Every Satelife report runs through a 14-step AI pipeline that pulls real satellite data, historical fire records, and on-the-ground imagery — then scores your property across six risk dimensions.
Every run starts with a property address. We resolve it to exact parcel coordinates and validate coverage before any data is fetched.
The user submits a US property address — street, city, state. Batch mode supports up to hundreds of parcels per request for portfolio analysis.
Entry pointThe address is resolved to latitude/longitude coordinates via Nominatim (OpenStreetMap), with Google Maps as fallback. The result is cached for 30 days to avoid repeat lookups.
Nominatim · Google MapsSeven independent data streams run in parallel — imagery, terrain, fire history, vegetation, weather, wind, and road access. Each feeds a separate scored layer.
Nine image sources fire in parallel: Google Maps Static, MapTiler, Esri World Imagery, NAIP aerial, and a four-direction Street View sweep (N/E/S/W). All stored in Supabase Storage.
Google · MapTiler · Esri · NAIPElevation, slope, and aspect are derived from USGS Digital Elevation Models. Steep south-facing slopes with uphill wind exposure receive higher hazard scores.
USGS DEMCAL FIRE's public ArcGIS REST service returns the official Fire Hazard Severity Zone (Moderate / High / Very High) for the parcel's jurisdiction — State, Local, or Federal Responsibility Area.
CAL FIRE · FHSZHistorical fire perimeters from CAL FIRE and NIFC are queried for the surrounding area. Proximity and recency of past fires directly affect the risk score.
CAL FIRE · NIFCVegetation density and fuel continuity are measured at 30 m and 100 m aggregation from NLCD and California Forest Observatory data. Dense, continuous fuel loads elevate the score significantly.
NLCD · California Forest ObservatoryReal climate data is fetched for both California and Portugal adapters. The climate factor is a composite of Fire Weather Index percentile (45%), fire-season mean wind (30%), aridity index (15%), and special-event bonus (10%).
FWI · ERA5 · NOAAPrevailing wind direction and speed are pulled from historical records and current forecasts. Wind rose data feeds both the climate factor and the terrain exposure calculation.
Wind rose · Seasonal patternsFire station locations are fetched from OpenStreetMap Overpass and routed to the property via OSRM. The estimated brigade-response ETA (≤5 min → score 10; no station → score 95) is a direct input to the risk model.
Overpass · OSRMGPT-Vision analyses the property imagery and the RiskEngine combines all scored layers into a single 0–100 risk score calibrated per jurisdiction.
GPT-Vision reviews the Street View and aerial imagery to assess vegetation clearance across three zones — Zone 0 (0–5 ft), Zone 1 (5–30 ft), and Zone 2 (30–100 ft) — around the structure.
GPT-Vision · Street ViewA second Vision pass evaluates structural fire resistance: roof material, vents, deck construction, eaves, and window type. A confidence score triggers human review if below the 0.7 threshold.
GPT-Vision · Admin review gateThe RiskEngine applies the formula Risk = Hazard × Exposure × Vulnerability, combining all 11 scored layers into a single 0–100 score and a risk tier (Low / Moderate / High / Very High). The engine uses swappable regional adapters — California and Portugal are live.
RiskEngine · Regional adaptersThe RiskEngine combines 11 composable data layers. Each layer is scored independently and weighted by its contribution to wildfire risk at the parcel level.
Parcel boundary, jurisdiction, address resolution, and regional adapter selection.
Slope, elevation, aspect, and uphill wind-exposure score from USGS DEM data.
Official FHSZ classification combined with proximity and recency of historical fire perimeters.
Fuel density and continuity at 30 m and 100 m radius from NLCD and Forest Observatory datasets.
Fire Weather Index, aridity, seasonal wind patterns, and special fire-weather event bonuses.
AI-assessed vegetation clearance across three zones plus structural fire-resistance scoring via GPT-Vision.
The final step packages everything into a structured JSON payload and a four-page PDF report, then sends a notification email with a secure download link.
A four-page PDF is rendered with the risk score, tier, per-layer breakdown, satellite imagery, and a prioritised mitigation plan. Stored securely in Supabase Storage with a signed URL.
Every report produces a machine-readable JSON payload with risk_score, risk_tier, per-layer scores, imagery URLs, and the full mitigation plan — ready for API consumers and portfolio tools.
A transactional email via Resend delivers the "your report is ready" notification with a direct link to the dashboard download. The full pipeline completes in under 30 seconds for cached areas.
Enter your property address and get your first Satelife wildfire risk report — free, in under 30 seconds.
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