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Improvement of Forest Boundary in Landcover Classification Map(Level-II) for Functional Assessment of Ecosystem Services

생태계 서비스 기능평가를 위한 중분류 토지피복지도 산림지역 경계설정 개선 방안

  • Jeon, Seongwoo (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Kim, Jaeuk (Korea Environment Institute) ;
  • Kim, Yuhoon (Korea Environment Institute) ;
  • Jung, Huicheul (Korea Environment Institute) ;
  • Lee, Woo-Kyun (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Kim, Joon-Soon (Department of Forest Management, Kangwon National University)
  • 전성우 (고려대학교 환경생태공학부) ;
  • 김재욱 (한국환경정책.평가연구원) ;
  • 김유훈 (한국환경정책.평가연구원) ;
  • 정휘철 (한국환경정책.평가연구원) ;
  • 이우균 (고려대학교 환경생태공학부) ;
  • 김준순 (강원대학교 산림경영학과)
  • Received : 2015.02.02
  • Accepted : 2015.02.25
  • Published : 2015.02.28

Abstract

Interests in ecosystem services have increased and a number of attempts to perform a quantitative valuation on them have been undertaken. To classify the ecosystem types landcover classification maps are generally used. However, some forest types on landcover classification maps have a number of errors. The purpose of this study is to verify the forest types on the landcover map by using a variety of field survey data and to suggest an improved method for forest type classifications. Forest types are compared by overlaying the landcover classification map with the 4th forest type map, and then they are verified by using National Forest Inventory, 3rd National Ecosystem Survey and field survey data. Misclassifications of forest types are found on the forest on the forest type map and farm and other grassland on the landcover map. Some errors of forest types occur at Daegu, Busan and Ulsan metropolitan cities and Gangwon province. The results of accuracy in comprehensive classification show that deciduous forest is 76.1%; coniferous forest is 54.0%; and mixed forest is 22.2%. In order to increase the classification accuracy of forest types a number of remote sensing images during various time periods should be used and the survey period of NFI and the National Forest Inventory and National Ecosystem Survey should be consistent. Also, examining areas with wide forest patch should be prioritized during the field survey in order to decrease any errors.

Keywords

References

  1. Burkhard, B.,F. Kroll.F. Muuller and W. Windhorst. 2009. Landscapes' Capacities to Provide Ecosystem Services-a Concept for Land-Cover Based Assessments. Landscape Online 15: 1-22. DOI:10.3097/LO.200915.
  2. Jeon SW.Kim JU and Jung HC. 2013. A Study on the Forest Classification for Ecosystem Services Valuation - Focused on Forest Type Map and Landcover Map. J. Korean Env. Res. Tech. 16(3): 31-39.
  3. Lee SI.Lee CS.Cho JG and Yoon YS. 2003. Mapping of Land Cover Map using Satellite Imagery Data - Focusing on the Ministry of Environment Land Cover Map(Level II). Proceeding of Geographic Information Systems Association of Korea 629-636.
  4. Liu, S.,R. Costanza.A. Troy.J. D'Aagostino and W. Mates. 2010. Valuing New Jersey's Ecosystem Services and Natural Capital : A Spatially Explicit Benefit Transfer Approach. Environmental Management 45(6): 1271-1285. https://doi.org/10.1007/s00267-010-9483-5
  5. Park JJ.Ku CY and Kim BS. 2007. Improvement of the Level-2 Land Cover Map with Satellite Image. The Journal of GIS Association of Korea 15(1): 67-80.
  6. You BO.Kim CC and Kim SH. 2011. Development of FAPIS(Forest Aerial Photograph Interpretation System) for Digital Forest Cover Type Mapping(Version 1.0). Journal of the Korean Association of Geographic Information Studies. 14(2): 128-137. https://doi.org/10.11108/kagis.2011.14.2.128

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  2. 산림의 CO2 흡수량 평가를 위한 통계 및 공간자료의 활용성 검토 - 안산시를 대상으로 - vol.27, pp.2, 2015, https://doi.org/10.14249/eia.2018.27.2.124