Housing Density
Athena’s Voice of the Acre® has been optimized for economic losses, the analysis includes density, proximity to the WUI and vegetation.
On the surface, housing density is straight-forward, a measure of the number of homes or buildings in a given area. There is no universally accepted methodology for calculating density. Athena uses Gross Density, which includes the common areas such as roads and open spaces and open space between buildings.
Many people think of housing density as crowded neighborhoods, which isn’t exactly correct. The New York Times, in 2020 published an article on the topic, Everything You Think You Know About Housing is Probably Wrong.
The data Athena uses for Housing Density (and many other data points) is the same data all wildfire models use. Athena’s Value-Add is the processing to make the data easy to use, and our application modules, such as Wildfire Risk.
Housing Density comes from HUD in a raster file where the measurement is housing units per square kilometer (sq km). Housing units are any structures that have residential population associated with them and include primary single-family and multi-family residential buildings, secondary or seasonal homes, and facilities such as prisons, dormitories, barracks, and nursing homes.
Census blocks are delineated by housing density and proximity of housing to wildfire susceptible vegetation. Athena gives a score to each density and proximity class, then combines them to produce a WUI Score. The higher the density and closer proximity the higher the potential insurable loss value.
This is partially offset by the statistical evidence that lower density neighborhoods have higher wildfire risk. Numerous academic papers have been written in the past 5 years, pointing this out in Southeast France and in California. These neighborhoods usually have a close proximity to wildlands, known as the WUI or Wildland Urban Interface.
Athena’s Voice of the Acre® has been optimized for insured or economic losses, so the analysis includes density, proximity to the WUI and the nature of the contact.
Here a picture really is worth a thousand words:
On the left you have low density, with trees and shrubs near homes, as well as close proximity to the WUI — this is known as Intermix. Most low-density neighborhoods in close proximity to WUI look like this.
From a wildfire risk perspective, a higher density neighborhood, which tends to have fewer trees and shrubs near the buildings has lower risk, despite being in close proximity to the WUI. This is known as WUI Interface. The government agency or NGO responsible for the wilderness area generally maintains a clean border with the structures and takes action to mitigate wildfire risks — including clearing brush.
In contrast, in the picture on the left, even if the wooded area is well maintained to mitigate wildfire risks, the intermix of shrubs and trees is almost universally considered the responsibility of the homeowners. Wildfire risk comes not just from your lot and your landscaping, but from all neighbors within 1,000 meters. Those neighbors are at risk for wildfire activity within 2 miles, which in turn is impact by wildfire activity futher from the original location.
To accurately assess the risk at any property, you need to consider every aspect of the land, structures, vegetation, climate, roads, natural firebreaks and human behavior, within 5 miles. Which what Athena Intelligence’s conditional, geospatial, machine learning wildfire risk model provides.
For more information, please read our commentary on the Proximity to Wildland flag.
Athena is a next generation InsurTech data vendor which produces synthetic data. The earth’s essential data is refined to make it easy for enterprises to use environmental information for future contracts, proprietary business decisions and risk management.
Contact us at Info@Project-Athena.com
