Abstract
This paper summarizes the fuel type systems currently adopted by the fire danger rating systems or fire behavior prediction systems of some countries, such as Canada, the United States, Australia, Greece, and Switzerland. As an example, the Canadian Forest Fire Danger Rating System organizes fuel types into five major groups, with a total of 16 discrete fuel types recognized. In the United States National Fire Danger Rating System, fuel models are divided into four vegetation groups and twenty fire behavior fuel models. The Promethus System (Greece) divides fuels into 7 types, and Australia has adopted only three distinct fuel types: open grasslands, dry eucalyptus forests, and heath/shrublands. Four approaches to mapping fuels are acceptable: field reconnaissance, direct mapping methods, indirect mapping methods, and gradient modeling. Satellite remote-sensing techniques provide an alternative source of obtaining fuel data quickly, since they provide comprehensive spatial coverage and enough temporal resolution to update fuel maps in a more efficient and timely manner than traditional aerial photography or fieldwork. Satellite sensors can also provide digital information that can be easily tied into other spatial databases using Geographic Information System (GIS) analysis, which can be used as input in fire behavior and growth models. Various fuel-mapping methods from satellite remote sensing are discussed in the paper. According to the analysis of the fuel mapping techniques worldwide, this paper suggests that China should first create appropriate fuel types for its fire agencies before embarking on developing a national fire danger rating system to improve the current data situation for it's fire management programs.
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Fundation item: This paper was supported by the Beijing Fund of Nature Science (No. 6042025), China NKBRSF Project (No. 2001CB409600) and Laboratory of Forest Protection, State Forestry Administration.
Biography: TIAN Xiao-rui (1971-), Corresponding author, male, Ph. Doctor, associate professor in Research Institute of Forestry Protection, Chinese Academy of Forestry, Beijing 100091, P.R. China.
Responsible editor: Chai Ruihai
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Xiao-rui, T., McRae, D.J., Li-fu, S. et al. Fuel classification and mapping from satellite imagines. Journal of Forestry Research 16, 311–316 (2005). https://doi.org/10.1007/BF02858198
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DOI: https://doi.org/10.1007/BF02858198