California’s fire regimes are changing rapidly due to complex and interconnected factors including fuel loads (i.e., bottom-up controls due to fire suppression, fuel accumulation, and forest management practices) and climate (i.e. top-down controls driven by winds, changing temperature and aridity regimes). Efforts to map and monitor California’s changing fire regimes rely on sophisticated models parameterized with detailed field and remotely sensed data, especially airborne laser scanner (ALS, or small-footprint lidar) measurements of forest 3D structure to estimate surface, ladder, and canopy fuels, to model fire behavior, and to assess wildfire severity. However, ALS is constrained by high costs, slow delivery times, large data volumes, inconsistency between products, and a scarcity of repeat sampling in particular areas. Spaceborne large-footprint lidar from NASA’s Global Ecosystem Dynamics Investigation (GEDI; https://gedi.umd.edu) mission, on the other hand, provides free, timely, and consistent multitemporal information on forest structure at near-global scales. As the first mission designed specifically for monitoring near-global vegetation structure, GEDI offers great potential for wildfire applications.

This project’s overarching objective is to demonstrate the value of GEDI spaceborne lidar for systematic and timely wildfire severity prediction, and to assess how GEDI-detected structural changes due to wildfire and fuels treatments alter predictions of future wildfire severity in California forests. Our analysis will focus on conifer, hardwood, and mixed closed-canopy forests to open-canopy woodlands in the North Coast, Central Coast and Sierra Nevada regions of California, especially Demonstration State Forests and priority landscapes defined by Fire and Resource Assessment Program Reduce Wildfire Threat to Communities and Reducing Wildfire Risk to Forest Ecosystem Services maps. Specifically, we will: 1) use machine learning to relate wildfire severity from large recent fires (2019-2021) to GEDI structural metrics; 2) demonstrate the sensitivity of GEDI metrics to changes in forest structure due to wildfire severity and treatments for use in future wildfire severity prediction; 3) increase the spatial and temporal resolution and extent of wildfire severity predictions spatially-continuous spaceborne imagery and radar datasets calibrated with current GEDI measurements; and 4) deepen our understanding of predicted wildfire severity and explore the potential for timely updates to hazard maps by comparing our results to existing FRAP priority landscape maps (wildland urban interface [WUI] and watershed). Our research will provide insights into several CAL FIRE priority topics, including prediction and future climate, management strategies, contemporary fire regimes, and WUI areas. The proposed project includes the GEDI Science Lead and Team members, and will leverage partnerships from a network of collaborators to provide robust field data and on-the-ground expert opinion for model calibration and validation.

No publications at this time.

Contact Information:

Mathew Clark (PI)
matthew.clark@sonoma.edu

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