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遥感技术与应用  2008, Vol. 23 Issue (5): 500-504    DOI: 10.11873/j.issn.1004-0323.2008.5.500
技术研究与图像处理     
国家级森林火险等级预报方法研究
覃先林1,张子辉2,李增元1,易浩若1
(1.中国林业科学研究院资源信息研究所,林业部重点开放性实验室—林业遥感与信息技术实验室,北京 100091;2.国家林业局森林防火预警监测信息中心,北京 100714)
Forecasting Methodology of National-level Forest Fire Risk Rating
QIN Xian-lin1,ZHANG Zi-hui2,LI Zeng-yuan1,YI Hao-ruo1
 (1.Research Institute of Forest Resource Information Technology,State Laboratory for Remote Sensing and Information Technology,CAF,Beijing 100091,China;2.Information Center of Forest FirePrediction and Monitoring,State Forestry Administration,Beijing 100714,China)
 全文: PDF(569 KB)  
摘要:

对国家级森林火险等级的定量化预报方法进行了探讨,即:利用MODIS数据反演获得可燃物状态指数;将通过网络获得的全国气象数据和建立的可燃物类型分布、森林火险区划等基础数据库,在ArcGIS平台上数量化后计算背景综合指数,由这两者计算获得火险指数,以火险指数为国家级森林火险等级预报的量化指标,并利用它进行全国森林火险等级的分级,从而实现了全国森林火险等级从定性描述到定量估测。同时,以近几年我国发生的重特大森林火灾为例,对该方法进行了验证。实验表明:该方法可较好地对国家级森林火险等级进行定量化预报。

关键词: 森林火险指数森林火险预报MODISGIS技术    
Abstract:

The risk level of forest fire depends not only on weather,topography,human activities,socio-economic conditions,but also closely related to the types,growth,moisture content,and quantity of forest fuel on the ground.How to timely acquire information on the dynamics of growth and moisture content of forest fuel and climate in the whole country is critical to national-level forest fire risk forecasting.The development and application of Remote Sensing (RS),geographic information system (GIS),databases,Internet,and other modern information technologies has provided- an important technical means for macro-regional forest fire risk forecasting.Quantified forecasting of national-level forest fire risk was studied using Fuel State Index (FSI) and Background Composite Index (BCI).The FSI was estimated using MODerate resolution Imaging Spectroradiaometer (MODIS) data.National meteorological data and other basic data on distribution of fuel types and forest fire risk rating were standardized in ArcGIS platform to calculate BCI.The FSI and the BCI were used to calculate the Forest Fire Danger Index (FFDI),which is regarded as a quantitative indicator for national forest fire risk forecasting and forest fire risk rating,shifting from qualitative description to quantitative estimation.The major forest fires occurred in recent years was taken as examples to validate the above method,and results indicated that the method can be used for quantitative forecasting of national-level forest fire risks.

Key words: Forest fire danger index    Forest fire risk forecasting    MODIS    GIS
收稿日期: 2008-04-10 出版日期: 2011-11-07
:  TP 79  
基金资助:

得到“十一五”国家科技攻关课题“森林灾害监测、预警技术研究(2006BAD23B04);中国林科院院科研基金重点项目“院属实验林重要资源和林火预警监测技术研究(CAFYBB2007003)”;中欧科技合作项目“龙计划”中“中国森林火灾卫星监测及示范”课题(Dragon Proposal id 2531)和ITTO 项目“中国热带林火卫星遥感监测与管理系统(PD 228/03 Rev.3 (F))” 的资助。

作者简介: 覃先林(1969-),男,博士,副研究员,主要从事卫星遥感技术在森林及林火预警监测中的应用方法研究。E-mail:noaags@caf.ac.cn。
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引用本文:

覃先林,张子辉,李增元,易浩若. 国家级森林火险等级预报方法研究[J]. 遥感技术与应用, 2008, 23(5): 500-504.

QIN Xian-lin,ZHANG Zi-hui,LI Zeng-yuan,YI Hao-ruo. Forecasting Methodology of National-level Forest Fire Risk Rating. Remote Sensing Technology and Application, 2008, 23(5): 500-504.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2008.5.500        http://www.rsta.ac.cn/CN/Y2008/V23/I5/500

