Ontario Aviation Forest Fire and Emergency Services (AFFES)
Ministry of Natural Resources division managing wildland fire response, prevention and aviation services; no standalone AFFES page exists.
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Considerations for Categorizing and Visualizing Numerical Information: A Case Study of Fire Occurrence Prediction Models in the Province of Ontario, Canada
Wildland fire management decision-makers need to quickly understand large amounts of quantitative information under stressful conditions. Categorization and visualization “schemes” have long been used to help, but how they are done affects the speed and accuracy of interpretation. Using traditional fire management schemes can unduly restrict the design of new products. Our design process for Ontario’s fine-scale, spatially explicit, daily fire occurrence prediction (FOP) models led us to develop guidance for designing new schemes. We show selected historical fire management schemes and describe our method. It includes specifying goals and requirements, exploring design options and making trade-offs. The design options include gradient continuity, hue selection, range completeness and scale linearity. We apply our method to a case study on designing the scheme for Ontario’s FOP models. We arrived at a smooth, nonlinear scale that accommodates data spanning many orders of magnitude. The colouring draws attention according to levels of concern, reveals meaningful spatial patterns and accommodates some colour vision deficiencies. Our method seems simple now but reconciles complex considerations and is useful for mapping many other datasets. Our method improved the clarity and ease of interpretation of several information products used by fire management decision-makers.
Fifty years of wildland fire science in Canada
We celebrate the 50th anniversary of the Canadian Journal of Forest Research by reflecting on the considerable progress accomplished in select areas of Canadian wildland fire science over the past half century. Specifically, we discuss key developments and contributions in the creation of the Canadian Forest Fire Danger Rating System; the relationships between wildland fire and weather, climate, and climate change; fire ecology; operational decision support; and wildland fire management. We also discuss the evolution of wildland fire management in Banff National Park as a case study. We conclude by discussing some possible directions in future Canadian wildland fire research including the further evaluation of fire severity measurements and effects; the efficacy of fuel management treatments; climate change effects and mitigation; further refinement of models pertaining to fire risk analysis, fire behaviour, and fire weather; and the integration of forest management and ecological restoration with wildland fire risk reduction. Throughout the paper, we reference many contributions published in the Canadian Journal of Forest Research, which has been at the forefront of international wildland fire science.
History and overview of research and development for Ontario’s FireGUARD decision support system for appropriate response
Research and development for a real-time wildfire decision support system was undertaken to support appropriate response decision-making in Ontario, Canada. We describe the context, history, requirements, research and development process, and components of FireGUARD (Fire Growth under Uncertainty for Appropriate Response Decision Support) and show examples of its prototype products. The work was a collaborative effort between researchers, specialists, and fire management experts. FireGUARD prototype outputs include a weather forecast and high-resolution maps of burn probability out to 14 days, fuel type, impact, and risk. Additional uses of include triaging multiple new fires, prioritizing scarce suppression resources, and large fire management. FireGUARD was very useful and remains in demand; its success led to further decision-support initiatives. Supplementary materials including fact sheets and technical summaries are available on this landing page beneath the references.
Impacts of wildland fire effects on resources and assets through expert elicitation to support fire response decisions
A modelling framework to spatially score the impacts from wildland fire effects on specific resources and assets was developed for and applied to the province of Ontario, Canada. This impact model represents the potential ‘loss’, which can be used in the different decision-making methods common in fire response operations (e.g. risk assessment, decision analysis and expertise-based). Resources and assets considered include point features such as buildings, linear features such as transmission lines, and areal features such as forest management areas. Three categories of fire impacts were included: social, economic and emergency response. Category-specific scores were determined through expert elicitation and then adjusted to account for fire intensity. Expert elicitation was shown to compare favourably with other methods in terms of the complexity, time, set-up cost and operational use. When compared with historical fire data from Ontario, it was found that impact model scores were associated with the objective to suppress or monitor fires. The model framework provides a consistent pre-fire impact assessment to support individual fire response decisions. The impact assessment can also represent the total impact for areas of Ontario that do not have prescriptive response in a formal fire response plan.
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.