University of Utah lidar helps wildland firefighters stay safe

18 Sep 2024

Modelling rates of travel from lidar data can also help plan evacuations or locate walkers.

A project at the University of Utah has developed a method for predicting rates of travel for on- and off-path walkers, based on analysis of lidar data mapping the terrain they cover.

Christened STRIDE, for Simulating Travel Rates In Diverse Environments, the approach could be valuable for assessing risk to outdoor firefighters, as well as modelling troop movements or travel networks.

STRIDE is the first model that incorporates ground roughness and vegetation density in addition to slope steepness, so as to predict walking travel times with unprecedented accuracy, according to the project team.

"One of the fundamental questions in firefighter safety is mobility," commented Mickey Campbell from the University of Utah. "If I'm in the middle of the woods and need to get out of here, what is the best way to go and how long will it take me?"

Previous Utah applications of optical technology to outdoor ecology have included the use of light-sheet illumination to track falling snowflakes, and the new research builds on previous work at the Utah Remote Sensing Applications lab (URSA) studying the use of lidar and other techniques for evaluating woodland ecosystems and mapping biomass.

"Discrete-return airborne lidar is unique in its ability to map three-dimensional structure over space based on point clouds representing the x, y, and z coordinates of reflective surfaces, eg. ground and vegetation," noted the project in its Scientific Reports paper.

"Narrow laser pulses exploit small gaps in vegetation canopies to measure ground elevations with high precision, and even in the presence of tall vegetation, airborne lidar can characterize the structure of vegetation within the above-ground height ranges that are most relevant to human movement."

Life-saving routes for those in danger

Although walking times on flat even terrain in urban settings can be reliably predicted, there is a need for better ways to model travel times off-road and off-path, for military purposes, search and rescue, and wildland firefighting.

The STRIDE modelling analysis, now made available as an open-source package, is based around three particular variables - slope, vegetation density and surface roughness - all derived from lidar data taken for an existing mapping survey, the USGS 3D Elevation Program.

After clearing the data of noise as much as possible, the lidar point clouds were used to derive 1-meter-resolution digital terrain models through interpolation of classified ground points. Surface roughness at the meter-scale and ground-level vegetation can be assessed from the data and the relative density of lidar point returns.

Travel rates based on the surface data were then modeled, and in trials STRIDE explained more than 80 percent of the variance in the mean travel rates from three separate field experiments, with an average predictive error less than 16 percent according to the team.

STRIDE consistently chose routes resembling paths that a person would logically seek out, said the project. It preferred roads, trails and paths of least resistance, and produced much more accurate travel times than the standard slope-only models that severely underestimated travel time.

"If a wildland fire reaches a firefighter before they reach safety, the results can be deadly," said Mickey Campbell. "STRIDE has the potential to not only improve firefighter evacuation but also better our understanding of pedestrian mobility across disciplines from defense to archaeology, disaster response and outdoor recreation planning."