Understory fuels play an important role in wildfire spread and severity. It is important to quantify changes in fuels before and after wildfires across multiple spatial scales. Developments in LiDAR remote sensing present new avenues for quantifying these changes across different forest types. This project evaluates the use of handheld mobile LiDAR (HMLS) to measure surface fuels in Northern California redwood forests and oak woodlands. We aim to validate the use of HMLS to estimate surface fuel mass and determine the ideal voxel size for the most accurate measure of mass. Next, this method will be applied at a plot level to detect changes in surface fuels post-fire and post-logging. We hypothesize that voxelized HMLS data will accurately measure surface fuel volume and smaller voxel sizes will better estimate dry mass. We predict that surface fuels will decrease after wildfire and not change following logging at the plot level. The application of HMLS in this project presents an opportunity to expand the range of tools that land managers and conservationists could use to quantify and understand understory vegetation in fire-dependent ecosystems.

No publications at this time

For more information on this project please visit:
https://lisapatrickbentley.org/

Contact Information:

CAL FIRE Forest Health Research Program
FHResearch@fire.ca.gov