DOI QR코드

DOI QR Code

Evaluation of a Land Use Change Matrix in the IPCC's Land Use, Land Use Change, and Forestry Area Sector Using National Spatial Information

  • Park, Jeongmook (Department of Forest Management, College of Forest and Environmental Sciences, Kangwon National University) ;
  • Yim, Jongsu (Forest Geographic Information System Remote Sensing, Korea Forest Research Institute) ;
  • Lee, Jungsoo (Department of Forest Management, College of Forest and Environmental Sciences, Kangwon National University)
  • Received : 2017.10.30
  • Accepted : 2017.11.14
  • Published : 2017.11.30

Abstract

This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change's (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

Keywords

References

  1. Bae YJ, Bae SJ, Seo IH, Seo K, Lee JJ, Kim GY. 2013. Estimation of uncertainty on greenhouse gas emission in the agriculture sector. J Korean Soc Rural Plan 19: 125-135. (in Korean with English abstract) https://doi.org/10.7851/ksrp.2013.19.4.125
  2. Federal Environment Agency (FEA). 2017. Submission under the United Nations Framework Convention on Climate Change and the Kyoto Protocol 2017. pp. 540-648.
  3. Greenhouse Gas Inventory & Research Center (GIR). 2016. National Greenhouse Gas Inventory Report of Korea. pp. 255-300. (in Korean)
  4. Intergovernmental Panel on Climate Change (IPCC). 2003. Good practice guidance for land Use, land-use change and forestry. Institute for Global Environmental Strategies, Hayama, Kanagawa, pp 2.7-2.17.
  5. Intergovernmental Panel on Climate Change (IPCC). 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Institute for Global Environmental Strategies, Hayama, Kanagawa, pp 1.1-1.21.
  6. Korea Forest Research Institute (KFRI). 2011. The 6th National Forest Inventory and Forest Health Monitoring-Field Manual-. Korea Forest Service, Seoul, pp 59. (in Korean)
  7. Korea Institute for International Economic Policy (KIEP). 2015. Comparative analysis on climate support: key findings and implications. Korea Institute for International Economic Policy, Sejong, pp 23-29. (in Korean with English abstract)
  8. Korea Research Institute for Human Settlements (KRIHS). 2002. Land use/cover classification method for individual land parcel in high spatial resolution remotely sensed imagery. Korea Research Institute for Human Settlements, Sejong, pp 57-66. (in Korean with English abstract)
  9. Lee GH, Lee JS. 2012. Extraction and accuracy assessment of deforestation area using GIS and remotely sensed data. J Korean For Soc 101: 365-373. (in Korean with English abstract)
  10. Ministry of Environment (ME). 2013. Guidelines for Land Cover Mapping. (in Korean)
  11. Ministry of Land, Infrastructure and Transport (MOLIT). 2000. Statistical Year Book of MOLIT 2000. (in Korean with English abstract)
  12. Ministry of Land, Infrastructure and Transport (MOLIT). 2007. Statistical year book of MOLIT 2007. Ministry of Land, Infrastructure and Transport, Sejong. (in Korean with English abstract)
  13. Ministry of Land, Infrastructure and Transport (MOLIT). 2010. Statistical year book of MOLIT 2010. Ministry of Land, Infrastructure and Transport, Sejong. (in Korean with English abstract)
  14. Ministry of the Environment, Japan (MEJ). 2017. National greenhouse gas inventory report of Japan. Center for Global Environmental Research, Onogawa, Tsukuba, Ibarak.
  15. Ogle SM, Breidt FJ, Eve MD, Paustian K. 2003. Uncertainty in estimating land use and management impacts on soil organic carbon storage for US agricultural lands between 1982 and 1997. Global Change Biol 9: 1521-1542. https://doi.org/10.1046/j.1365-2486.2003.00683.x
  16. Park SJ, Lee CH, Kim MS, Yun SG, Kim YH, Ko BG. 2016. Calculation of GHGs emission from LULUCF-cropland sector in South Korea. Korean J Soil Sci Fert 49: 826-831. (in Korean with English abstract) https://doi.org/10.7745/KJSSF.2016.49.6.826
  17. Statistics Finland (SF). 2017. Greenhouse gas emissions in Finland 1990 to 2015. National Inventory report under the UNFCCC and the Kyoto Protocol, Helsinki, pp 264-361.
  18. Swedish Environmental Protection Agency (SEPA). 2017. National Inventory report Sweden 2017. Naturvardsverket, Stockholm, pp 338-375.
  19. Yim JS, Kim RH, Lee SJ, Son YM. 2015. Land-use change assessment by permanent sample plots in national forest inventory. J Clim Change Res 6: 33-40. (in Korean with English abstract) https://doi.org/10.15531/ksccr.2015.6.1.33
  20. Yoo SH, Heo J, Jung JH, Han SH, Kim KM. 2011. Estimation of aboveground biomass carbon stock using landsat TM and ratio images - kNN algorithm and regression model priority. J Korean Soc Geospat Inf Syst 19: 39-48. (in Korean with English abstract)
  21. Yu SC, Ahn W, Ok JA. 2015. A study on construction plan of the statistics for national green house gas inventories (LULUCF Sector). J Korean Spat Inf Soc 23: 67-77. (in Korean with English abstract)