Journal of Korean Society of Forest Science (한국산림과학회지)

Korean Society of Forest Science (한국산림과학회)
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Mapping of Spatial Distribution for Carbon Storage in Pinus rigida Stands Using the National Forest Inventory and Forest Type Map: Case Study for Muju Gun

국가산림자원조사 자료와 임상도를 활용한 리기다소나무림의 탄소 저장량에 대한 공간분포도 작성: 무주군의 사례로

  • Seo, Yeonok (Warm-Temperate and Subtropical Forest Research Center, National Institute of Forest Science) ;
  • Jung, Sungcheol (Forest Policy Division, Korea Forest Service) ;
  • Lee, Youngjin (Department of Forest Resources, Kongju National University)
  • 서연옥 (국립산림과학원 난대.아열대산림연구소) ;
  • 정성철 (산림청 산림정책과) ;
  • 이영진 (공주대학교 산림자원학과)
  • Received : 2017.03.15
  • Accepted : 2017.04.12
  • Published : 2017.06.30
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Abstract

This study was conducted to develop a carbon storage distribution map of Pinus rigida stands in Muju-gun by using of the National Forest Inventory data and digital forest map. The relationships between the stand variables such as height, age, diameter at breast height (DBH), crown density and aboveground biomass of Pinus rigida were analyzed. The results showed that the crown density had the highest positive correlation with a value of 0.74 followed by the height variable with value of 0.61. The aboveground biomass regression models were developed to estimate biomass and carbon storage map. The results of this study showed that the average carbon storage was 58.2 ton C/ha while the total carbon stock of rigida pine forests in Muju area was estimated to be 430,963 C ton.

본 연구의 목적은 국가산림자원조사 자료와 수치임상도를 활용하여 무주군 지역 리기다소나무림의 추정된 탄소 저장량에 대한 공간분포도를 작성하고자 하였다. 국가산림자원조사 자료를 이용하여 바이오매스 추정식을 개발하기 위해서 수고, 임령, 흉고직경, 수관밀도와의 상관관계를 분석한 결과, 수관밀도(0.74)인자가 가장 높은 양(+)의 상관성을 보였고, 다음으로는 수고(0.61)인자에서 높은 상관관계가 나타났다. 상관분석 결과를 기반으로 탄소 저장량 추정식을 도출한 후 수치임상도를 활용하여 추정된 탄소 저장량 공간지도를 작성하였다. 수관밀도와 수고를 적용하여 추정된 탄소 저장량을 산출한 결과, 평균 58.2 ton C/ha로 나타났으며 전북 무주지역 리기다소나무림의 지상부 총 탄소저장량은 430,963 C ton으로 추정되었다.

