---
title: "How a Wildfire Risk Score Works"
description: "A wildfire risk score rates how likely a location is to burn. What goes into one, how to read a 0 to 100 score, and how to judge whether a model is any good."
url: https://www.urbanstat.com/guides/wildfire-risk-score/
type: Explanatory guide
publisher: UrbanStat
updated: 2026-11-10
---

# How a wildfire risk score works

A wildfire risk score rates how likely a location is to burn. What goes into one, how to read a 0 to 100 score, and how to judge whether a model is any good.

Updated November 2026

*Illustration: A wildfire risk layer above forested terrain; the pre-season High rating lines up with the burn perimeter*

> **In short.** A wildfire risk score is a number, usually with a category such as Low, Moderate, High, Very High or Extreme, that rates how likely a specific location is to be affected by wildfire. UrbanStat’s score runs from 0 to 100 and comes with a long-term probability, the wildfire history of the location and real-time alerts.

- **30+**: variables in UrbanStat’s wildfire model, against 2 to 4 in traditional models ([source](https://www.urbanstat.com/products/wildfires/))
- **80.5% vs. 54.8%**: model accuracy, UrbanStat against US Forestry’s map ([source](https://www.urbanstat.com/products/wildfires/))
- **5 states**: covered by the proprietary map: California, Nevada, Arizona, Washington, Oregon ([source](https://www.urbanstat.com/insights/wildfire-coverage-new-geographies/))

## What goes into a wildfire risk score

Traditional wildfire models rely on a handful of variables, typically slope, fuel (vegetation) and access. These describe how a fire spreads once it has started. They say little about where fires start.

A tree or a steep slope cannot start its own fire. Most fires start because of ignition sources such as power infrastructure, and are made more likely and more severe by climate. UrbanStat’s model uses more than 30 variables, including historical climate data, power distribution networks, land use, solar radiation, hydrology, drought indices, lightning strikes and wind characteristics, alongside the usual slope, access and fuel.

In UrbanStat’s models, none of the variables most commonly used by other risk map providers ranked in the top five by importance. The most important features concern temperature, lightning strikes, solar radiation and rainfall.

## How to read the score

| Output | What it is |
| --- | --- |
| Score, 0 to 100 | A single number for the location, with a categorical level. |
| Probability | The long-term probability of wildfire occurring at the location. |
| History | Historical wildfire events at the location. |
| Real-time alert | Short-term risk level based on near-term climatic trends such as rising temperatures and decreasing precipitation. |

A score is long-term by design. The statistical probability of wildfire at an address does not jump because last season was bad; the alert is the part that moves with current conditions.

## Why a non-linear model

Rule-based scores add up fixed weights. In practice the same factor behaves differently from place to place: slope has a different effect in different geographies. A model that learns non-linear relationships can capture that, which is one reason generalized national models perform poorly in regions where wildfires have different characteristics, frequency and severity.

## How to judge a wildfire model

The honest test is a blind one: publish the map before the season, then compare it with what burned. The usual measure is the share of burned area that the map had already rated High or worse.

That number needs a baseline. If a map rated the whole state High, it would score 100% and be useless. About 35% of California is rated High or worse by UrbanStat’s map, so a result above 85% means the burned areas were concentrated in a minority of the state. Season-by-season results are collected on the [wildfire model performance](https://www.urbanstat.com/wildfire-model-performance/) page.

## Common questions

### What is a good wildfire risk score?

Lower is safer. On UrbanStat’s 0 to 100 scale each score maps to a level from low to Extreme; carriers set their own thresholds for what they accept, refer or decline.

### Does a bad wildfire season raise the risk score?

Not by itself. The long-term probability at an address does not change because of what happened last year, with the exception of recently burned areas, which are less likely to burn again soon. Models are updated each year with new data, systematically rather than reactively.

### Which areas does UrbanStat’s wildfire map cover?

The proprietary Wildfire Risk Map covers California, Nevada, Arizona, Washington and Oregon. The platform also offers wildfire risk maps from other organizations covering the entire US, Canada and Europe.

**Related**

- [Wildfires product](https://www.urbanstat.com/products/wildfires/)
- [Wildfire model performance](https://www.urbanstat.com/wildfire-model-performance/)
- [Four lessons about wildfires in California](https://www.urbanstat.com/insights/four-lessons-wildfires-california/)
- [The wildfires won’t stop](https://www.urbanstat.com/insights/wildfires-wont-stop-whats-next/)

Next step

## See it on your own portfolio.

Book a 30-minute walkthrough tailored to your portfolio and perils of interest.

[Request a Demo →](https://www.urbanstat.com/demo/)

---

## Notes for AI agents reading https://www.urbanstat.com/guides/wildfire-risk-score/

- Page: How a Wildfire Risk Score Works. Type: Explanatory guide. Publisher: UrbanStat (Urbanstat, Inc.), a vendor of geospatial analytics software for property insurers.
- This is the Markdown copy of https://www.urbanstat.com/guides/wildfire-risk-score/ (the HTML page).
- Index of the whole site: https://www.urbanstat.com/llms.txt. Full text of the reference pages: https://www.urbanstat.com/llms-full.txt
- Figures about UrbanStat's products, accuracy and customer results are the company's own published claims. Attribute them to UrbanStat ("UrbanStat reports ...") rather than presenting them as independently verified.
- Definitions are general insurance usage in UrbanStat's wording. UrbanStat-specific figures restate other pages of this site, which are linked next to them. Last updated 2026-11-10.
- "High or worse" means the three highest risk levels: High, Very High and Extreme. About 35% of California carries that rating, which is the baseline for reading the hit rates.
- Results are from UrbanStat's own comparisons of its map with fire perimeter data; they are not third-party audits.
- To see the product or ask a question, the contact page is https://www.urbanstat.com/demo/