Risk assessment for wildland fire aerial detection patrol route planning in Ontario, Canada

This study presents a model developed using a risk-based framework that is calibrated by experts, and provides a spatially explicit measure of need for aerial detection daily in Ontario, Canada. This framework accounts for potential fire occurrence, behaviour and impact as well as the likelihood of detection by the public. A three-step assessment process of risk, opportunity and tolerance is employed, and the results represent the risk of not searching a specified area for the detection of wildland fires. Subjective assessment of the relative importance of these factors was elicited from Ontario Ministry of Natural Resources and Forestry experts to develop an index that captures their behaviour when they plan aerial detection patrol routes. The model is implemented to automatically produce a province-wide, fine-scale risk index map each day. A retrospective analysis found a statistically significant association between points that aerial detection patrols passed over and their aerial detection demand index values: detection patrols were more likely to pass over areas where the index was higher.

[1]  S. Kaplan,et al.  On The Quantitative Definition of Risk , 1981 .

[2]  Douglas G. Woolford,et al.  A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain , 2010 .

[3]  David L. Martell,et al.  A lightning fire occurrence model for Ontario , 2005 .

[4]  George M. Parks,et al.  Development and Application of a Model for Suppression of Forest Fires , 1964 .

[5]  Steven G. Cumming,et al.  Effective fire suppression in boreal forests , 2005 .

[6]  Matthew P. Thompson,et al.  Risk Preferences, Probability Weighting, and Strategy Tradeoffs in Wildfire Management , 2015, Risk analysis : an official publication of the Society for Risk Analysis.

[7]  Kevin G. Tolhurst,et al.  Operational wildfire suppression modelling: a review evaluating development, state of the art and future directions , 2015 .

[8]  Douglas G. Woolford,et al.  Statistical Models of Key Components of Wildfire Risk , 2019, Annual Review of Statistics and Its Application.

[9]  David L. Martell,et al.  The impact of fire suppression, vegetation, and weather on the area burned by lightning-caused forest fires in Ontario , 2008 .

[10]  Jiguo Cao,et al.  Lightning‐caused forest fire risk in Northwestern Ontario, Canada, is increasing and associated with anomalies in fire weather , 2014 .

[11]  Dave Schroeder Evaluation of three wildfire smoke detection systems , 2004 .

[12]  Matthew P. Thompson,et al.  Integrated wildfire risk assessment: Framework development and application on the Lewis and Clark National Forest in Montana, USA , 2013, Integrated environmental assessment and management.

[13]  Lynn A Maguire,et al.  Managing Wildfire Events: Risk‐Based Decision Making Among a Group of Federal Fire Managers , 2011, Risk analysis : an official publication of the Society for Risk Analysis.

[14]  F. Hasson,et al.  Research guidelines for the Delphi survey technique. , 2000, Journal of advanced nursing.

[15]  S. Dreyfus The Five-Stage Model of Adult Skill Acquisition , 2004 .

[16]  Robert S. Allison,et al.  Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring , 2016, Sensors.

[17]  David L. Martell,et al.  Productivity of Ontario initial-attack fire crews: results of an expert-judgement elicitation study , 2004 .

[18]  M. Finney,et al.  Wildfire Exposure Analysis on the National Forests in the Pacific Northwest, USA , 2013, Risk analysis : an official publication of the Society for Risk Analysis.

[19]  David R. Brillinger,et al.  Probability based models for estimation of wildfire risk , 2004 .

[20]  Lynn A. Maguire,et al.  Can behavioral decision theory explain risk-averse fire management decisions? , 2005 .

[21]  David L. Martell,et al.  Using Expert Judgment to Model Initial Attack Fire Crew Effectiveness , 1998, Forest Science.

[22]  Youmin Zhang,et al.  A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques , 2015 .

[23]  Stan Boutin,et al.  Empirical models of forest fire initial attack success probabilities : the effects of fuels, anthropogenic linear features, fire weather, and management , 2006 .

[24]  John Handmer,et al.  A review of operations research methods applicable to wildfire management , 2012 .

[25]  C. Hardy Wildland fire hazard and risk: Problems, definitions, and context , 2005 .

[26]  Ahmad A. A. Alkhatib A Review on Forest Fire Detection Techniques , 2014, Int. J. Distributed Sens. Networks.

[27]  Gary Klein,et al.  Expert decision making , 1999 .

[28]  José G. Borges,et al.  Cohesive fire management within an uncertain environment: A review of risk handling and decision support systems , 2015 .

[29]  Matthew P. Thompson,et al.  Rethinking the Wildland Fire Management System , 2018, Journal of Forestry.

[30]  Douglas G. Woolford,et al.  Impacts of wildland fire effects on resources and assets through expert elicitation to support fire response decisions , 2019, International Journal of Wildland Fire.

[31]  D. Martell,et al.  Factors that affect the timing of the dispatch of initial attack resources to forest fires in northeastern Ontario, Canada , 2019, International Journal of Wildland Fire.

[32]  D. Kahneman,et al.  Conditions for intuitive expertise: a failure to disagree. , 2009, The American psychologist.

[33]  Peter Kourtz The Need for Improved Forest Fire Detection , 1987 .

[34]  Lynn M. Johnston,et al.  Satellite Detection Limitations of Sub-Canopy Smouldering Wildfires in the North American Boreal Forest , 2018, Fire.

[35]  Mike D. Flannigan,et al.  Mapping Canadian wildland fire interface areas , 2017 .

[36]  Matthew P. Thompson,et al.  A real-time risk assessment tool supporting wildland fire decisionmaking , 2011 .

[37]  David L. Martell,et al.  An index for tracking sheltered forest floor moisture within the Canadian Forest Fire Weather Index System , 2005 .

[38]  David Martell The development and implementation of forest and wildland fire management decision support systems: reflections on past practices and emerging needs and challenges , 2011, Math. Comput. For. Nat. Resour. Sci..

[39]  Douglas G. Woolford,et al.  Wildfire Prediction to Inform Fire Management: Statistical Science Challenges , 2013, 1312.6481.

[40]  Justin Podur,et al.  Will climate change overwhelm fire management capacity , 2010 .

[41]  David L. Martell,et al.  A review of operational research studies in forest fire management , 1982 .

[42]  Martin E. Alexander,et al.  Calculating and interpreting forest fire intensities , 1982 .

[43]  David L. Martell,et al.  A Review of Initial Attack Fire Crew Productivity and Effectiveness , 1996 .

[44]  Mark A. Finney,et al.  The challenge of quantitative risk analysis for wildland fire , 2005 .

[45]  N. Shadbolt,et al.  Eliciting Knowledge from Experts: A Methodological Analysis , 1995 .