期刊
INTERNATIONAL JOURNAL OF WILDLAND FIRE
卷 25, 期 5, 页码 505-519出版社
CSIRO PUBLISHING
DOI: 10.1071/WF15121
关键词
climate factors; driving factors; forest fire prediction; prediction accuracy; wildfire ignition
类别
资金
- National Natural Science Foundation of China [31400552]
- Natural Science Foundation of Fujian Province [2015J05049]
- Special Funding for Universities by Fujian Education Department [JK2014012]
We applied logistic regression and Random Forest to evaluate drivers of fire occurrence on a provincial scale. Potential driving factors were divided into two groups according to scale of influence: 'climate factors', which operate on a regional scale, and 'local factors', which includes infrastructure, vegetation, topographic and socioeconomic data. The groups of factors were analysed separately and then significant factors from both groups were analysed together. Both models identified significant driving factors, which were ranked in terms of relative importance. Results show that climate factors are the main drivers of fire occurrence in the forests of Fujian, China. Particularly, sunshine hours, relative humidity (fire seasonal and daily), precipitation (fire season) and temperature (fire seasonal and daily) were seen to play a crucial role in fire ignition. Of the local factors, elevation, distance to railway and per capita GDP were found to be most significant. Random Forest demonstrated a higher predictive ability than logistic regression across all groups of factors (climate, local, and climate and local combined). Maps of the likelihood of fire occurrence in Fujian illustrate that the high fire-risk zones are distributed across administrative divisions; consequently, fire management strategies should be devised based on fire-risk zones, rather than on separate administrative divisions.
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