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Key Terms, Metrics, and Data Layer Definitions

Key terms, metrics, and data layer definitons used in Technosylva’s Wildfire Planning (FireSight) include:

Wildfire Response

Active Fire Incidents

Point-based locations representing reported wildfire ignitions currently under active management, sourced from the National Interagency Fire Center (NIFC) or integrated federal/state fire reporting systems.

Active Fire Perimeters

The mapped outer boundaries of wildfires currently burning or recently active, typically sourced from federal and state agencies via the National Interagency Fire Center (NIFC) and similar feeds. Perimeters are derived from aerial infrared mapping, satellite detection, and ground-based GPS tracking. In FireSight, this layer provides situational awareness of ongoing fire events within or adjacent to a utility's service territory.

CA High Fire Threat District (HFTD)

A regulatory classification established by the California Public Utilities Commission (CPUC) and California Public Resources Code that designates areas of elevated wildfire ignition and spread risk from utility infrastructure. The HFTD is divided into two tiers — Tier 2 (Elevated) and Tier 3 (Extreme) — based on fire threat modeling conducted by CAL FIRE. Utilities operating within HFTD boundaries are subject to enhanced wildfire mitigation requirements, including Wildfire Mitigation Plan (WMP) filings and stricter equipment and vegetation management standards.

NWS Fire Weather Zones

Geographic areas designated by the National Weather Service (NWS) used to issue fire weather forecasts, watches, and warnings (including Red Flag Warnings). Zone boundaries are drawn to reflect regional topography, vegetation, and prevailing weather patterns.

Utility Infrastructure

Risk and Probability

Probability of Failure (POF)

Probability of Failure (POF) is the likelihood that a utility asset will experience a fault resulting in a spark or burning material under a given set of weather conditions. It represents the first link in the risk chain before Probability of Ignition (POI). The POF model looks at events that could potentially cause ignition (such as equipment failure, object contact, or vegetation contact) and integrates them with historical weather data to create dynamic circuit fragility curves. These curves consist of a static POF (representing the POF in windless conditions) and the dynamic exponential increase due to wind.

Probability of Ignition (POI)

Probability of Ignition (POI) is the likelihood that a failure resulting in spark or burning material at a utility asset results in an ignition. Environmental variables such as the National Fire Danger Rating System’s Ignition Component (IC) are used to generate a POI estimate. This analysis considers fuel variables along with wind speed to determine the likelihood of a wildfire starting from burning material on the ground. POI represents the second link in the risk chain after Probability of Failure (POF): given that an asset has failed, POI determines how likely that failure is to ignite a fire.

Conditional Risk

Conditional Risk quantifies the wildfire consequences associated with a utility asset, assuming an ignition occurs at that location. Conditional Risk answers the question: "if a fire starts here, what could happen?"

For each asset, FireSight evaluates seven risk metrics at 100-meter intervals along the line, taking the maximum value for each risk type to represent the worst-case consequence. These values are then aggregated across all simulated weather days to build a statistical distribution, from which FireSight derives percentiles, average, and standard deviation. For example, a cold, wet, low wind speed day may represent the lowest percentile while a hot, dry, windy day may represent represent the upper percentile.

The seven risk metrics considered for Conditional Risk are:

Expected Risk

Expected Risk quantifies the wildfire risk associated with a utility asset by integrating three factors: the Probability of Failure (POF), the Probability of Ignition (POI) given that failure, and the Conditional Risk of a resulting fire. Expected Risk reflects the full chain of events from equipment fault to fire consequence — making it the right metric when the question is "which assets pose the greatest overall risk of causing a damaging wildfire?"

For each simulated weather day, FireSight calculates the likelihood that an asset experiences an outage, the likelihood that the outage produces an ignition, and the potential fire consequences if ignition occurs. These daily values are combined and aggregated across all weather days to build a statistical distribution including percentiles, average, and standard deviation.

Risk Associated with an Ignition Location (RAIL)

Risk Associated with an Ignition Location (RAIL) assigns risk scores to specific utility assets based on their potential to ignite wildfires and the resulting consequences. A RAIL analysis incorporates:

The final output is a Conditional Risk and Expected Risk for each asset. By combining these components, RAIL generates asset-specific risk scores that enable utilities to prioritize mitigation efforts, operational decisions, and resource allocation based on the highest-risk equipment in their network.

Risk Associated with Value Exposure (RAVE)

Risk Associated with Value Exposure (RAVE) determines which locations have the highest risk from all surrounding assets, considering both fire spread exposure and demographic characteristics such as population, buildings, and infrastructure. By combining these components, RAVE generates risk scores across the landscape, linking them directly to electric utility assets as potential ignition sources.

RAVE differs from Risk Associated with an Ignition Location (RAIL), though the two are complementary. RAIL focuses on location-based consequences of a potential ignition, while RAVE incorporates environmental and community consequences. Together, RAVE and RAIL support composite asset risk metrics for both short-term operations and long-term mitigation planning.

