Monitoring Fuel Loads and Prescribed Fire Effects with the Push of a Button

Monitoring fuel loads and fuel treatment effects is critical for assessing management needs and outcomes yet has been difficult to achieve at management scales. Monitoring data allows managers to identify fuel hazards, run fire behavior simulation models that inform how fires may progress under different weather and forest management scenarios, and predict ecological impacts of management decisions. Such monitoring is needed now more than ever to understand and respond to the growing challenges of wildfire and climate change on many landscapes. New monitoring approaches with terrestrial laser scanning developed by Northern Research Station (NRS) scientists and partners are helping managers collect better monitoring data faster and more easily than ever at the push of a button.

Terrestrial laser scanning, or TLS, is a type of remote sensing technology used to detect the location of surrounding objects and surfaces, such as vegetation. Another name for TLS is “terrestrial LiDAR” (LiDAR meaning Light Detection And Ranging), as it is a ground-based type of LiDAR. TLS operates by emitting laser pulses that then bounce off objects, like vegetation or the ground, and return to a sensor that is paired with the emitter. Onboard software uses information from the scan to then calculate the three-dimensional coordinates of the object the laser pulse. TLS sends out millions of laser pulses to capture information about its surroundings in about 4 minutes.

Ongoing research by NRS scientists uses TLS to estimate fuel loads, structure, and burn severity after fires, as well as to monitor the effects of prescribed burning and thinning on forest vegetation. The success of TLS hinges on relationships between laser data and physical measurements of forest characteristics, which give the LiDAR data definition in terms of ecological conditions or properties. Their research will help optimize the use of TLS for fuels inventorying and treatment effects monitoring purposes in forest management and increase the ability of managers to collect numerical data about management needs and outcomes. Much of this work has occurred in the Pinelands National Reserve in New Jersey, in coordination with the Silas Little Experimental Forest.

Key Findings

• Terrestrial laser scanning can provide fuel structure and biomass estimates to describe forest conditions and management outcomes, as well as to gather fuel inputs for fire behavior models. 
• Terrestrial laser scanning can scan a plot in about 4 minutes, which is a fraction of the time it would take a person to collect data using traditional means. 
• Terrestrial laser scanning is easily accomplished with the push of a single button. 
• As field methods and data analysis procedures improve, Northern Research Station scientists are developing clear and open-access protocols describing how to use TLS technology with field data to optimize the monitoring forest condition and management outcomes, especially those related to wildland fire. This will enable managers to adopt the TLS approach to increase their ability to document and describe management needs and outcomes.

Approach

Conceptualization of data preparation, modeling, and assessment and comparison workflows. 

For terrestrial laser scanning to be useful in wildland fire and forestry applications, scientists first need to develop methods to predict vegetation characteristics and conditions from the raw LiDAR data (i.e., amount and spatial distribution of different types of vegetation or debris that can burn in a fire and their change from fuel treatments). This is done by evaluating the relationships between physical or traditionally measured forest characteristics and TLS data using statistics and mathematics. The results then provide a way to automatically predict forest characteristics of interest from the TLS data (e.g., coordinates of points in space). NRS scientists have been doing this by taking TLS measurements in conjunction with physical measurements at the Silas Little Experimental Forest and on state land in New Jersey. Partnerships with universities, the National Forest System, US Fish and Wildlife Service, and the US Department of Defense are guiding the collection of data on numerous other landscapes.

Examples of recent investigations include evaluating the number of shrubs to measure per plot to produce accurate shrub height estimates from TLS, using TLS measurements to estimate burn severity, and estimating several different categories of fuel biomass using TLS measurements. Using a synthetic scanning environment to explore simulated data can help rapidly improve how field and analysis approaches in TLS scanning are designed and implemented across unique vegetation types. This research advances our understanding of how TLS measurements can be used to reflect fuel conditions and informs the measurement and analysis protocols used to make these comparisons. Beyond numerically describing management needs and outcomes, the results of TLS scanning can be used to quickly parameterize fire behavior models to simulate prescribed fires and wildfires under realistic conditions.

Expected Outcomes

NRS research on the use of TLS to monitor fuels, forest conditions, and management effects supports the next generation of fuels management, promoting the use of TLS among land managers to plan prescribed fires and predict the effects of wildfire on forests. With both internal USDA Forest Service and external collaborators, they are developing clear, straightforward, and easily accessible protocols to measure fuels in conjunction with TLS measurements and relate these measurements to fire effects.