Guide
Wildfire Risk Assessment: How to Evaluate Your Property's Exposure
Over 46 million homes in the United States are in the wildland-urban interface (WUI) — the zone where development meets undeveloped wildland vegetation. USFS and FEMA data show that wildfire risk is not evenly distributed: some communities face catastrophic exposure while neighboring areas are relatively safe. Understanding how risk is assessed helps homeowners, buyers, and communities make informed decisions.
Leading causes of US home fires
Share of residential fires by cause
- Cooking
Cooking
49 % of fires
- Heating Equipment 15
Heating Equipment
15 % of fires
- Vehicle Fires 14
Vehicle Fires
14 % of fires
- Electrical & Lighting 9
Electrical & Lighting
9 % of fires
- Intentional (Arson) 8
Intentional (Arson)
8 % of fires
- Smoking Materials 6
Smoking Materials
6 % of fires
- Wildland & Brush 5
Wildland & Brush
5 % of fires
- Candles 4
Candles
4 % of fires
What this shows Cooking is the leading cause, accounting for 49% of US home fires. Smoking materials cause a far larger share of deaths than fires — a reminder that the most common causes are not always the deadliest.
1. What Is the Wildland-Urban Interface (WUI)?
The WUI is the geographic zone where human development and wildland fuels intermix or are adjacent. It is the primary geography of wildfire risk to structures.
- ▸ Intermix WUI — homes are scattered within wildland vegetation (houses built in forested or brush areas)
- ▸ Interface WUI — dense development directly abuts wildland vegetation (subdivisions at the edge of forests or grasslands)
- ▸ The WUI has expanded 33% since 1990 as development pushed into previously undeveloped areas
- ▸ USFS publishes WUI maps at the census block level — available through the SILVIS Lab at the University of Wisconsin
- ▸ Living in the WUI does not guarantee a wildfire will reach you — it means the *potential* exists based on vegetation and proximity
- ▸ Check the FEMA National Risk Index for county-level wildfire risk scores and historical disaster data
2. How Wildfire Risk Is Calculated
Wildfire risk assessment combines multiple data layers to estimate the likelihood and potential impact of wildfire on a specific area.
- ▸ Fire Weather — wind speed, humidity, temperature, drought conditions. <a href="https://www.noaa.gov/" target="_blank" rel="noopener nofollow">NOAA</a> and the <a href="https://www.weather.gov/fire/" target="_blank" rel="noopener nofollow">National Weather Service</a> produce fire weather forecasts and Red Flag Warnings
- ▸ Vegetation (fuel load) — type, density, and moisture content of vegetation. <a href="https://landfire.gov/" target="_blank" rel="noopener nofollow">LANDFIRE</a> (a <a href="https://www.usgs.gov/programs/landfire" target="_blank" rel="noopener nofollow">USGS</a>/USFS program) maps fuel types nationally
- ▸ Topography — slope, aspect, and elevation. Fire spreads faster uphill and on south-facing slopes in the Northern Hemisphere
- ▸ Historical fire occurrence — past fire locations and frequencies from NIFC (National Interagency Fire Center) datasets
- ▸ Human ignition probability — proximity to roads, campgrounds, power lines, and other human activity that can start fires
- ▸ Structural vulnerability — building materials, defensible space, and community design (IBHS assessment framework)
3. Federal Wildfire Data Sources
Several federal agencies produce wildfire risk data that is freely available to the public.
- ▸ USFS Wildfire Risk to Communities (wildfirerisk.org) — community-level risk scores combining likelihood, intensity, and structural exposure
- ▸ FEMA National Risk Index — county-level wildfire risk ratings as part of the multi-hazard risk index
- ▸ NIFC InciWeb — active wildfire incident tracking (current fires, not historical risk)
- ▸ LANDFIRE — national vegetation, fuel, and fire regime mapping (used by fire managers, technical audience)
- ▸ CAL FIRE Hazard Severity Zones — California-specific but the gold standard for state-level risk mapping
- ▸ PlainFireData county and state pages show fire department coverage, which directly affects wildfire response capacity in your area
4. Assessing Your Property
Individual property risk depends on both landscape-level factors (which you cannot change) and parcel-level factors (which you can).
- ▸ Use wildfirerisk.org to check your community's overall wildfire risk score and see which risk factors are highest
- ▸ Check whether your home is in a mapped WUI area — this affects insurance availability and cost
- ▸ Evaluate your defensible space (see our Wildfire Home Protection guide for Zone 1/2/3 specifications)
- ▸ Assess your home's construction materials — roof, siding, decking, and vent materials determine ember vulnerability
- ▸ Know your evacuation routes — areas with limited road access face higher risk during evacuation scenarios
- ▸ Check your fire department's type and staffing on PlainFireData — volunteer departments in WUI areas may have longer response times during large fires
5. Insurance and Financial Implications
Wildfire risk increasingly affects property insurance availability and cost, particularly in western states.
- ▸ Major insurers have withdrawn from high-risk areas in California, Colorado, and other western states
- ▸ FAIR Plans (state-backed insurers of last resort) provide basic coverage but at higher cost with limited benefits
- ▸ Homes with documented defensible space, fire-resistant materials, and community wildfire protection plans may qualify for reduced premiums
- ▸ ISO fire protection ratings consider wildfire risk — properties with poor ratings may pay 2-3x higher premiums
- ▸ Buyers should check insurance availability BEFORE purchasing property in WUI areas — some properties are effectively uninsurable through standard markets
- ▸ Community Wildfire Protection Plans (CWPPs), when adopted, can help improve insurance availability for entire neighborhoods
Read our methodology — how this data is sourced, computed, and verified.
Related
Understanding the Data
The information presented throughout this guide is informed by publicly available public records published by federal and state government agencies. Our database aggregates and standardizes these records to make them more accessible and easier to interpret for general audiences. When we reference specific statistics or trends, they are drawn directly from these authoritative sources unless explicitly noted otherwise.
It is important to understand the limitations of any large-scale data dataset. Records may contain errors from the original data collection process, some fields may be incomplete for older entries, and classification systems may have changed over time. Our analysis accounts for these factors by clearly labeling data vintage, flagging records with missing critical fields, and noting when temporal comparisons span methodology changes in the source data.
For readers who want to conduct their own research, we recommend going directly to the source whenever possible. federal and state government agencies provides detailed documentation on collection methodology, sampling frames, and known data quality issues. Our goal is not to replace primary sources but to make them more approachable and to highlight patterns that may not be immediately obvious when browsing raw records.
How We Analyze Data Records
Our analytical approach involves several steps designed to surface meaningful insights from large datasets. First, we clean and standardize the raw data, handling variations in naming conventions, date formats, and categorical labels. Then we compute summary statistics, distributions, and comparative benchmarks across relevant dimensions such as geography, time period, and category type.
Key metrics we examine include statistical records, geographic distributions, temporal trends. These indicators provide a multi-dimensional view of each entity in our database, allowing users to understand not just individual records but how they compare to peers, regional averages, and national benchmarks. We believe this contextual approach is far more valuable than presenting raw numbers in isolation.
