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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

An evaluation of spatial and temporal patterns of lightning- and human-caused forest fires in Alberta, Canada, 1980–2007

Yonghe Wang A B and Kerry R. Anderson A
+ Author Affiliations
- Author Affiliations

A Northern Forestry Centre, Canadian Forest Service, 5320 122nd Street, Edmonton, AB, T6H 3S5, Canada.

B Corresponding author. Email: ywang@nrcan.gc.ca

International Journal of Wildland Fire 19(8) 1059-1072 https://doi.org/10.1071/WF09085
Submitted: 5 August 2009  Accepted: 8 July 2010   Published: 10 December 2010

Abstract

We used the K-function and kernel estimation methods to evaluate the spatial and temporal patterns of ignition locations of lightning- and human-caused forest fires in Alberta, Canada. Although both of these fire types have spatial patterns of cluster distribution, quantitative measures for evaluating the patterns in the province are lacking. Our results revealed annual differences in the spatial patterns between the two fire types, whereby fires caused by humans tended to be more clustered and had more complex spatial patterns than those caused by lightning. Spatial interactions of cluster and inhibition existed between the two fire types. Human-caused fires in the period 2003–07 were highly concentrated in the southern parts of the province, indicating the existence of an interaction between space and time. Kernel analysis confirmed the observation that in northern Alberta, lightning-caused fires were more likely to occur than human-caused fires; the opposite was true in southern Alberta. This study provided useful spatial information that is not obvious or cannot be inferred from visual examination of raw data. Such quantitative knowledge could lead to the development of fire-response and fire-suppression strategies appropriate to specific regions within the province.

Additional keywords: Alberta Wildfire Management Areas, K-function, kernel estimation, spatial intensity, spatial point patterns.


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