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Remote Sensing Technology and Application  2008, Vol. 23 Issue (5): 500-504    DOI: 10.11873/j.issn.1004-0323.2008.5.500
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)
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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     
Received:  10 April 2008      Published:  07 November 2011
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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.

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