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A comparison of forest fire indices for predicting fire risk in contrasting climates in China

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  • Xiaowei Li
  • Gang Zhao
  • Xiubo Yu
  • Qiang Yu

Abstract

The relationships between fire danger indices and fire risk have been extensively studied in many regions of the world. This work uses partial effect analysis in semiparametric logistic regression models to assess the nonlinear relationships among location, day, altitude, fire danger indices, normalized difference vegetation index (NDVI), and fire ignition from 1996 to 2008 in four different climatic regions in China. The four regions are North China (NR), Northeast China (NE), Southeast China (SE), and Southwest China (SW). The three main results are as follows: First, different fire danger indices are selected as significant variables dependent on the region. The inter-regional difference could be partially explained by difference in local weather and vegetation conditions. Second, spatial location exerts highly significant effects in all four regions. NDVI values are selected as explained variable for NR, NE, and SE on fire ignitions. On a daily scale, altitude influences fire ignition for NR, SE, and SW. Third, the robustness of the probability models used in NE, SE, and SW is better than that in NR on a daily scale. The semiparametric logistic regression model used in this study is useful for assessing the ability of fire danger indices to estimate probabilities of fire ignition on a daily scale. This study encourages further research on assessing the predictive ability of fire danger indices developed at other temporal and spatial scales in China. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Xiaowei Li & Gang Zhao & Xiubo Yu & Qiang Yu, 2014. "A comparison of forest fire indices for predicting fire risk in contrasting climates in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(2), pages 1339-1356, January.
  • Handle: RePEc:spr:nathaz:v:70:y:2014:i:2:p:1339-1356
    DOI: 10.1007/s11069-013-0877-6
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    References listed on IDEAS

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    1. Christos Vasilakos & Kostas Kalabokidis & John Hatzopoulos & Ioannis Matsinos, 2009. "Identifying wildland fire ignition factors through sensitivity analysis of a neural network," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 50(1), pages 125-143, July.
    2. Kirsten Thonicke & Wolfgang Cramer, 2006. "Long-term Trends in Vegetation Dynamics and Forest Fires in Brandenburg (Germany) Under a Changing Climate," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 38(1), pages 283-300, May.
    3. Litao Wang & Yi Zhou & Weiqi Zhou & Shixing Wang, 2013. "Fire danger assessment with remote sensing: a case study in Northern China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(1), pages 819-834, January.
    4. De Angelis, Antonella & Bajocco, Sofia & Ricotta, Carlo, 2012. "Modelling the phenological niche of large fires with remotely sensed NDVI profiles," Ecological Modelling, Elsevier, vol. 228(C), pages 106-111.
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