RAVE (Local Risk Factors)

RAVE Local Risk Factors represent the static and semi-static components of the RAVE framework — local characteristics (terrain difficulty, suppression access) and vulnerability (population demographics) — independent of fire behavior or ignition probability.

RAVE (Local Risk Factors) — FULL

An expanded version of the RAVE Local Risk Factors layer that incorporates all three RAVE components: local characteristics, fire spread exposure, and vulnerability. Unlike the standard Local Risk Factors view, the FULL layer integrates dynamic fire behavior and weather-driven spread exposure alongside static local and vulnerability factors, producing a complete composite risk signal across the landscape.

RAVE (Asset Susceptibility)

A layer that quantifies how exposed individual utility assets are to wildfire risk based on the RAVE framework — combining the asset's ignition probability with the risk profile of the surrounding landscape it could impact. Asset Susceptibility translates the spatial RAVE risk surface into asset-level scores, enabling direct comparison and ranking of assets across the portfolio.

Composite Risk Metrics

See the Using Composite Risk Metrics Tutorial for more information.

  • Fire Behavior Composite: A combined measure of Rate of Spread (ROS), Flame Length (FL), and Acres Burned that characterizes the intensity, speed, and overall magnitude of a potential fire.

  • Immediate Impacts Composite: A combined measure of Buildings Threatened, Population Impacted, and Acres Burned that quantifies the direct consequences a fire would have on nearby communities.

  • Suppression Difficulty Composite: A combined measure of Terrain Difficulty and Fire Behavior Composite that reflects how challenging a fire would be to control.

  • Utility Risk Composite: A combined measure of Suppression Difficulty and Immediate Impacts that identifies where infrastructure-caused wildfires pose the greatest direct risk to communities, supporting initial prioritization of system hardening and asset replacement.

  • Utility Risk Vegetation Composite: A composite measure of Utility Risk Composite and Canopy Risk focused on high-risk locations where vegetation management such as tree trimming and canopy thinning can most effectively reduce wildfire risk to both utility infrastructure and surrounding communities.

  • Utility Risk Fuel Loading Composite: A combined measure of Utility Risk Composite and Total Fuel Loading focused on high-risk locations where fuel reduction treatments can most effectively reduce wildfire risk, supporting strategic planning for fuel treatment programs and coordination with land management agencies.

Sub-Composite Risk Metrics

  • Acres Sub-Composite: A normalized score representing the total area that simulated fires originating at a given asset are projected to burn across weather scenarios (Acres Burned). Reflects the potential geographic scale of a fire event.

  • Buildings Threatened Sub-Composite: A normalized score representing the number of structures within the projected fire footprint across simulated weather scenarios (Buildings Threatened). Derived from conditional fire simulations, it reflects the structural exposure a fire originating at a given asset could produce.

  • Flame Length Sub-Composite: A normalized score representing the simulated Flame Length associated with fires originating at a given asset. Flame Length is a primary indicator of fire intensity and a key driver of both suppression difficulty and structural damage potential.

  • Population Impacted Sub-Composite: A normalized score representing the number of people within the projected fire footprint across simulated weather scenarios (Population Impacted). Captures the human exposure dimension of conditional fire risk.

  • Rate of Spread Sub-Composite: A normalized score representing the simulated rate at which fires originating at a given asset are projected to spread across the landscape. Rate of Spread reflects how quickly a fire could grow and how difficult it would be to contain in the early stages.

  • Terrain Difficulty Sub-Composite: A normalized score reflecting the difficulty of the terrain surrounding a given asset as it relates to fire suppression access and operations (Terrain Difficulty Index). Steeper slopes, rugged topography, and limited access routes increase both fire spread rates and the challenge of deploying firefighting resources.

  • Canopy Risk Score: Quantified vegetation canopy characteristics that promote crown fire behavior and vertical fire spread.

  • Total Fuel Loading: Sum of combustible material loads across fuel size classes:

Fuels

Terms like 2022B or 2030Fuels indicate the fuel scenario used for the risk metric. These scenarios indicate baseline or projected future vegetation and fuel conditions derived from the specific reference year, used as the current or future state fuel input for risk metric calculations. Risk metrics calculated against a future fuels scenario allow utilities to evaluate how wildfire risk may evolve over time and to assess whether planned mitigation activities are sufficient to offset increasing fuel loads or changing conditions. For more information on fuels, visit the Technosylva Fuels Glossary.

Other Terms and Abbreviations

Statistics

  • E or underscore e: Expected

  • C or underscore c: Conditional

  • Min: Minimum

  • Max: Maximum

  • Stddev: Standard Deviation

  • Percentiles:

    • 20th: 20th percentile 

    • 40th: 40th percentile

    • 60th: 60th percentile

    • 80th: 80th percentile

    • 90th: 90th percentile

    • 95th: 95th percentile

    • 98th: 98th percentile

Other Terms

  • Line Miles: Line miles per circuit.