Himawari-8 AHI fire detection in clear sky based on time-phase change

  • role: First author第一作者
  • Affiliation:

    HUAYUN ShineTek,Beijing100081,China

  • Email:yanjj@cma.gov.cn
  • Introduction:鄢俊洁,1980年生,女,高级工程师,研究方向为气象卫星数据处理与应用。E-mail:yanjj@cma.gov.cn
YAN Junjie1,  
  • Affiliation:

    HUAYUN ShineTek,Beijing100081,China

QU Jianhua1,  
  • Affiliation:

    HUAYUN ShineTek,Beijing100081,China

RAN Maonong1,  
  • Affiliation:

    HUAYUN ShineTek,Beijing100081,China

ZHANG Fangfang1

Resümee

Himawari-8 is suitable in fire detection because of its high spatial resolution, observation frequency, and time efficiency. This paper proposes an improved fire detection algorithm based on the continuous phase change at the 3.9 and 11.2 μm measurements by Himawari-8 satellite. The brightness temperature change is stable and evident on the basis of the results on brightness temperature change in different latitudes under clear sky conditions in one day. The brightness temperature at the 3.9 μm channel changes faster than that at the 11.2 μm channel under the continuous phase change for 10 min when a fire occurs. The proposed improved fire detection algorithm for clear sky conditions considers the visible spectral effect at the 3.9 μm channel during day time. Experiments on this algorithm are conducted in several places, such as the serious explosive fire near a chemical plant in Qiaodong District, Zhangjiakou City, Hebei Province, at 16:40 (UTC) on November 27, 2018 and a fire incident in southwestern Australia on February 28, 2019, and the proposed algorithm quickly and effectively detects the occurrence of fire. Results shows that the proposed algorithm can perform fire detection well during winter, night time, and daytime.

Schlüsselwort

remote sensing;Himawari-8;AHI;fire detection;high-frequency observation;phase change;brightness temperature

References

  1. 1.
    Bessho K, Date K, Hayashi M, Ikeda A, Imai T, Inoue H, Kumagai Y, Miyakawa T, Murata H, Ohno T, Okuyama A, Oyama R, Sasaki Y, Shimazu Y, Shimoji K, Sumida Y, Suzuki M, Taniguchi H, Tsuchiyama H, Uesawa D, Yokota H and Yoshida R. 2016. An introduction to Himawari-8/9-Japan's new-generation geostationary meteorological satellites. Journal of the Meteorological Society of Japan, 94(2): 151-183
  2. 2.
    Boles S H and Verbyla D L. 2000. Comparison of three AVHRR-based fire detection algorithms for interior Alaska. Remote Sensing of Environment, 72(1): 1-16
  3. 3.
    Chen J, Zheng W and Liu C. 2017. Application of grassland fire monitoring based on Himawari-8 geostationary meteorological satellite data. Journal of Natural Disasters, 26(4): 197-204
  4. 4.
    Dozier J. 1981. A method for satellite identification of surface temperature fields of subpixel resolution. Remote Sensing of Environment, 11: 221-229
  5. 5.
    Du P, Liu M X, Xu T T and Song Y. 2018. Application of Himawari-8 data in monitoring forest fire. Acta Scientiarum Naturalium Universitatis Pekinensis, 54(6): 1251-1258
  6. 6.
    Flannigan M D and Vonder Haar T H. 1986. Forest fire monitoring using NOAA satellite AVHRR. Canadian Journal of Forest Research, 16(5): 975-982
  7. 7.
    Griffith P C. 2016. Advanced Himawari Imager (AHI) design and operational flexibility//12th Annual Symposium on New Generation Operational Environmental Satellite Systems. [s.l.]: AMS
  8. 8.
    He Q J and Liu C. 2008. Improved Algorithm of Self-adaptive Fire Detection for MODIS Data,12(3): 448-453
  9. 9.
    Kaufman Y J, Tucker C J and Fung I Y. 1989. Remote sensing of biomass burning in the tropics. Advances in Space Research, 9(7): 265-268
  10. 10.
    Schroeder W, Oliva P, Giglio L and Csiszar I A. 2014. The New VIIRS 375m active fire detection data product: algorithm description and initial assessment. Remote Sensing of Environment, 143: 85-96
  11. 11.
    Wickramasinghe C H, Jones S, Reinke K and Wallace L. 2016. Development of a multi-spatial resolution approach to the surveillance of active fire lines using Himawari-8. Remote Sensing, 8(11): 932
  12. 12.
    Xiao W P. 2015. Japanese first next-generation weather satellite Himawari-8 enters geostationary orbit. Space International, (2): 87-91
  13. 13.
    Zheng W, Wang M, Chen J and Liu C. 2016. Application of Himawair-8 satellite data in environmental monitoring: a case study of cyanobacteria blooms and straw incineration monitoring//2016 Annual Meeting of the Chinese Society of Environmental Sciences. Haikou: CSES

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