Plateau Meteorology

Plateau Meteorology >

2015 , Vol. 34 >Issue 3: 797 - 803

DOI: https://doi.org/10.7522/j.issn.1000-0534.2014.00023

Study on Application of AOD Information in Forest Fire Detection

  • ZHANG Jie ,
  • ZHANG Wenyu ,
  • WANG Yanfeng ,
  • FAN Guangzhou ,
  • HAN Tingting ,
  • LIU Haiwen
Expand
  • 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

Fold

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.

Key words： Forest fires; Aerosol Optical Dept; Smoke plume detectio

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

References

[1]Kaufman Y J, Justice C O, Flynn L P, et al. Potential global fire monitoring from EOS-MODIS[J]. J Geophys Res, 1998, 103(D24): 32215-32238.
[2]Justice C O, Giglio L, Korontzi S, et al. The MODIS fire products[J]. Remote Sens Environ, 2002, 83(1): 244-262.
[3]王宏斌, 张镭, 刘瑞金, 等. 中国地区两种MODIS气溶胶产品的比较分析[J]. 高原气象, 2011, 30(3): 772-783.
[4]胡蝶, 张镭, 王宏斌. 黄土高原干旱半干旱地区气溶胶光学厚度遥感分析[J]. 高原气象, 2013, 32(3): 654-664, doi: 10.7522/j.issn.1000-0534.2012.00062.
[5]王钊, 彭艳, 车慧正, 等. 近10年关中盆地MODIS气溶胶的时空变化特征[J]. 高原气象, 2013, 32(1): 234-242, doi: 10.7522/j.issn.1000-0534.2013.00023.
[6]Kaufman Y J, Justice C, Flynn L, et al. Monitoring global fires from EOS-MODIS[J]. J Geophys Res, 1998, 102(29): 611-624.
[7]Giglio L, David P, Quayle B, et al. An active-fire based burned area mapping algorithm for the MODIS sensor[J]. Remote Sens Environ, 2009, 12(9): 409-418.
[8]Loboda T, Gigilio L, Boschetti L, et al. Regional fire monitoring and characterization using global NASA MODIS fire products in dry lands of Central Asia[J]. Frontiers of Earth Science, 2012, 6(2): 196-205.
[9]周梅, 郭广猛, 宋冬梅, 等. 使用MODIS监测火点的几个问题探讨[J]. 干旱区资源与环境, 2006, 20(3): 180-183.
[10]高懋芳, 覃志豪, 刘三超. MODIS数据在林火监测中的应用研究[J]. 国土资源遥感, 2005(2): 60-63.
[11]覃先林, 易洁若. 基于MODIS数据的林火识别方法研究[J]. 火灾科学, 2004, 13(12): 84-89.
[12]唐中实, 王海葳, 赵红蕊, 等. 基于MODIS的重庆森林火灾监测与应用[J]. 国土资源遥感, 2008(3): 52-55.
[13]陈文波, 刘闯, Doko T, 等. 俄罗斯远东林区林火过程数值分类研究[J].资源科学, 2007, 29(5): 190-194.
[14]Boles S H, Verbyla D L. Comparison of three AVHRR-based fire detection algorithms for interior Alaska[J]. Remote Sens Environ, 2000, 72(1): 1-16.
[15]李建, 陈晓玲, 陆建忠, 等. 森林火灾遥感监测方法适用性研究[J]. 华中师范大学学报(自然科学版), 2011, 45(3): 485-496.
[16]周利霞, 高光明, 邱冬生, 等. 基于MODIS数据FPI-NDVI火灾监测方法研究[J]. 安全与环境学报, 2008, 8(2): 114-116.
[17]Wang W T, John J. An improved algorithm for small and cool fire detection using MODIS data: a preliminary study in the southeastern united states[J]. Remote Sens Environ, 2007, 108: 163-170.
[18]Kaufman Y J, Ichoku C, Giglio L, et al. Fire and smoke observed from the Earth Observing System MODIS instrument-products, validation, and operational use[J]. Int J Remote Sens, 2003, 24(8): 1765-1781.
[19]Chung Y S, Le H V. Detection of forest-fire smoke plumes by satellite imagery[J]. Atmos Environ, 1984, 18(10): 2143-2151.
[20]Chrysoulakis N, Opie C. Technical note: Using NOAA and FY imagery to track plumes caused by the 2003 bombing of Baghdad[J]. Int J Remote Sens, 2004, 25(23): 5247 5254.
[21]Kaufman Y J, Tucker C J, Fung I Y. Remote sensing of biomass burning in the tropics[J]. Adv Space Res, 1989, 9(7): 265-268.
[22]Randriambelo T, Baldy S, Bessafi M, et al. An improved detection and characterization of active fires and smoke plumes in south-eastern Africa and Madagascar[J]. Int J Remote Sens, 1998, 19(14): 2623-2638.
[23]Xie Y, Qu J J, Xiong X, et al. Smoke plume detection in the eastern United States using MODIS[J]. Int J Remote Sens, 2007, 28(10): 2367-2374.
[24]Chrysoulakis N, Cartalis C. A new algorithm for the detection of plumes caused by industrial accidents, based on NOAA/AVHRR imagery[J]. Int J Remote Sens, 2003, 24(17): 3353-3368.
[25]Li Z, Khananian A, Fraser R H, et al. Automatic detection of fire smoke using artificial neural networks and threshold approaches applied to AVHRR imagery[J]. IEEE Trans Geosci Remote Sens, 2001, 39(9): 1859-1870.
[26]王钊, 彭艳, 白爱娟, 等. 近 60 年西安日照时数变化特征及其影响因子分析[J]. 高原气象, 2012, 31(1): 185-192.
[27]郑小波, 罗宇翔, 段长春, 等. 云贵高原近 45 年来日照及能见度变化及其成因初步分析[J]. 高原气象, 2010, 29(4): 992-998.
[28]邓涛, 张镭, 吴兑, 等. 兰州地区高云和气溶胶光学特性及其辐射效应[J]. 高原气象, 2010, 29(1): 230-235.
[29]Kaufman Y J, Wald A E, Remer L A, et al. The MODIS 2.1-μm channel-correlation with visible reflectance for use in remote sensing of aerosol[J]. IEEE Trans Geosci Remote Sens, 1997, 35(5): 1286-1298.
[30]刘玉洁, 杨忠东, 等. MODIS遥感信息处理原理与算法[M]. 北京: 科学出版社, 2001.
[31]张婕, 张武, 陈权亮. 利用MODIS数据反演植被指数的敏感性研究[J]. 西南大学学报(自然科学版), 2011, 33(11): 152-158.
Options
Outlines

/

〈 〉

The system is designed and developed by Beijing magtec Technology Development Co., Ltd. with technical support: support@magtech.com.cn