These maps display wildfire risk exposure of households in the state of California. Estimates of the number of households that fall within areas with the highest wildfire risk are aggregated within small area hexagons and then displayed on the map using a color-coding scheme described in the legend. Lighter yellow hues signify the highest concentration of individual households in highest risk areas. A hexagon that is orange or yellow does not necessarily indicate that wildfire risk is highest, overall, but rather that the hexagon contains the most households in high risk areas, relative to other hexagons. These orange and yellow areas, then, are the most likely to involve conflagrations that impact large populations. Therefore, estimates of concentrations can serve as a guide to conduct further data analysis and vulnerability assessments, emergency planning, and resource allocation.
To produce these maps, researchers used 2017 United States Postal Service (USPS) address vacancy data1. The USPS vacancy data is a quarterly updated dataset of the universe of all addresses in the United States and are, thus, the most granular geographic housing unit data available to HUD. The data of occupied residential units can be geographically plotted at the Zip+4 centroid, which typically encompasses 10-30 actual housing units. To assess wildfire risk, researchers matched Zip+4 centroids to the 2018 Wildfire Hazard Potential (WHP) Map produced by the US Forest Service2. This national wildfire risk data is an index generated from multiple data sources that measure attributes such as wildfire likelihood and intensity, fuel and vegetation, and past fire occurrences. The result is a national map of wildfire potential at 270- m.² resolution. For this analysis, Zip+4 centroids that matched with WHP risk of High or Very High are used to convey high-risk households. The maps only display counts of households that are at high or very high risk. The household counts are then aggregated within small area hexagons measuring approximately four-mi.², which are assigned a color based on the number of at-risk households.
A note of caution regarding USPS vacancy data. Though this data is more granular than Census data with regard to geographic location, the Zip+4 centroids associate with capture areas of varying geographic size, such that rural Zip+4 centroids tend to include addresses that are more geographically dispersed. As a result, and because of how we used the Zip+4 centroid data to match to granular wildfire risk data, the rural data may be less accurate in flagging wildfire risk, either over-counting or under-counting households within high-risk areas.