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MODIS NDVI 및 기후정보 활용 산림생태계의 기후변화 민감성 분석

Analysis of Climate Change Sensitivity of Forest Ecosystem using MODIS Imagery and Climate Information

  • 송봉근 (국립재난안전연구원 재난원인조사실) ;
  • 박경훈 (창원대학교 환경공학과)
  • SONG, Bong-Geun (Disaster Scientific Investigation Division, National Disaster of Management Institute) ;
  • PARK, Kyung-Hun (Dept. of Environmental Engineering, Changwon National University)
  • 투고 : 2018.06.20
  • 심사 : 2018.07.16
  • 발행 : 2018.09.30

초록

본 연구는 공간분석기법을 활용하여 6개 국립공원지역을 대상으로 기후변화에 따른 산림생태계 민감성을 분석하였다. 분석방법은 공간해상도 $1km{\times}1km$와 16일 단위의 MODIS NDVI와 기상청 남한상세 기온자료를 활용하여 시계열 분석 및 상관분석을 통해 도출하였다. 기후변화에 가장 민감한 지역은 평균 상관계수가 가장 높은 지리산 국립공원(r=0.434)과 설악산 국립공원(r=0.415)으로 나타났다. 기후변화에 의한 산림생태계의 민감성은 국립공원 내 식생유형 및 서식지의 특성 등에 따라 상이한 것으로 나타났다. 특히 한라산 국립공원의 구상나무 군락지에서는 기온이 증가하는 반면, 식생지수는 감소하는 것을 알 수 있었다. 이는 구상나무가 기후변화에 취약한 종임을 선행연구와 비교를 통해 증명되었다. 이와 같은 결과는 향후 산림생태계 보호를 위한 기후변화 대응 및 적응정책을 마련하는데 기초적인 자료로 활용될 것으로 판단된다.

The purpose of this study is to analyze sensitivity of forest ecosystem to climate change using spatial analysis methods focused on 6 national parks. To analyze, we constructed MODIS NDVI and temperature of Korea Meteorologic Administration based on 1km spatial resolution and 16 days. And we conducted time-series and correlation analysis using MODIS NDVI and temperature. A most sensitive region to climate change is Jirisa National Park(r=0.434) and Seoraksan National Park(r=0.415), there is the highest mean correlation coefficient. The sensitivity of forest ecosystem varied according to habitat characteristics and forest types in national park. In Abies koreana of Hallsan Nation Park, temperature has raised, but NDVI has decreased. these results will be based data of climate change adaption policy for protecting forest ecosystem.

