Research on the emergency response of forest fires in Sichuan with the help of high-definition remote sensing technology: An example of emergency monitoring of forest fires in Mianning “4·20”

  • role: First author第一作者
  • Affiliation:

    Sichuan Academy of Safety Science and Technology, Chengdu 610045, China

    Sichuan Anxin Kechuang Technology Co., Ltd, Chengdu 610045, China

  • Email:tangyao985@163.com
  • Introduction:1985E-mailtangyao985@163.com
TANG Yao12,  
  • Affiliation:

    Sichuan Academy of Safety Science and Technology, Chengdu 610045, China

    Sichuan Anxin Kechuang Technology Co., Ltd, Chengdu 610045, China

WANG Lijuan12,  
  • Affiliation:

    Sichuan Vocational and Technical College of Communications,Chengdu 611130, China

DENG Cong3,  
  • Affiliation:

    Combat Training Office of Sichuan Forest Fire Rescue Corps, Chengdu 610045, China

GAN Yuquan4,  
  • Affiliation:

    High-resolution Earth Observation System Sichuan Data and Application Center, Chengdu 610000, China

ZHAO Juan5

ملخص

High-scoring remote sensing has the advantages of “high availability”, “easy process”, “high spatial resolution”, “multiple satellites”, “rich information acquisition” and “strong long-term observation ability”, etc., which are useful for realizing forest fires. The prevention and control objectives of “playing early, playing small, and fighting” provide important technical means.In this paper, the high-scoring remote sensing technology is used in the emergency rescue of the “4·20” forest fire disaster in Mianning, Sichuan, and the forest fire elements are quickly extracted through the high-scoring remote sensing texture features to obtain information about the location of the water source near the fire site, rescue forces, and fire-fighting routes; use it The spectral characteristics sense the abnormal brightness temperature in the area to detect fire points, monitor the evolution of the fire situation and the development of the fire; carry out dynamic monitoring of the range of the fire area and migration changes based on the spectral characteristics, predict the development trend of the fire, and propose emergency rescue deployment suggestions in real time. Support disaster relief; use the Normalized Vegetation Index (NDVI) to complete the extraction of fire areas, fire intensity information and preliminary disaster assessment.In view of the secondary hidden dangers after the fire, combined with the distribution of fire areas and topographical factors, 28 potential debris flow gullies were delineated after the fire, and it was proposed based on the proportion of the high intensity area in the debris flow gully, the length of the main gully, the vertical drop of the gully bed, the drainage area and the gully. Influencing factors such as the average slope of the internal fire zone are used to evaluate the susceptibility of potential debris flow gully. Four of them are predicted to be highly prone, 11 are medium prone, and 13 are low prone.The research results show that high-scoring remote sensing technology can predict forest fire emergency rescue and post-fire secondary hidden hazards, effectively support forest fire disaster emergency treatment, and the method has good timeliness and generalizability. It is an emergency decision-making for forest fire fighting. Disaster prevention and mitigation activities such as effective deployment of fighting forces, scientific decision-making, prediction of secondary hazards after fire, and post-disaster reconstruction provide important decision support basis for disaster prevention and mitigation activities.

مفهوم

high-scoring remote sensing technology;mianning fire;emergency fire fighting;debris flow after the fire;pre-judgment of hidden dangers

References

  1. 1.
    Chen Y Y. 2018. Study on remote sensing monitoring of forest fire and simulation of fire spread and estimation after forest fire disaster. Huhhot: Inner Mongolia University
  2. 2.
    Chen X F, Liu L, Li J G, Ou W H and Zhang Y H. 2020. Application and research progress of fire monitoring using satellite remote sensing. Journal of Remote Sensing, 24(5): 531-542
  3. 3.
    Dong X R. 2018. Forest fire monitoring system based on FY3 remote sensing image. Harbin: Harbin Engineering University
  4. 4.
    Hu X W, Jin T, Yin W Q, Huo Z B, Song Y P, Zhang S K, Wang Y and Yang Y. 2020. The characteristics of forest fire burned area and susceptibility assessment of post-fire debris flow in Jingjiu township, Xichang city. Journal of Engineering Geology, 28(4): 762-771
  5. 5.
    Liu M and Jia D. 2018. Application of remote sensing technology in forest fire fighting. City and Disaster Reduction, (6): 66-70
  6. 6.
    Mo W H, Ma L J, He L and Tan Z K. 2001. Introduction to the satellite remote-sensing forest fire detection system of Guangxi based on GIS. Journal of Guangxi Meteorology, 22(3): 56-57
  7. 7.
    Qin X L, Li X T, Liu S C, Liu Q and Li Z Y. 2020. Forest fire early warning and monitoring techniques using satellite remote sensing in China. Journal of Remote Sensing, 24(5): 511-520
  8. 8.
    Rao Y M, Wang C and Huang H G. 2020. Forest fire monitoring based on multisensor remote sensing techniques in Muli County, Sichuan Province. Journal of Remote Sensing, 24(5): 559-570
  9. 9.
    Ren Y. 2018. The disaster mechanism and risk assessment of Sejiao post-fire debris flow in Jiulong, Sichuan. Chengdu: Southwest Jiaotong University(任云. 2018. 四川九龙县色脚沟火后泥石流成灾机理及危险性评价. 成都: 西南交通大学)
  10. 10.
    Sun W W, Yang G, Chen C, Chang M H, Huang K, Meng X Z and Liu L Y. 2020. Development status and literature analysis of China’s earth observation remote sensing satellites. Journal of Remote Sensing, 24(5): 479-510
  11. 11.
    Tang Y, Wang L J, Ma G C, Jia H J and Jin X. 2019. Emergency monitoring of high-level landslide disasters in Jinsha River using domestic remote sensing satellites. Journal of Remote Sensing, 23(2): 252-261
  12. 12.
    Tang Y, Wang L J, Zhao J and Wang A L. 2021. Monitoring “3·28
  13. 13.
    Wang L N and Sun D. 2006. Application of GIS and RS techniques to forest fire monitoring and decision assistant system in Heilongjiang province. Forest Fire Prevention, (2): 23-25
  14. 14.
    Wang Z L, Wang L J and Tang Y. 2020. On emergency monitoring of “12.5” forest fire disaster in Foshan area, Guangdong province based on domestic high score data. City and Disaster Reduction, (3): 41-45
  15. 15.
    Wu J W, Feng R, Sun L Y, Ji R P, Yu W Y, Yuan Y and Zhang Y S. 2018. Fire forest remote sensing monitoring based on Himawari-8 and GF-1 satellites. Journal of Catastrophology, 33(4): 53-59
  16. 16.
    Yang W and Jiang X L. 2018. Review on remote sensing information extraction and application of the burned forest areas. Scientia Silvae Sinicae, 54(5): 135-142

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