DOI QR코드

DOI QR Code

Estimation of Fire Emissions Using Fire Radiative Power (FRP) Retrieved from Himawari-8 Satellite

히마와리 위성의 산불방사열에너지 자료를 이용한 산불배출가스 추정: 2017년 삼척 및 강릉 산불을 사례로

  • Kim, Deasun (Department of Spatial Information Engineering, Pukyong National University) ;
  • Won, Myoungsoo (Center for Forest and Climate Change, National Institute of Forest Science) ;
  • Lee, Yangwon (Department of Spatial Information Engineering, Pukyong National University)
  • 김대선 (부경대학교 지구환경시스템과학부 공간정보공학전공) ;
  • 원명수 (국립산림과학원 기후변화연구센터) ;
  • 이양원 (부경대학교 지구환경시스템과학부 공간정보공학전공)
  • Received : 2017.11.30
  • Accepted : 2017.12.27
  • Published : 2017.12.31

Abstract

Wildfires release a large amount of greenhouse gases (GHGs) into the atmosphere. Fire radiative power (FRP) data obtained from geostationary satellites can play an important role for tracing the GHGs. This paper describes an estimation of the Himawari-8 FRP and fire emissions for Samcheock and Gangnueng wildfire in 6 May 2017. The FRP estimated using Himawari-8 well represented the temporal variability of the fire intensity, which cannot be captured by MODIS (Moderate Resolution Imaging Spectroradiometer) because of its limited temporal resolution. Fire emissions calculated from the Himwari-8 FRP showed a very similar time-series pattern compared with the AirKorea observations, but 1 to 3 hour's time-lag existed because of the distance between the station and the wildfire location. The estimated emissions were also compared with those of a previous study which analyzed fire damages using high-resolution images. They almost coincided with 12% difference for Samcheock and 2% difference for Gangneung, demonstrating a reliability of the estimation of fire emissions using our Himawari-8 FRP without high-resolution images. This study can be a reference for estimating fire emissions using the current and forthcoming geostationary satellites in East Asia and can contribute to improving accuracy of meteorological products such as AOD (aerosol optical depth).

산불은 다량의 온실가스를 대기 중으로 방출하는 자연재해로서, 이를 효율적으로 감시하기 위해서는 정지궤도 위성의 산불방사열에너지(fire radiative power, FRP)를 활용하는 방법이 필요하다. 본 연구에서는 2017년 5월 6일에 발생한 우리나라 삼척과 강릉 산불을 사례로, 히마와리 위성의 중적외 채널자료를 이용하여 FRP를 산출하였으며, 이를 통해 MODIS(Moderate Resolution Imaging Spectroradiometer)의 제한적인 시간해상도로는 관측이 불가능한 10분 간격의 산불 피해강도의 실시간 모니터링이 가능함을 확인하였다. 또한 히마와리 FRP를 이용하여 강릉 산불의 배출가스를 계산하였으며, 에어코리아 실측치와 비교하였을 때 거리 차에 의한 1~3시간의 지연현상과 함께, 산불배출가스의 시계열 패턴이 매우 잘 일치함을 알 수 있었다. 또한 선행연구에서 고해상도 영상분석을 통해 제시한 산불배출가스 추정량과 비교하였을 때, 100 ha당 배출량이 삼척은 약 12%, 강릉은 약 2%의 차이로 매우 유사한 결과를 나타냈다. 이는 산불 피해면적과 피해강도에 대한 직접적인 분석 없이도, 정지궤도 위성의 FRP만을 이용하여 산불배출가스의 정밀한 추정이 가능함을 의미한다. 이 연구는 향후 발사될 우리나라 정지궤도 기상위성인 GK-2A(Geostationary Korea Multi-Purpose Satellite-2A)의 산불배출가스 추정 및 에어로솔 산출에 활용될 수 있을 것으로 사료된다.

