Landowners and land managers in California are being encouraged now more than ever to manage forests to improve forest health. There are various approaches and tools that exist to estimate the impact of their forestry and timber management plans, but there are currently some issues related to these approaches. Specifically, exact aboveground biomass (AGB) in the study area is unknown, AGB allometries are incomplete or inaccurate for the species present, and fuel loads and distribution are difficult to measure, but very important to estimate. To address these issues, our research evaluates the use of innovative remote sensing techniques to rapidly and more accurately estimate AGB, calculate AGB allometric relationships to tree properties (e.g., DBH, height) for a range of tree species, and estimate crucial fuels parameters to help validate or refine fire probability and behavior models across diverse California forests. To accomplish these goals we use a state-of-the-art terrestrial laser scanner (TLS) and a low-cost unmanned aerial system (UAS), combined with modern data processing techniques, to acquire detailed measurements of 3-dimensional forest structure in coastal and southern Cascade forests of northern California. Specifically, our research focuses on two California State Demonstration Forests (Latour, Jackson) and the Pepperwood Preserve, a site in Sonoma County that focuses on science-based ecosystem research and management. At these sites, we acquire quantitative measurements of forest AGB and fuels parameters with TLS and UAS before and after implementation of forest fuels/health treatments, allowing us to assess effectiveness and impacts of different techniques. These measurements will assist with the reduction of wildfire risk to forests and wildfire threat to communities by evaluating a rapid method to assess fire fuels. In addition, the knowledge gained from this research will ultimately result in improved quantitative assessment of greenhouse gas impacts or improved management actions and/or policy related to the Forest Carbon Plan due to direct quantification of carbon via measurements of AGB.

Forbes, B., Reilly, S., Clark, M., Ferrell, R., Kelly, A., Krause, P., Matley, C., O’Neil, M., Villasenor, M., Disney, M. and Wilkes, P., 2022. Comparing Remote Sensing and Field-Based Approaches to Estimate Ladder Fuels and Predict Wildfire Burn Severity. Frontiers in Forests and Global Change, 5. https://doi.org/10.3389/ffgc.2022.818713

Reilly, S., Clark, M.L., Bentley, L.P., Matley, C., Piazza, E. and Oliveras Menor, I., 2021. The Potential of Multispectral Imagery and 3D Point Clouds from Unoccupied Aerial Systems (UAS) for Monitoring Forest Structure and the Impacts of Wildfire in Mediterranean-Climate Forests. Remote Sensing, 13(19), p.3810. https://doi.org/10.3390/rs13193810

L.P. Bentley, M. Clark, B. Forbes, P. Krause, S. Reilly, L. Blesius, A. Kelly. (2021) Remote sensing of 3D forest structure for fuels management and carbon accounting. CSU Geospatial Review, Summer 2021.

Barajas-Ritchie, A., P. Krause, B. Forbes, L.P. Bentley. (2021) Optimizing Quantitative Structure Model (QSMs) parameters for Coastal Redwoods (Sequoia sempervirens) for accurate aboveground biomass. McNair Scholars Research Journal, Sonoma State University.

For more information on this project please visit:

The Bentley Lab website: 
https://lisapatrickbentley.org/?page_id=126

Contact Information:

Lisa Bentley, Ph.D. (PI)
lisa.bentley@sonoma.edu

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