Keywords

References

  1. Blackard, J.A., Finco, M.V., Helmer, E.H., Holden, G.R., Hoppus, M.L., Jacobs, D.M., Lister, A.J., Moisen, G.G., Nelson, M.D., Riemann, R., Ruefenacht, B., Salajanu, D., Weyermann, D.L., Winterberger, K.C., Brandeis, T.J., Czaplewski, R.L., McRoberts, R.E., Patterson, P.L. and Tymcio, P.P. 2008. Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information. Remote Sensing of Environment 112(4): 1658-1677. https://doi.org/10.1016/j.rse.2007.08.021
  2. Breidenbach, J., Naesset, E. and Gobakken, T. 2012. Improving k-nearest neighbor predictions in forest inventories by combining high and low density airborne laser scanning data. Remote sensing of environment 117: 358-365. https://doi.org/10.1016/j.rse.2011.10.010
  3. Chun J.H., Lim, J.H. and Lee, D.K. 2007. Biomass estimation of Gwangneung catchment area with Landsat ETM+ image. Journal of Korean Forestry Society 96(5): 591-601.
  4. Chung, S.Y., Yim, J.S., Cho, H.K., Jeong, J.H., Kim, S.H. and Shin, M.Y. 2009. Estimation of forest biomass for Muju county using biomass conversion table and remote sensing data. Journal of Korean Forest Society 98(4): 409-416.
  5. Fournier, R.A., Luther, J.E., Guindon, L., Lambert, M.C., Piercey, D., Hall, R.J. and Wulder, M.A. 2003. Mapping aboveground tree biomass at the stand level from inventory information: test cases in Newfoundland and Quebec. Canadian Journal of Forest Resources 33: 1846-1863. https://doi.org/10.1139/x03-099
  6. Fuchs, H., Magdon, C., Kleinn, C. and Flessa, H. 2009. Estimating aboveground carbon in a catchment of the Siberian forest tundra: combining satellite imagery and field inventory. Remote Sensing of Environment 113(3): 518-531. https://doi.org/10.1016/j.rse.2008.07.017
  7. Gjertsen, A.K. 2007. Accuracy of forest mapping based on Landsat TM data and a kNN-based method. Remote Sensing of Environment 110(4): 420-430. https://doi.org/10.1016/j.rse.2006.08.018
  8. Jung, J.H., Heo, J., Yoo, S.H., Kim, K.M. and Lee, J.B. 2010. Estimation of aboveground biomass carbon stock in Danyang area using kNN algorithm and landsat TM seasonal satellite images. Journal of the Korean Society for Geospatial Information Science 18(4): 119-129.
  9. Jung, J.H., Kim, S.P., Hong, S.C., Kim, K.M., Kim, E.S., Im, J.H. and Heo, J. 2013. Effects of national forest inventory plot location error on forest carbon stock estimation using k-nearest neighbor algorithm. Journal of Photogrammetry and Remote Sensing 82: 82-92.
  10. Kim, E.S., Kim, K.M., Kim, C.C., Lee, S.H. and Kim, S.H. 2010. Estimating the spatial distribution of forest stand volume in Gyeonggi Province using national forest inventory data and forest type map. Journal of Korean Forest Society 99(6): 827-835.
  11. Kim, E.S., Kim, K.M., Lee, J.B., Lee, S.H. and Kim. C.C. 2011a. Spatial upscaling of aboveground biomass estimation using national forest inventory data and forest type map. Journal of Korean Forest Society 100(3): 455-465.
  12. Kim, K.D., Park, J.W., Park, I.H., Kim, C.M. and Cheong, S.H. 1985. Growth and dry matter production of Pinus Rigida Mill and Robinia Pseudoacacia L. Journal of Korea Forestry Energy Research Society 5(1): 1-9.
  13. Kim, K.M., Lee, J.B., Kim, E.S., Park, H.J., Roh, Y.H., Lee, S.H., Park, K.H. and Shin. H.S. 2011b. Overview of research trends in estimation of forest carbon stocks based on remote sensing and GIS. Journal of Korean Association of Geographic Information Studies 14(3): 236-256. https://doi.org/10.11108/kagis.2011.14.3.236
  14. Kim, S.Y. 2011. Assessment of crown fire hazard based on the fuel characteristics in Pinus densiflora stands. Department of Forest Resource Graduate School of Kongju National University PP. 84.
  15. Korea Forest Research Institute. 2010. Main tree species carbon emission factors for forest greenhouse inventory pp. 89.
  16. Korea Forest Service. 2009. Table of tree harvest and weight and volume. pp. 21.
