BioOne.org will be down briefly for maintenance on 17 December 2024 between 18:00-22:00 Pacific Time US. We apologize for any inconvenience.
How to translate text using browser tools
1 June 2012 Probability Models of Fire Risk Based on Forest Fire Indices in Contrasting Climates over China
Li Xiaowei, Fu Guobin, Melanie J. B. Zeppel, Yu Xiubo, Zhao Gang, Derek Eamus, Yu Qiang
Author Affiliations +
Abstract

Fire weather indices have been widely applied to predict fire risk in many regions of the world. The objectives of this study were to establish fire risk probability models based on fire indices over different climatic regions in China. We linked the indices adopted in Canadian, US, and Australia with location, time, altitude, vegetation and fire characteristics during 1998–2007 in four regions using semi— parametric logistic (SPL) regression models. Different combinations of fire risk indices were selected as explanatory variables for specific regional probability model. SPL regression models of probability of fire ignition and large fire events were established to describe the non—linear relationship between fire risk indices and fire risk probabilities in the four regions. Graphs of observed versus estimated probabilities, fire risk maps, graphs of numbers of large fire events were produced from the probability models to assess the skill of these models. Fire ignition in all regions showed a significant link with altitude and NDVI. Indices of fuel moisture are important factors influencing fire occurrence in northern China. The fuel indices of organic material are significant indicators of fire risk in southern China. Besides the well skill of predicting fire risk, the probability models are a useful method to assess the utility of the fire risk indices in estimating fire events. The analysis presents some of the dynamics of climate-fire interactions and their value for management systems.

Li Xiaowei, Fu Guobin, Melanie J. B. Zeppel, Yu Xiubo, Zhao Gang, Derek Eamus, and Yu Qiang "Probability Models of Fire Risk Based on Forest Fire Indices in Contrasting Climates over China," Journal of Resources and Ecology 3(2), 105-117, (1 June 2012). https://doi.org/10.5814/j.issn.1674-764x.2012.02.002
Received: 3 May 2012; Accepted: 1 May 2012; Published: 1 June 2012
KEYWORDS
Climate
fire risk indices
forest fire
meteorological risk
semi—parametric logistic regression model
RIGHTS & PERMISSIONS
Get copyright permission
Back to Top