Study on Application of AOD Information in Forest Fire Detection

  • ZHANG Jie ,
  • ZHANG Wenyu ,
  • WANG Yanfeng ,
  • FAN Guangzhou ,
  • HAN Tingting ,
  • LIU Haiwen
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  • Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China;2. College of Atmospheric Sciences, Chengdu University of Information Technology, Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu 610225, China

Received date: 2013-05-24

  Online published: 2015-06-28

Abstract

The limitation of existing MODIS fire detection algorithm appears when it is applied to monitor forest fires in different season or in different regions. In response to these problems, the smoke plume identification in forest fires over complex surface types is studied to improve detection ability of open flame fire spots and cool smouldering fire spots. According to the effect of smoke plume diffusion on atmospheric aerosol distribution, a detection method for the smoke plume is offered as potentiating tools to identify fire pixels by extracting atmospheric Aerosol Optical Depth (AOD) information from fire areas. Based on the 6S (Second Simulation of a Satellite Signal in the Solar Spectrum) radioactive transfer model, the Dark Target (DT) method is used to retrieve AOD form MODIS data in many fire spots and background areas. In addition, the sensitivity of AOD cumulative effect to the smoke plume diffusion in different azimuth directions and different diffusion ranges is discussed. The results show that AOD retrieved by DT method could stand for the distribution characters of smoke volume, as well as indicate the direction and the rough range of smoke spread. The values of AOD in 32 azimuth directions are accumulated when the distance from the centre is 10 km, if the true fire spots are thought as the centre of a circle. The most remarkable difference of AOD cumulative value is found by comparing the leeward side to the windward side. The ratio of the two is more than ten to one. So it will provide an effective auxiliary criterion for MODIS fire detection algorithm to avoid missing disperse fire spots, especially cool fire spots.

Cite this article

ZHANG Jie , ZHANG Wenyu , WANG Yanfeng , FAN Guangzhou , HAN Tingting , LIU Haiwen . Study on Application of AOD Information in Forest Fire Detection[J]. Plateau Meteorology, 2015 , 34(3) : 797 -803 . DOI: 10.7522/j.issn.1000-0534.2014.00023

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