Wildfire

  • Using Remote Sensing Data and Raster Analysis Tools to Assess Fire Hazard Severity in South-Central British Columbia
    The Penticton region of British Columbia, Canada is an area which is experiencing increasingly worsening wildfire events. These natural disturbances represent a significant threat to local ecosystems, property and human life and wellbeing. Landscape analysis of fire hazard levels is necessary to direct emergency service management prior to and during wildfire events and to inform policy on how to manage these natural disasters. To assess fire hazard levels, a GIS-based multi-criteria analysis was performed to understand fire hazard spatially, subdivided into low, moderate, high, and severe hazard areas. Two models were built to achieve this, taking into account commonly used variables employed to assess fire hazard severity around the world. To identify potential differences in hazard assessment, the models weighted these variables differently from one another. Fire location points from the year 2000 to 2021 were overlayed with each respective model output. Model 1 spatially overlapped with 73.88% of these fires, while model 2 spatially overlapped with 74.35%. These results can help identify areas of elevated hazard under ideal burning conditions, inform deployment of emergency services and resources, and provide a framework for using a GIS to conduct a fire hazard landscape assessment.
  • Metrics of Change: Informing Ecological Restoration by Quantifying Landscapes and Processes in Banff National Park
    The landscapes in the Rocky Mountain Cordillera undergo constant change due to the intricate interplay of ecological processes, with fire being the primary disturbance agent. Fire suppression policies have impeded the ecological role of fire, resulting in increased conifer forest dominance and declines in landscape heterogeneity. The objective of this study was to develop a methodology to accurately measure regional landscape changes resulting from fire suppression and fire restoration in Banff National Park, with the goal of supporting data-informed resource management. A landscape metrics approach was selected to investigate changes across 27 management units. Four landscape metrics were calculated using annual land cover maps derived from Virtual Land Cover Engine/Landsat-5/7 imagery spanning 34 years (1984-2019). Metrics were selected to capture conifer encroachment (proportion of conifer class) and landscape heterogeneity (contagion, edge density, Shannon’s diversity index) changes. Time-series analysis and Thiel-Sen slope estimation were used to identify metric trends. The study’s resulting metrics offer resource managers additional landscape attributes to compare and monitor management units, which can support decision-making, prioritize fire restoration and inform future ecological studies.
  • Burn-P3 modelling of fire behaivour on Rose Swanson Mountain, British Columbia before and after harvesting
    It has been long known that wildfire and harvesting can have a relationship. However, this relationship is not straightforward and well understood. In this paper, we hope to quantify the impact of proposed harvesting on the wildfire severity and probability on Rose Swanson Mountain. Rose Swanson Mountain is a small mountain in South Central BC near the town of Armstrong used by the locals for its bountiful outdoor recreation. In early 2020 British Columbia Timber Sales added part of the Rose Swanson Mountain Sensitive Area to its list of soon-to-be harvested areas. This paper illustrates the research done in BurnP3 and ArcPro to simulate and measure fire in a pre and post logged Rose Swanson.
  • Vegetation Change in the Tumbler Ridge region, BC from 1940 to 2020
    In recent years, the application of remote sensing technology in vegetation change monitoring has played an important role. The purpose of this project is to explore changes in vegetation in the Tumbler Ridge region of British Columbia between the 1940s and 2020 and to discuss the relationship to fire urbanization and deforestation. A series of aerial photographs (taken in the 1940s), Landsat 5 remote sensing images (1985), and forest vegetation composite polygons (2020) were classified and analyzed by Object-Based Image Analysis (OBIA) and Support Vector Machines (SVM) for evaluation Vegetation Composition and Matrix Analysis of Vegetation Change in the Tumbler Ridge Region Using Vegetation Transition Matrix.
  • Wildfire and Geomorphic Events From Landsat
    Around the world, the frequency and intensity of wildfire events are rapidly increasing. Such a trend increasingly exposes some communities to the risk of the secondary hazards of wildfire, such as post-wildfire geomorphic events like a landslide and debris flow. To better manage the risk imposed by the secondary hazards of wildfire, a better understanding of the relationship between wildfire activities and the geomorphic events related therewith is necessary. In this paper, the temporal relationship between past wildfire events and the frequency of two different types of geomorphic events (landslides and debris flow) was studied statistically through the conduction of a time series analysis.