키워드

참고문헌

  1. Bragin, N., S. Amgalanbaatar, G. Wingard, and R.P. Reaing. 2017. Creating a model of habitat suitability using vegetation and ruggedness for Ovis ammon and Capra sibirica (Artiodactyla: Bovidae) in Mongolia. Journal of Asia-Pacific Biodiversity 10:390-395. https://doi.org/10.1016/j.japb.2017.06.003
  2. Clark, D.B., P.C. Olivas, S.F. Oberbauer, D.A. Clark and M.G. Ryan. 2008. First direct landscape-scale measurement of tropical rain forest Leaf Area Index, a key driver of global primary productivity. Ecology Letters 11:163-172.
  3. Cleveland, R.B., W.S. Cleveland, J.E. McRae and I. Terpenning. 1990. STL: A seasonal-trend decomposition procedure based on loess. Journal of Official Statistics 6(1):3-73.
  4. Fan, Z.M., and J. Li, T.X. Yue. 2012. Changes of climate-vegetation ecosystem in loess plateau of China. Procedia Environmental Sciences 13:715 -720. https://doi.org/10.1016/j.proenv.2012.01.064
  5. Heumann, B.W., J.W. Seaquist, L. Eklundh and P. Jonsson. 2007. AVHRR derived phenological change in the Sahel, Sudan, Africa, 1982-2005. Remote Sensing Environment 108:385-392. https://doi.org/10.1016/j.rse.2006.11.025
  6. Huete, A.R., C. Justice, W.V. Leeuwen. 1999. MODIS Vegetation Index (MOD13) Algorithm Theoretical Basis Document Version 3.
  7. Hong, S.Y., J. Hur, J.B. Ahn, J.M. Lee, B.K. Min, C.K. Lee, Y. Kim, K.D. Lee and S.H. Kim. 2012. Estimating rice yield using MODIS NDVI and meteorogical data in Korea. Korean Journal of Remote Sensing 28(5):509-520. https://doi.org/10.7780/kjrs.2012.28.5.4
  8. IPCC(Intergovernmental Panel of Climate Change). 2014. Climate Change 2014: Impacts, Adaptation, and Vulnerability: Summary for Policymakers. pp. 27-30.
  9. Kang, S.H. 2003. A study on the flood damage assessment by Typhoon RUSA in the East Coast of Kangwon Prefecture following the 2000 large scale fire disaster focused on the watershed of oship river, Samecheok City. FIRE SCIENCE AND ENGINEERING 17(4):70-75.
  10. Kim, H, J. Hong, S.C. Kim, S.H. Oh and J. Kim. 2011. Plant phenology of threatened species for climate change in sub-alpin zone of Korea. Korean Journal of Plant Resources 24(5):549- 556. https://doi.org/10.7732/kjpr.2011.24.5.549
  11. Kim, N.S. 2012. Detection of vegetation dieback area in the subalpine zone of Mt. Baekdu using MODIS time series data. Journal of the Korean Geographical Society 47(6):825-835.
  12. Kong, W., S. Lee, H. Park and J.A. Yu. 2012. Ecosystem vulnerability assessment of local government due to climate change. Journal of Climate Change Research 3(1):51-69.
  13. Korea Environmental Institute. 2014. Measures for strengthening the ecosystem environment security in responding to climate change-focused on the examination and prospect of vulnerable ecosystem in terms of climate change-. Report of Korea Environmental Institute. pp. 2.
  14. Korea Meteorological Administration(KMA). 2011. Report about prospect of climate change over Peninsula. Report of Korea Meteorological Administration.
  15. Kwon, C.G., S.Y. Lee and H.P. Lee. 2012. Analysis of forest fire occurrences and damage in Samcheok. Proceedings on Korean Institute of Fire Science & Engineering. 444-447.
  16. Lee, M.B., N.S. Kim, H.S. Choe and K.H. Shin. 2003. An analysis on spatio-temporal changes of land cover focusing on NDVI using GIS and RS in Pyeongbuk Province, Northwest Korea. Journal of the Korean Geopgraphical Society 38(5):835-848.
  17. Liu, J., G. Kattel, H.P.H. Arp and H. Yang. 2015. Towards threshold-based management of freshwater ecosystems in the context of climate change. Ecological Modelling 318:265-274. https://doi.org/10.1016/j.ecolmodel.2014.09.010
  18. Macfadyen S., G. McDonald and M.P. Hill. 2018. From species distribution to climate change adaptation: Knowledge gaps in managing invertebrate pests in broad-acre grain crops. Agriculture, Ecosystems and Environment 253:208-219. https://doi.org/10.1016/j.agee.2016.08.029
  19. Park, C.Y., Y.E. Choi, Y.A. Kwon, J.I. Kwon and H.S. Lee. 2013. Studies on changes and future projections of subtropical climate zones and extreme temperature events over South Korea using high resolution climate change scenario based on PRIDE model. Journal of The Korean Association of Regional Geographers 19(4):600-614.
  20. Park, J.S. and K.T. Kim. 2009. Evaluation of MODIS NDVI for drought monitoring focused on comparison of drought index. The Journal of GIS Association of Korea 17(1):117-129.
  21. Park, S.Y. 2013. Satellite-Measured vegetation phenology and atmospheric aerosol time series in the Korean peninsula. Journal of the Korean Geographical Society 48(4):497-508.
  22. Potter, C., S. Klooster, A. Huete and V. Genovese. 2007. Terrestrial carbon sinks for the United States predicted from MODIS satellite data and ecosystem modeling. Earth Interactions 11.
  23. Safaei, M., M. Tarkesh, H. Bashari and M. Bassiri. 2018. Modeling potential habitat of Astragalus verus Olivier for conservation decisions: A comparison of three correlative models. Flora 242:61-69. https://doi.org/10.1016/j.flora.2018.03.001
  24. Sapta, S., B. Sulistyantara, I.S. Fatimah and A. Faqih. 2015. Geospatial approach for ecosystem change study of Lombok Island under the influence of climate change. Procedia Environmental Sciences 24:165-173. https://doi.org/10.1016/j.proenv.2015.03.022
  25. Tony, P. 2008. Conceptual framework for assessment and management of ecosystem impacts of climate change. Ecological complexity 5:329-338. https://doi.org/10.1016/j.ecocom.2008.09.002
  26. Wakelin, S.L., Y. Artioli, M. Butenschon, J.I. Allen and J.T. Holt. 2015. Modelling the combined impact of climate change and direct anthropogenic drivers on the ecosystem of the northwest European continental shelf. Journal, of Marine Systems 152:51.63. https://doi.org/10.1016/j.jmarsys.2015.07.006
  27. Yue, T.X., Z.M. Fan and C.F. Chen. 2011. Surface modelling of global terrestral ecosystems under three climate change scenarios. Ecological modelling 222: 2342-2361. https://doi.org/10.1016/j.ecolmodel.2010.11.026