Since 1980 an average of 8,600 woodland fires have occurred annually across Canada, which burn approximately 2.5 million hectares of forest (Canadian Council of Forest Ministers, 2006). In 2018, Alberta, Canada witnessed a total of 1,286 fires within its borders during the official fire season, which encompasses the months of April to October (Albert-Green et al, 2013). These fires were either human or lightning-caused, 61 percent and 39 percent respectively. The severity of these fires was linked to decreased levels of humidity, lack of rainfall, low moisture content, slope, wind speed, and wind direction (Alberta Fire, 2018; Beverly, J., 2009). Climate models suggest that the threat of forest fire is increasing each season. The area of boreal, mixedwood, taiga, and coniferous forest that is burned each year is projected to increase, signifying that the health, welfare, and quality of the environment in Canada may decline in the near future (Krawchuk, 2011).
Due to the unpredictable nature of wildfires, especially those that threaten the wildland/urban interface, residential, industrial, or agricultural areas that are located in close proximity to wildland settings are of primary concern (Westhaver, 2017; Partners in Protection, 2003). Large areas can be seriously affected by fire in a very short period of time, resulting in considerable impacts on forest-based or isolated communities, infrastructure, forest resources, extraction industries, and economic activity overall (Beverly et al, 2009).
A prime example of this is Fort McMurray, the industrial and financial hub of the Regional Municipality of Wood Buffalo. Although located approximately 300 kilometers southeast of Mackenzie County, this area faces similar issues in regards to wildfire. Early in May 2016 this community experienced the largest of several increasingly disastrous wildland/urban interface fires in Western Canada (Westhaver, 2017). In only three days, mandatory evacuation orders were released, forcing over 90,000 people to leave the area immediately (Westhaver, 2017). At the conclusion of the fire, more than 2,400 structures were destroyed costing a total of $9.9 billion dollars, approximately half of that cost representing insured losses (Westhaver, 2017).
This fire did not directly impact Mackenzie County, but the enormity of this event serves as a reminder that more effective fire protocols are required in Alberta, those of which better estimate the likelihood of fire ignitions in communities with extensive wildland/urban interface zones, some examples being Fort Vermillion, Habay, Rainbow Lake, and High Level among many others.
It is challenging to collect the data needed for studies of likelihood and susceptibility. The data required to calculate these values is extensive. At times it is challenging to find historical data from specific areas, as well as records that describe the humidity, rainfall, and vegetative moisture content that are all recorded during the same time period. As such, for the purposes of this study we will be focusing on data that overlap as much as possible. More importantly however, the spatial distribution of the data often fails to be even across the study area, creating a bias towards more populated areas.
Additionally the concepts of susceptibility, likelihood, and vulnerability are all heavily debated within the scientific community (Fuchs, 2012). Each concept is used in various disciplines, those of which focus on either a technical (physical) or social field of study, resulting in a range of paradigms for either a qualitative or quantitative assessment of vulnerability (Fuchs, 2012). One must be aware that efforts to reduce exposure to hazards such as fire requires intersections among the technical and social fields, since human activity cannot be considered independently from environmental settings (Fuchs, 2012). Acknowledging different roots of disciplinary paradigms, methods of determining structural, environmental, and economic vulnerability of both susceptibility and likelihood is key to creating a substantial vulnerability assessment (Fuchs, 2012).
Geographic information systems (GIS) combined with remote sensing strategies and fire behaviour models have been used to rate fire susceptibility at individual locations using various types of spatial data, some examples being humidity, rainfall, wind, and temperature extremes (Chuvieco et al, 1989). Statistical models have also been used to map the variations in fire susceptibility and likelihood as well. These models often contain data that is focused on vegetation, weather, topography, and human activity in locations where fires have occurred in the past (Beverly, 2009). In regions where fires have dramatic and continual impacts on communities and their surroundings, statistical models can be created that can predict the approximate level of vulnerability in a given area, as well as current or projected future conditions (Beverly, 2009).
Conducting a vulnerability analysis using GIS and remote sensing technologies will not only be beneficial to the Federal and Provincial governments in Canada, but will also be of considerable use in remote communities in Alberta, where a significant interest in reducing wildland/urban interface fires exists.