  • Wildfire and Geomorphic Change from LiDAR
    Wildfires remove vegetation and alter soil conditions resulting in increased susceptibility of ground surfaces to erosion, especially over periods of heavy precipitation. Geomorphic changes that are influenced by wildfire occurrence can evolve into hazardous natural events like landslides and flows that pose the risk of human fatality and costly infrastructural damage. We compare light detection and ranging (LiDAR) data time series to identify and compare landscape geomorphic change in burned and unburned areas in the William’s Lake area of the Cariboo Region of British Columbia following the 2017 wildfires.


  • Land Surface Temperature Anomalies and Fire Occurrence
    Wildfires can disrupt forest ecosystem, leading to a deterioration of the air quality, and loss of resources, property animals and people. Understanding the driving factors and the spatial distribution of wildfire benefits local forest fire management planning and resource allocation for fire suppression. To analyze how the land surface temperature (LST) anomaly is related to fire frequency, a fire dataset including more than 400 fires occurred in Cariboo region and a daily LST anomaly dataset based on historical MODIS observations were gathered and processed.


  • Fire Occurrences and Land Surface Temperature Anomalies
    Victoria, Australia has suffered from forest fire for a long period, and forest cover account for almost 25% of land cover. Therefore, it is significant to control fire events especially predict the fire burning effectively. Land surface temperature (LST) anomaly, as an important index, may build a relationship with fire occurrences to help fire management.


  • Burn Severity and Forest Resiliency of the Little Bobtail Lake Wildfire
    Understanding how resilient forests are after wildfire events is important to forest management practices. The objective of this study was to use Landsat-8 data to understand how the burn severity of the Little Bobtail Lake wildfire has impacted forest regrowth several years later. This was done by deriving different vegetation indices to see how the changes in vegetation health were impacted by burn severity. Additionally, landscape pattern metrics were used to understand the changes in the spatial patterns of the burn severity and vegetation health over time.


  • Burning In The Muskwa-Kechika Management Area
    Landscape configuration and composition change are common in rangeland management areas where burning is used to maintain grasslands on slopes. However, little is known about the spatial character of patches within landscapes. The spatial character of landscape patches can be used to link landcover patterns to fire occurrences. We conducted a study to examine the composition and configuration of landscape as a link between landcover types and fires in the Halfway Region – Muskwa Kechika Management Area (M-KMA) in British Columbia.


  • Machine Learning of Wildfire Fuel Types
    Wildfire drives a tremendous amount of forest and land cover change in the central interior of British Columbia, Canada. Fuel type maps have been acknowledged as critical references to conduct landscape-level fire simulations as well as fire behavior predictions. Nonetheless, the current thematic maps are not updated on an annual basis and cannot be easily produced at a certain scale and speed.


  • Fuels Fragmentation and Fire Severity
    Geospatial analyses focused on quantifying fuel types fragmentation and its autocorrelation with megafire severity inform decision making in contexts such as forest management and human activities regulation. Fuel type fragmentation plays a crucial role in fire severity contribution.


  • Vegetation Recovery Following the Elephant Hill Megafire
    The 2017 Elephant Hill wildfire is considered as one of the most destructive fires in Canada. Wildfires are a major ecosystem disturbance which also causes residential displacement and financial loss. Monitoring vegetation recovery following wildfires becomes crucial to rebuilding the local community and ecological system.


  • Shifting Landscape of the Interior Douglas-fir Zone
    The Interior Douglas-fir zone of British Columbia’s Cariboo Region evolved alongside wildfire through millennia of repeat exposure. Resulting from these interactions were fire adapted species and landscape configurations that supported low to moderate severity wildfires. Removing the dominant disturbance agent of these dry forest ecosystems through systematic fire suppression has resulted in unforeseen repercussions. Presently, forests of the Interior Douglas-fir zone hold the potential for higher severity wildfire posing an increased threat to human life.