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A Study on the Improvement of Sub-divided Land Cover Map Classification System - Based on the Land Cover Map by Ministry of Environment -

세분류 토지피복지도 분류체계 개선방안 연구 - 환경부 토지피복지도를 중심으로 -

  • Oh, Kwan-Young (Korea Adaptation Center for Climate Change, Korea Environment Institute) ;
  • Lee, Moung-Jin (Korea Adaptation Center for Climate Change, Korea Environment Institute) ;
  • No, Woo-Young (Ministry of environment. Environmental Information Office)
  • 오관영 (한국환경정책.평가연구원 국가기후변화적응센터) ;
  • 이명진 (한국환경정책.평가연구원 국가기후변화적응센터) ;
  • 노우영 (환경부 정보화담당관실)
  • Received : 2016.03.10
  • Accepted : 2016.04.03
  • Published : 2016.04.30

Abstract

The purpose of this study is to improve the classification system of sub-divided land cover map among the land cover maps provided by the Ministry of Environment. To accomplish the purpose, first, the overseas country land cover map classification items were examined in priority. Second, the area ratio of each item established by applying the previous sub-divided classification system was analyzed. Third, the survey on the improvement of classification system targeting the users (experts and general public) who actually used the sub-divided land cover map was carried out. Fourth, a new classification system which improved the previous system by reclassifying 41 classification items into 33 items was finally established. Fifth, the established land cover classification items were applied on study area, and the land cover classification result according to the improvement method was compared with the previous classification system. Ilsan area in Goyang city where there are diverse geographic features with various land surface characteristics such as the urbanization area and agricultural land were distributed evenly were selected as the study area. The basic images used in this study were 0.25 m aerial ortho-photographs captured by the National Geographic Information Institute (NGII), and digital topographic map, detailed stock map plan, land registration map and administrative area map were used as the relevant reference data. As a result of applying the improved classification system into the study area, the area of culture-sports, leisure facilities was $1.84km^2$ which was approximately more than twice larger in comparison to the previous classification system. Other areas such as transportation and communication system and educational administration facilities were not classified. The result of this study has meaningful significance that it reflects the efficiency for the establishment and renewal of sub-divided land cover map in the future and actual users' needs.

본 연구는 현재 환경부에서 제공하는 토지피복지도 중 세분류 토지피복지도의 분류체계를 개선하기 위한 것이다. 이를 위하여 첫째, 해외 토지피복지도 분류 항목을 중점 검토하였다. 둘째, 기존 세분류 분류체계를 적용하여 구축된 항목 당 면적비율을 분석하였다. 셋째, 실제 세분류 토지피복지도를 사용하는 사용자(전문가 및 일반인)을 대상으로 분류체계 개선에 대하여 설문조사를 수행하였다. 넷째, 최종적으로 기존 41개 분류체계를 33개 항목으로 개선하는 분류체계를 설정하였다. 다섯째, 설정된 토지피복 분류항목을 시범 적용하였으며, 기존 분류체계와 개선안에 따른 토지피복 분류 결과를 비교하였다. 연구대상지는 시가화 지역, 농경지등 다양한 지표특성을 지니고, 지형지물이 비교적 골고루 분포되어 있는 고양시 일산 지역을 대상으로 하였다. 연구에 사용된 기본 영상은 국토지리정보원에서 촬영하고 있는 0.25 m 급 정사항공영상이며, 관련 참조자료는 수치지형도, 정밀 임상도, 지적도, 행정구역도 등을 사용하였다. 개선된 분류체계를 시범지역에 적용한 결과 문화체육 휴양시설이 $1.84km^2$으로 분류되었으며, 이는 기존 분류체계 면적대비 약 2배 이상 증가한 것이다. 기타 교통통신시설 및 교육행정시설 등은 분류되지 않았다. 본 연구결과는 향후 세분류 토지피복지지도 구축과 갱신의 효율성과 실질적인 사용자 수요를 반영하였다는데 의의가 있다.

Keywords

References

  1. Australian Government, Dynamic Land Cover Datasaet (DLCD), http://www.ga.gov.au.
  2. DOI and USGS, Multi-Resolution Land Characteristics Consortium(MRLC), http://www.mrlc.gov.
  3. Geoscience Australia, 2011, The national dynamic land cover dataset. Geoscience Australia, Australia.
  4. Hong, S. M., Jung, I. K., & Kim, S. J., 2004. Standardizing Agriculture-related Land Cover Classification Scheme using IKONOS Satellite Imagery, Korean Journal of Remote Sensing, 20(4), 253-259(in Korean with English abstract). https://doi.org/10.7780/kjrs.2004.20.4.253
  5. Kim, Y. J., Cha, S. Y., & Cho, Y. H., 2014. A study of Landcover Classification Methods Using Airborne Digital Ortho Imagery in Stream Corridor, Korean Journal of Remote Sensing, 30(2), 207-218(in Korean with English abstract). https://doi.org/10.7780/kjrs.2014.30.2.4
  6. Lee, M. J., Jeon, S. W., Song, W. K., Kang, B. J., 2007. Improvement and Application for Environmental Conservation Value Assessment Map (ECVAM) of National Land in Korea, Korean Journal of Remote Sensing, 23(5), 335-346(in Korean with English abstract). https://doi.org/10.7780/kjrs.2007.23.5.335
  7. Lee, M. J., Jeon, S. W., Lee, C. s., Kang, B. J., Song, W. K., 2007. A Study on Basic Plan for Upscaling Environmental Conservation Value Assessment Map(ECVAM) of National Land in South Korea, Journal of Environmental Policy, 6(3), 115-145(in Korean with English abstract). https://doi.org/10.17330/joep.6.3.200709.115
  8. Land Cover Map (LCM), http://www.ceh.ac.uk/services/land-cover-map-2007.
  9. Lee, M. J., Kim, K. H., Park, J. H., 2014. National Environment Atlas Development and Application base on Spatial Information Environmental, Journal of Environmental Policy, 13(4), 51-78(in Korean with English abstract). https://doi.org/10.17330/joep.13.4.201412.51
  10. Ministry of environment, 2009. Short- and long-term planning land cover map to enhance the utilization, Ministry of environment, Republic of Korea.
  11. Ministry of Agriculture, Food and Rural Affairs, 2013. Establishing measures for Smart Farm map, Ministry of Agriculture, Food and Rural Affairs, Republic of Korea.
  12. Ministry of environment, 2015. A Study on the deployment of advanced the Land Cover Map, Ministry of environment, Republic of Korea.
  13. Ministry of environment, Environmental Geographic Information Service(EGIS), http://egis.me.go.kr.
  14. MILT of Japan, National Land Numerical Information download service(NLNI), http://nlftp.mlit.go.jp.
  15. Mortom, D., et al. 2011. Final Report for LCM2007-the new UK land cover map, Countryside Survey, UK
  16. National Land Information Diuision, National Land Numerical Information (NLNI), http://nlftp.mlit.go.jp/ksj-e.
  17. USGS, National Land Cover Database (NLCD), http://landcover.usgs.gov.

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