Wildfire risk in the utility corridor
New whitepaper reveals what fuel models are missing today
If you work in utility wildfire risk, consequence modeling is probably central to how you guide investment decisions, prioritize mitigation, and meet regulatory requirements. But wildfire programs focused on landscape-level spread alone are missing a key question: where ignitions themselves are most likely and most mitigable.
Standard, public fuel maps like LANDFIRE were built for landscape-scale analysis of natural systems, not utility operations and rights of way. That means that a utility using landscape-scale fuel data to model spread and consequence may be missing critical information. Without granular, corridor-specific fuel data, utilities can't know which spans need the most attention, or defensibly make the case for targeted prevention investments in vegetation management and asset hardening.
The right question isn't just where a fire will spread. It's where one will start.
Most wildfire programs are built around a landscape-level question: if a fire starts somewhere in this region, where does it go? That's a useful question. But for utilities, it's not the only one. Utility ignition happens at specific sites, often as a result of specific hazards. The question driving controllable prevention is: which locations are most likely to ignite?
As wildfire risk accelerates across North America, utilities must own their core controllable risk and draw on both fire science and ignition data. Without tracking the most likely ignition drivers across their network, they can't run a maximally efficient wildfire program, or accurately model the spread risk that they pose .
The problem isn’t the data. It’s the resolution.
Tools like LANDFIRE are valuable, but they were not built for utility-scale decisions. A single pixel can cover an area as large as two football fields, often blending actively managed rights-of-way with surrounding terrain. That averaging effect hides the very conditions utilities work hardest to manage: cleared corridors, regrowth patterns, and accumulated surface fuels.
These environments also behave differently than surrounding landscapes in ways that matter directly for ignition risk.
Fuel moisture is one example. When vegetation is cleared, it loses the canopy cover that helps retain moisture. Sun exposure increases, wind moves more freely, and humidity drops. Fuels inside the corridor can dry out faster than those nearby, increasing ignition risk even on days that appear moderate based on regional fire weather metrics like NFDRS indices.
Standard models miss that difference. And when mitigation decisions are based on data that can't distinguish conditions inside your corridor from those outside it, the result is a program that's broader than it needs to be and less targeted where it counts.
Without granular data, you can't know which spans need attention most.
Utility rights-of-way are actively managed systems, and that management creates fuel conditions that standard models weren't built to represent. Cyclic clearing produces stump sprouts and slash accumulations. Herbicide treatment leaves standing dead vegetation drying in place. The result is a mosaic of fuel conditions that varies significantly from span to span but that looks uniform from 30 meters up.
At a high level, many sites appear similar. At the span level, they're not. Fuel type, moisture, and vegetation structure can vary significantly between adjacent spans, changing how likely a given location is to ignite. When you can't see that variation, prevention efforts become broader than they need to be and less targeted where ignition risk is actually concentrated.
Learn more about the gaps in existing consequence models. Download the whitepaper.