Keywords

References

  1. Akagi, S.K., R.J. Yokelson, C. Wiedinmyer, M.J. Alvarado, J.S. Reid, T. Karl, J.D. Crounse, and P.O. Wennberg, 2011. Emission factors for open and domestic biomass burning for use in atmospheric models, Atmospheric Chemistry and Physics, 11: 4039-4072. https://doi.org/10.5194/acp-11-4039-2011
  2. Delmas, R., J.P. Lacaux, and D. Brocard, 1995. Determination of Biomass Burning Emission factors: Methods and Results, Environmental Monitoring and Assessment, 38: 181-204.
  3. ECMWF, 2017. ECMWF Technical Memoranda 790, https://www.ecmwf.int, Accessed on Oct. 25, 2017.
  4. FAO (Food and Agriculture Organization of the United Nations). 2005. The state of food and agriculture 2005, http://www.fao.org/, Accessed on Oct. 25, 2017.
  5. Giglio, L. and J.D. Kendall, 2001. Application of the Dozier Retrieval to Wildfire Characterization: A Sensitivity Analysis, Remote Sensing of Environment, 77: 34-49. https://doi.org/10.1016/S0034-4257(01)00192-4
  6. Huijnen, V., M.J. Wooster, J.W. Kaiser, D.L.A. Gaveau, J. Flemming, M. Parrington, A. Inness, D. Murdiyarso, B. Main, and M. van Weele, 2016. Fire carbon emissions over maritime southeast Asia in 2015 largest since 1997, Scientific Reports, 6: 26886. https://doi.org/10.1038/srep26886
  7. Ito, A. and J.E. Penner, 2004. Global estimates of biomass burning emissions based on satellite imagery for the year 2000, Journal of Geophysical Research, 109: D14S05.
  8. IPCC, 2003. Good practice guidance for land use, landuse change and forestry, national greenhouse gas inventories programme, the institute for global environmental strategies (IGES) for the IPCC, Geneva, Switzerland.
  9. Lee, B.D., H.J. Yoon, K.S. Koo, and K.H. Kim, 2012. Estimation of biomass loss and greenhouse gases emissions from surface layer burned by forest fire, Journal of Korean Forest Society, 101(2): 286-290 (in Korean with English abstract).
  10. Li, Z., H. Wu, N. Wang, S. Qiu, J.A. Sobrino, Z. Wan, B. Tang, and G. Yan, 2013. Land surface emissivity retrieval from satellite data, International Journal of Remote Sensing, 34: 3084-3127. https://doi.org/10.1080/01431161.2012.716540
  11. Kerr, Y.H., J.P. Lagouarde, and J. Imbernon, 1992. Accurate land surface temperature retrieval from AVHRR data with use of an improved split window algorithm, Remote Sensing of Environment, 41: 197-209. https://doi.org/10.1016/0034-4257(92)90078-X
  12. Kim, D.S. and Y-W. Lee, 2016. Retrieval of fire radiative power from Himawari-8 satellite data using the mid-infrared radiance method, Journal of the Korean Society for Geospatial Information Science, 24(4): 105-113 (in Korean with English abstract). https://doi.org/10.7319/kogsis.2016.24.4.105
  13. Peterson, D., J. Wang, C. Ichoku, E. Hyer, and V. Ambrosia, 2013. A sub-pixel-based calculation of fire radiative power from MODIS observations: 1: algorithm development and initial assessment, Remote Sensing of Environment, 129: 262-279. https://doi.org/10.1016/j.rse.2012.10.036
  14. Reid, J.S., E.M. Prins, D.L. Westphal, C.C. Schmidt, K.A. Richardson, S.A. Christopher, T.F. Eck, E.A. Reid, C.A. Curtis, and J.P. Hoffman, 2004. Real-time monitoring of South American smoke particle emissions and transport using a coupled remote sensing/box-model approach, Geophysical Research Letters, 31: L06107.
  15. Seiler, W. and P.J. Crutzen, 1980. Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere from biomass burning, Climatic Change, 2: 207-247. https://doi.org/10.1007/BF00137988
  16. Valor, E. and V. Caselles, 1996. Mapping land surface emissivity from NDVI: application to European, African, and South American areas, Remote Sensing of Environment, 57: 167-184. https://doi.org/10.1016/0034-4257(96)00039-9
  17. van der Werf, G. R., J.T. Randerson, L. Giglio, G.J. Collatz, P.S. Kasibhatla, and A.F. Arellano Jr, 2006. Interannual variability in global biomass burning emissions from 1997 to 2004, Atmospheric Chemistry and Physics, 6(11): 3423-3441. https://doi.org/10.5194/acp-6-3423-2006
  18. van der Werf, G.R., J.T. Randerson, L. Giglio, G.J. Collatz, M. Mu, P.S. Kasibhatla, D.C. Morton, R.S. DeFries, Y. Jin, and T.T. van Leeuwen, 2010. Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009), Atmospheric Chemistry and Physics, 10: 11707-11735. https://doi.org/10.5194/acp-10-11707-2010
  19. Wiedinmyer, C., B. Quayle, C. Geron, A. Belote, D. McKenzie, X. Zhang, S.O' Neill, and K.K. Wynne, 2006. Estimating emissions from fires in North America for air quality modeling, Atmospheric Environment, 40: 3419-3432. https://doi.org/10.1016/j.atmosenv.2006.02.010
  20. WMO (World Meteorological Organization), 2016. Gap analyses by Variable: Fire Radiative Power, http://www.wmo-sat.info/oscar/gapanalyses?view=61, Accessed on Oct. 25, 2017.
  21. Won, M.S., K.S. Koo, M.B. Lee, and Y.M. Son, 2008. Estimation of non-CO2 greenhouse gases emissions from biomass burning in the Samcheok largefire area using Landsat TM imagery, Korean Journal of Agricultural and Forest Meteorology, 10(1): 17-24 (in Korean with English abstract). https://doi.org/10.5532/KJAFM.2008.10.1.017
  22. Wooster, M.J., 2002, Small-scale experimental testing of fire radiative energy for quantifying mass combusted in natural vegetation fires, Geophysical Research Letters, 29(21): 2027. https://doi.org/10.1029/2002GL015487
  23. Wooster, M.J., G. Roberts, and G.L.W. Perry, 2005. Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release, Journal of Geophysical Research, 110(D24).
  24. Zhang, X. and S. Kondragunta, 2008. Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product, Remote Sensing of Environment, 112: 2886-2897. https://doi.org/10.1016/j.rse.2008.02.006