[1] Song Z J.Principle and Prediction of Forest Fire[M].Meteorological Publishing House,1991.[宋志杰.林火原理和林火预报[M].气象出版社,1991.]
[2] Robert E B.1988 Revisions to the 1978 National Fire Danger Rating System[S].USDA Forest Service.1988.
[3] Robert E B,Robert W K,Jacqueline M K.Fuel Models and Fire Potential from Satellite and Surface Observations[J].International Journal of Wildland Fire,1998,8(3):159-170.
[4] Carlson J D,Robert E B,David M E,etal.The Oklahoma Fire Danger Model:An Operational Tool for Mesoscale Fire Danger Rating in Oklahoma[J].International Journal of Wildland Fire,2002,11:183-191.
[5] Jack D C,John E D.The National Fire Danger Rating System:Basic Equations[S].USDA Forest Service.2002.
[6] The Missoula Fire Sciences Lab and SEM[Z].http://www.wfas.net/.2008.8.1.
[7] Stocks B J.Canadian Forest Fire Danger Rating System Users'Guide[S].Canadia Forest Service Fire Danger Group.1987.
[8] Canadian Forest Service[Z].http://cwfis.cfs.nrcan.gc.ca/en/background/bi_FWI_summary_e.php.2008.8.1.
[9] Vidal A,Pinglo F,Durand H,etal.Evaluation of a Temporal Fire Risk Index in Mediterranean Forest from NOAA Thermal IR[J].Remote Sensing of Environment,1994,49:296-303.
[10] Maselli F,Rodolfi A,Conese C.Evaluation of Forest Fire Risk by the Analysis of Environmental Data and TM Images[J].International Journal of Remote Sensing,1996,17(7):1417-1423.
[11] Sudiana D,Kuze H,Takeuchi N,et al.Assessing Forest Potential in Kalimantan Island. Indonesia. Using Satellite and Surface Weather Data[J].International Journal of Wildland Fire,2003,12:175-184.
[12] European Communities. http://effis. jrc. ec. europa. eu/index.php.2008.8.1.
[13] Wang Z F.Three-index Method of Predicting Forest Fires,Journal of Ecology[J].1988,7(Supp.):75-81.[王正非.三指标林火预报法[J].生态学杂志,1988,7(增):75-81.]
[14] Wen G Y,Hou X M,Chen H H.The Application of Artificial Nervous Net to Forecasting Forest Fire[J].Journal of Biomathematics,2001,16(2):225-228.[温广玉,侯锡明,陈华豪.人工神经网络在林火发生预报中的应用[J].生物数学学报,2001,16(2):225-228.]
[15] Zheng H Q,Zhang C G,Chen J J ,et al.Study on Monitoring of Forest Fire Ranks in Fujian Using NOAA-AVHRR Data[J].Journal of Fujian College of Forestry,2003,23(2):114-118.[郑海青,张春桂,陈家金,等.利用NOAA卫星遥感监测福建省森林火险[J].福建林学院学报,2003,23(2):114-118.]
[16] Zhou W Q, Zhou Y, Wang S X,et al. Early Warning for Grassland Fire Danger In North China Using Remote Sensing[J].IEEE,2003,3:2505-2507.
[17] Wang L T,Zhou Y,Wang S X,etal.Monitoring for Grassland and Forest Fire Danger Using Remote Sensing Data [J].IEEE,2004,2:2095-2098.
[18] Zhou Y,Chen S R,Zhou W Q,etal.Early Warning and Monitoring System for Forest and Grassland Fires by Remote Sensing Data[J].IEEE,2004,2:4799-4802.
[19] Yi H R,Ji P,Qin X L.Study on the National Forest Fire Danger Forecast System and Its Operation[J].Forest Science.2004,40(3):203-207.[易浩若,纪平,覃先林.全国森林火险预报系统的研究与运行[J].林业科学,2004,40(3):203-207.]
[20] Qin X L.Study on Forest Fire Early Warning and Monitoring Methodology Using Remote Sensing and Geography Information System Techniques[D].PHD Paper of Chinese Academy of Forestry,2005.[覃先林.遥感与地理信息系统技术相结合的林火预警方法的研究[D].中国林业科学研究院博士学位论文,2005.]
[21] Guo G M,Zhou M.Using MODIS Land Surface Temperature to Evaluate Forest Fire Risk of Northeast China[J].Geo-science and Remote Sensing Letters,IEEE,2005,1(2):98-100.
[22] Liu Y J,Yang Z D.MODIS Remote Sensing Information Processing Theory and Arithmetic[M].Beijing:Chinese Science and Techniques Publishing House,2001.[刘玉洁,杨忠东.MODIS遥感信息处理原理与算法[M].北京:科学出版社,2001.]
[23]    Land Processes Distributed Active Archive Center[Z]. http://edcimswww.cr.usgs.gov/pub/imswelcome/.2008.
[24] Wang X X,Liu Z Z,Wu S Y,et al.National Forest Fire Risk Weather Danger (LY/T 1172-95 ) [S]. Beijing: Standards Press of China,1996.[王贤祥,刘志忠,吴士英,等.林业部森林防火办公室提出,中华人民共和国林业行业标准·全国森林火险天气等级( LY/T 1172-95 )[S].北京:中国标准出版社,1996.]

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