How to interpret the interactive Fire Maps

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Learn how to use the interactive Fire Maps to visually understand risk on a property level and community level.

With Risk Factor, you unlock access to a variety of interactive maps to help better understand a property’s risk. These interactive maps can be used to visualize where flames from a wildfire may reach, how tall these flames may be, and better understand the intensity of the forecasted wildfires.

Maps Layers

Current & Future Risk

To provide the most accurate current and future wildfire risk assessments, the Model simulates over 100 million wildfires for 2022, to see which of these wildfires grow and become damaging. It outputs over 8 million significant fires per simulation that are then used to calculate risk. Publicly available and 3rd party data is used to identify property boundaries and buildings. The building’s location is then used to determine the likelihood of the home being in a wildfire based on how many times the 8 million simulated fires reached the home. To determine a property’s risk 30 years from now this process is repeated to account for the impacts of climate change on future ‘fire weather’ conditions. Both 2022 and 2052 wildfire simulations provide estimates of burn probability, fire intensity, and ember exposure. This data is then used to determine risk for each year within this 30-year window. 

Year

The First Street Foundation Wildfire Model can determine the burn probability, fire intensity, and ember exposure of a property in any given year, which is known as an annual wildfire likelihood, or annual probability. An annual probability is the chance of something happening at least once within a specific, singular year. Risk Factor® includes three annual probabilities: the current year, 15 years in the future, and 30 years in the future. As the environment continues to change, temperatures will continue to rise creating a drier atmosphere, creating conditions that are prime for wildfires to spread. Explore flood risk by year to understand how environmental changes impact risk. 

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Wildfire Scenarios

  • Likelihood of wildfire or ember zone: The model simulates the ignition of wildfires based on historic fire locations. It then observes how wildfires spread given the fuel and fire weather conditions, and tracks fires that grow to a sufficient size, noting the distance, location, and duration of these fires. The model then calculates a property’s annual burn probability based on how many times the simulated fires reached the building’s location. Annual burn probability is the estimated likelihood of the area burning in any single year.
  • Ember exposure: A property can be directly exposed to a wildfire through direct flames, or indirectly from embers blown by the wind. Embers are small pieces of material that remain after a fire and radiate a substantial amount of heat and are light enough to be carried long distances by the wind without being extinguished. A property in an urban area with little vegetation can be indirectly exposed to distant wildfire from embers carried aloft by the wind. The risk of exposure to flying embers is estimated from the relative amount of embers that land in an area due to nearby simulated wildfires.
  • Average wildfire intensity:  Flame length is a measure of fire intensity. Flame length is the distance between the tip of the flame and the center of the flame at the base of the fire on the ground. Based on the flame lengths of all simulated wildfires that reached a property the model can determine the average flame length expected to reach a property in each year.
  • Max wildfire intensity: The maximum wildfire intensity refers to the maximum flame height that could reach a property in a given year. A property’s maximum expected flame length is the largest flame size that reached home in the wildfire simulations.

Historic Risk

Past Events

The historic fires are sourced from the Monitoring Trends in Burn Severity (MTBS) program. This dataset compiles footprints of fires that exceeded 500 acres in the eastern US and 1,000 acres in the western US. Properties that are within the perimeter of a wildfire or are within 20 miles of a fire perimeter are considered to have been affected by those fires. The historic events shown reflect any wildfire that came within a 20-mile radius of the property since 1984.

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Please note, at the time our Wildfire Model was released, not all fires from the 2020 and 2021 fire seasons were included in the MTBS data. MTBS data is updated regularly. We assure you that our data will be updated as more historic fires are made available through MTBS. 

Statistics

For each event the model calculates the square miles covered by the fire, the distance of the wildfire from the property, and the total number of buildings impacted by the event. 

Community Risk 

Wildfires can have an indirect impact on you even if your home is not burned, by impacting the broader social, commercial, and community infrastructure surrounding your home. The First Street Foundation Wildfire Model is used to determine the likelihood of direct wildfire impact or indirect exposure to embers from nearby wildfires. The probability of being in a wildfire and exposure to embers is used to determine which structures are at risk, the number of structures at risk, and the severity of risk within a community.

Geographic Area

Flood risk can vary for different levels of geographies. The tabs in this section allow you to compare how risk can vary between neighborhoods, zip codes, cities, and counties. The location is automatically set to show risk at the lowest of geography available, which is either the neighborhood or zip code. All properties have information available at the zip code and county level but not necessarily for the neighborhood. 

Community Category

  • Overall: To determine the Community Risk of wildfires, the number of facilities in each category with direct and indirect exposure to wildfires this year and in 30 years is separately calculated. The average probability of being in a wildfire for all facilities in a community is calculated for each category: (1) Infrastructure; (2) Residential properties; (3) Commercial properties; (4) Social facilities. Once risk is determined for each of the 4 categories, the overall risk for a community is calculated by averaging the likelihood for all 4 categories. 
  • Residential: The proportion of residential properties with direct or indirect exposure to wildfire within a community
  • Commercial: The proportion of commercial properties with direct or indirect exposure to wildfire within a community.
  • Infrastructure: The average probability of being in a wildfire for all infrastructure facilities in a community is calculated. Infrastructure facilities include power stations, wastewater treatment facilities, superfund sites, fire stations, police stations, hospitals, seaports, and airports. The percent of infrastructure facilities that fall into each probability threshold is used to determine a community’s level of infrastructure risk.
  • Social: Considers the likelihood of schools, historic and government buildings, places of worship, and museums being in a wildfire. Social risk is determined based on the percentage of structures and the average probability of those structures being in a wildfire

The intensity of a fire can vary from low to medium to high and different areas within one larger wildfire can burn with different intensities.

Map Filters 

  • Filter by Risk Levels: The intensity of a fire can vary from low to medium to high and different areas within one larger wildfire can burn with different intensities. To view infrastructures by the level of risk, select "Filter by level."
  • Filter by Infrastructure, Filter by Social: For a deeper dive into infrastructure and social categorical risk, you can review specific structures at risk within a category by filtering the map to only show buildings of a certain type. For example, when viewing community infrastructure risk, you can filter the map to see risk to emergency services by only toggling fire stations, police stations, and hospitals.

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