  17. Kwak, D.A., Lee, W.K. and Son, M.H. 2005. Application of LiDAR for measuring individual trees and forest stands. Journal of Korean Forest Society 94(6): 431-440.
  18. Labrecque, S., Fournier, R.A., Luther, J.E. and Piercey, D. 2006. A comparison of four methods to map biomass from Landsat-TM and inventory data in western Newfoundland. Forest Ecology and Management 226: 129-144. https://doi.org/10.1016/j.foreco.2006.01.030
  19. Lee, C.S., Lee, W.K., Yoon, J.H. and Song, C.C. 2006. Distribution pattern of Pinus densiflora and Quercus Spp. stand in Korea using spatial statistics and GIS. Journal of Korean Forest Society 95(6): 663-671.
  20. Lee, W.K. 1996. Stand and general Height-DBH curve models for Pinus densiflora in Kangwon Province. Journal of Korean Forest Economics Society 4(2): 66-78.
  21. Lumbres, R.I. and Lee, Y.J. 2014. Aboveground biomass mapping of La Trinidad forests in Benguet, Philippines, using Landsat thematic mapper data and k-nearest neighbor method. Forest Science and Technology 10(2): 104-111. https://doi.org/10.1080/21580103.2013.866171
  22. Magnussen, S., McRoberts, R.E. and Tomppo, E.O. 2009. Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories. Remote Sensing of Environment 113(3): 478-488.
  23. McRoberts, R.E., Tomppo, E.O., Finley, A.O. and Heikkinen, J. 2007. Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery. Remote Sensing of Environment 111(4): 466-480. https://doi.org/10.1016/j.rse.2007.04.002
  24. Nelson, R., Jimenez-Ramon, J.A., Schnell, C.E., Hartshorn, G.S., Gregoire, T.G., and Oderwald, R. 2000, Canopy height models and airborne lasers to estimate forest biomass: two problems. International Journal of Remote Sensing 21(11): 2153-2162. https://doi.org/10.1080/01431160050029486
  25. O'Brien, S.T., Hubbell, S.P., Spiro, P. and Condit, R. 1995. Diameter, height, crown, and age relationships in eight neotropical tree species. Ecology 76(6): 1926-1939. https://doi.org/10.2307/1940724
  26. Park, H.J., Shin, H.S., Roh, Y.H., Kim, K.M. and Park. K.H. 2012. Estimating forest carbon stocks in Danyang using Kriging methods for aboveground biomass. Journal of The Korean Association of Geographic information Studies 15(1): 16-33. https://doi.org/10.11108/kagis.2012.15.1.016
  27. Rahman, M.M., Csaplovics, E., and Koch, B. 2008. Satellite estimation of forest carbon using regression models. International Journal of Remote Sensing 29(23): 6917-6936. https://doi.org/10.1080/01431160802144187
  28. Reese, H., Nilsson, M., Sandstrom, P., and Olson, H. 2002. Application using estimates of forest of forest parameters derived from satellite and forest inventory data. Computers and Electronics in Agriculture 37: 37-55. https://doi.org/10.1016/S0168-1699(02)00118-7
  29. SAS Institute, Inc., 2004. SAS/STAT 9.1 User's Guide. SAS Institute, Inc. Cary. NC.
  30. Shim, W.B., Jeong, J.H., Kim, S.H., Kim, J.S., Ryu, J.H., Kim, J.C., Seo, S.A. and You, B.O. 2008. 5th Korea national forest inventory-field survey manual-Korea Forest Research Institute. pp. 54.
  31. Shin, J.H. 2012. Estimation of forest biomass and carbon dioxide absorption using ggeographic information system (GIS) and remote sensing. Department of environmental health graduate school of Public Health, Seoul National University pp. 52.
  32. Statistical Yearbook of Muju. 2013. pp. 34-49.
  33. Tomppo, E., Nilsson, M., Rosengren, M., Aalto, P. and Kennedy, P. 2002. Simultaneous use of Landsat-TM and IRS-1C WiFS data in estimating large area tree stem volume and aboveground biomass. Remote Sensing of Environment 82: 156-171. https://doi.org/10.1016/S0034-4257(02)00031-7
  34. Yim, J.S., Han, W.S., Hwang, J.H., Chung, S.Y., Cho, H.K. and Shin, M.Y. 2009. Estimation of forest biomass based upon satellite date and national forest inventory data. Journal of Korean Remote Sensing 25(4):311-320.
  35. You, B.O., Kim, C.C. and Kim, S.H. 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