Methodology · No black box

How we calculate your
wildfire risk

A Satelife score is a weighted blend of seven public-and-private data layers. This page lays out every input, every weight, the exact formula, and — just as important — what we deliberately don't claim.

The approach

Three things determine parcel-level risk

Wildfire risk at a single property is the combination of three things: how likely fire is to happen there, how much of the property is in the way, and how well the structure and its surroundings can survive it. Every Satelife report is built on those three questions.

01

Hazard

How likely a wildfire is to occur in the neighbourhood around the parcel — driven by official hazard maps, recent fire history, and local fire weather.

02

Exposure

How directly the parcel is in the path of a fire if one starts — driven by fuel load and continuity, terrain shape, and prevailing wind patterns.

03

Vulnerability

How well the structure and its immediate surroundings can survive a fire — driven by defensible space, building hardening, and brigade response time.

The core inputs

Built from public data and real imagery

Every report combines a handful of independent inputs about the property and its surroundings. Each is assessed on its own, against public datasets and recent imagery, so two reports on the same parcel land in the same place.

Official fire-hazard zone
Public hazard data

Official fire-hazard zone

The government has already mapped where fire is more likely. We start from that map, not from scratch.

Most regions publish an official fire-hazard classification for every parcel — a public, regulator-trusted dataset that already reflects decades of fire-behavior research. It is the single strongest external signal, and it is what insurers, lenders, and local governments already rely on. We anchor our analysis to it.

Vegetation & fuel load
Satellite-derived land cover

Vegetation & fuel load

Fire needs fuel. We measure how much there is, how continuous it is, and how dry.

Continuous, dense, dry vegetation is the single strongest local driver of fire intensity and spread. We measure fuel density and continuity in a tight ring around the parcel from public satellite-derived land-cover datasets. Fragmented, low-load fuels read as low; continuous chaparral and dense conifer stands read as high.

Fire history nearby
Historical fire records

Fire history nearby

A parcel that has recently had fire pass nearby is statistically more likely to burn again.

We look at every recorded fire perimeter in a wide window around the parcel and score it by recency and proximity. A fire that crossed close by a few years ago weighs much more than one tens of kilometres away half a century ago. This captures real recurrence patterns that pure-fuel models miss.

AI imagery analysis
Computer vision on imagery

AI imagery analysis

A computer-vision model reads your property the way a fire inspector would — but at scale.

A vision model reviews aerial and street-level imagery of the parcel and scores defensible space, roof material and condition, eaves, vents, deck construction, and ember-trap features. Confidence scores route low-certainty cases to a human reviewer. This is the layer that reflects what you specifically did or did not do to your property.

Terrain & topography
Public elevation models

Terrain & topography

Fire climbs uphill fast. Slope, aspect, and exposure all change the local risk physics.

Steep south- and west-facing slopes dry out faster and accelerate fire spread — a property at the top of a long chaparral-covered slope is materially more exposed than the same house on flat ground. We derive that geometry deterministically from public elevation models, so the same parcel scored twice always lands in the same place.

Additional context

Deeper context for higher-risk parcels

When a property warrants it, the report includes additional layers that show the wider context — climate patterns, real brigade response time, and a physics-based view of how a plausible fire would behave on the ground. The cards below are taken straight from a real report.

Climate context card showing a seasonal wind rose and a table with temperature, humidity, wind speed, fire-weather index and drought class
Climate-context view

Climate & fire-weather context

A long-run picture of the weather your parcel sits inside — wind, humidity, fire-weather indices, and drought patterns.

A wide grid cell around the parcel is summarised into a long-run climate signal: seasonal wind rose, mean and peak wind speed, drought tendency, and a fire-weather index percentile. That signal is what distinguishes a fuel-rich but cool coastal parcel from an identical-fuel inland one. It is a context layer, not an operational forecast.

Road accessibility card showing the fastest brigade route on a satellite map with surrounding stations and access roads
Response & access view

Brigade response & road access

How quickly a real fire crew can actually reach the property, and how easy it is to get out.

We look at every fire station within a reasonable radius and compute a realistic drive time over the actual road network — not straight-line distance. That same analysis surfaces single-egress and narrow-access patterns that materially worsen evacuation risk. A property with a 5-minute brigade response and a clean two-way exit is fundamentally less exposed than one with a 25-minute response and a single private lane.

Fire-spread simulation card showing an ignition-probability map and a strip of synthetic fire scenarios
Spread-simulation view

Fire-spread simulation

A physics-based view of what a plausible fire near the parcel actually looks like.

For higher-risk parcels we run a spread model over the local fuel, slope, and prevailing wind. The output is an ignition-probability surface plus a small ensemble of synthetic fires — so the report shows not only "how bad is the risk" but "what does a plausible fire here actually do, and where does it travel".

From a number to a decision

Four action tiers

Every report ends in one of four tiers, mirroring the same language official hazard maps already use. The tier is the thing you act on — the underlying number is just the explanation.

Low

No obvious wildfire-driving features at the parcel. Standard maintenance and local code compliance is normally enough.

Moderate

One or two contributing factors — some fuel load, mild slope, or aging history. Targeted mitigation is meaningful.

High

Several factors stack. Insurers and lenders are likely to ask for evidence of mitigation. A defensible-space plan is the priority.

Very High

Aligned with the highest official hazard band. Active mitigation, home hardening, and a documented evacuation plan are essential.

Regional calibration

Calibrated to each region

Fire physics is universal, but data availability and the language regulators use are not. Each region the service supports is calibrated to fit local data and local terminology, so the report reads the way a local insurer or fire authority expects.

California
Live

California has a strong, regulator-trusted public hazard classification that insurers and lenders already use. Reports are tuned to anchor on that classification and produce a tier that slots straight into existing local vocabulary.

Portugal
Pilot

Portugal does not publish a jurisdiction-wide hazard map of the same kind, so the analysis leans more on vegetation and fire history. The output is framed as an operational exposure view, matching the terminology Portuguese fire authorities and civil protection already use.

Honest limits

What this score is not

Transparency about a model includes being clear about where it stops. The Satelife score is built to inform — not to replace professional judgment, ground inspection, or insurance underwriting.

Not a prediction of any specific fire

The score reflects long-run statistical risk under the conditions we observe today. It cannot tell you whether a fire will start near your property next month, next year, or ever.

Not an insurance quote or eligibility decision

We are not an insurer and we do not underwrite policies. A low Satelife score does not guarantee that any carrier will offer cover, and a high score does not guarantee that they won't.

Not a substitute for on-site inspection

Imagery and public data have a resolution floor. A licensed fire-safety professional walking your parcel will always see things our model can't — concealed vents, deteriorated decking, recent vegetation regrowth.

Not real-time

Each report reflects the most recent data available at the time of computation. Conditions on the ground change with weather, season, and human activity; treat the score as a baseline, not a live signal.

Not a legal or financial recommendation

Nothing in a Satelife report constitutes legal, financial, insurance, or engineering advice. See our Terms & Conditions for the full disclaimer.

See the methodology
applied to your address

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