 percent (greater than 80 percent). The dry field areas were shown in the A slope the most, followed by D, E, C, B, and F slopes. According to the statistics by agroclimatic zone, paddy and dry fields were mainly distributed in the North plain region(N-6) and North western coastal region(N-7). Forest areas were evenly distributed all over the agroclimatic regions. Periodic landcover analysis of North Korea based on remote sensing technique using satellite imagery can produce spatial and temporal statistics information for future landuse management and planning of North Korea.

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      참고문헌 (Reference)

      1 North Korea Road Atlas, "Woojun Map Publishing Cor" 1997

      2 Richards, J. A., "Remote sensing digital image analysis" Springer-Verlag 56-63, 1999

      3 Lillesand, T. M., "Remote sensing and image interpretatio" John Wiley & Sons, Inc. 466-471, 1994

      4 Rouse, J. W., "Monitoring vegetation systems in the great plains with ETRA, 3rd ETRS Symposium, NASA SP-353, U.S. Govt. Printing Office, Washington D.C. USA"

      5 Jensen, J. R., "Introductory digital image processing; A remote sensing perspectives" Prentice Hall 124-135, 1996

      6 Campbell, J. B., "Introduction to remote sensing" The Gilford Press 4-5, 1996

      7 IPCC, "Good practice guidance for land use, land use change and forestry" Institute for Global Environmental Strategies 2003

      8 Hong, S. Y., "Estimation of rice-planted area using Landsat TM Imagery in Dangjin-gun area" 3 : 5-15, 2001

      9 Okamoto, K., "Estimation of flood damage to rice production in North Korea in 1995" 19 : 365-371, 1995

      10 Kim, G. Y., "Estimating GHG emissions in agriculture based on IPCC guide lines, NIAST, RDA, Suwon, Korea, p.17"

      1 North Korea Road Atlas, "Woojun Map Publishing Cor" 1997

      2 Richards, J. A., "Remote sensing digital image analysis" Springer-Verlag 56-63, 1999

      3 Lillesand, T. M., "Remote sensing and image interpretatio" John Wiley & Sons, Inc. 466-471, 1994

      4 Rouse, J. W., "Monitoring vegetation systems in the great plains with ETRA, 3rd ETRS Symposium, NASA SP-353, U.S. Govt. Printing Office, Washington D.C. USA"

      5 Jensen, J. R., "Introductory digital image processing; A remote sensing perspectives" Prentice Hall 124-135, 1996

      6 Campbell, J. B., "Introduction to remote sensing" The Gilford Press 4-5, 1996

      7 IPCC, "Good practice guidance for land use, land use change and forestry" Institute for Global Environmental Strategies 2003

      8 Hong, S. Y., "Estimation of rice-planted area using Landsat TM Imagery in Dangjin-gun area" 3 : 5-15, 2001

      9 Okamoto, K., "Estimation of flood damage to rice production in North Korea in 1995" 19 : 365-371, 1995

      10 Kim, G. Y., "Estimating GHG emissions in agriculture based on IPCC guide lines, NIAST, RDA, Suwon, Korea, p.17"

      11 ERDAS, "ERDAS Field Guide. 4th Ed. Atlanta, Georgia, USA"

      12 Suzaki, J., "Development of land cover classification method using NOAA AVHRR, Landsat TM, and DEM images, Asian Conf. Remote Sens. R-2-1-R-2-6"

      13 Suzaki, J., "Crop field extraction method using NDVI and texture from Landsat TM images" Proc. of 1998 Int'l Symposium on Remote Sensing 159-162, 1998

      14 Crist, E. P., "Application of the tasseled cap concept to simulated thematic mapper data" 52 : 81-86, 1984

      15 Hong, S. Y., "Analysis on rice growth information and estimation of paddy field area by using remotely sensed data" Kyungpook National University 1999

      16 Shin, D. W., "Agricultural technology of North Korea" Ohsung Publishing Co. 1998

      17 Imagawa, T., "A monitoring method of land cover/land use change in Naiman, inner Mongolia autonomous region, China using Landsat data" 31 : 163-169, 1997

      18 Anderson, J. R., "A land use and land cover classification for use with remote sensor data, U.S. Geological Survey Professional Paper 964. Washington" Printing Office 1976

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      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2027 평가예정 재인증평가 신청대상 (재인증)
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      2017-09-19 학술지명변경 외국어명 : The Korean Society of Environmental Agriculture -> Korean Journal of Environmental Agriculture KCI등재
      2015-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2011-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2009-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2004-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2002-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.41 0.41 0.42
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.46 0.42 0.724 0.08
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