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

Li, X; Zhao, G; Yu, X; Yu, Q

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

Li, X Zhao, G Yu, X Yu, Q

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Publication Type:: Journal Article
Citation:: Natural Hazards, 2014, 70 (2), pp. 1339 - 1356
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Li, X	en_US
dc.contributor.author	Zhao, G	en_US
dc.contributor.author	Yu, X	en_US
dc.contributor.author	Yu, Q https://orcid.org/0000-0001-6950-1821	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Natural Hazards, 2014, 70 (2), pp. 1339 - 1356	en_US
dc.identifier.issn	0921-030X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/36165
dc.description.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. © 2013 Springer Science+Business Media Dordrecht.	en_US
dc.relation.ispartof	Natural Hazards	en_US
dc.relation.isbasedon	10.1007/s11069-013-0877-6	en_US
dc.subject.classification	Strategic, Defence & Security Studies	en_US
dc.title	A comparison of forest fire indices for predicting fire risk in contrasting climates in China	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	70	en_US
utslib.for	070503 Forestry Fire Management	en_US
utslib.for	0401 Atmospheric Sciences	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	en_US
utslib.for	1701 Psychology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	70	en_US

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. © 2013 Springer Science+Business Media Dordrecht.

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http://hdl.handle.net/10453/36165