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

Abstract

Wildfire shapes vegetation assemblages in Mediterranean ecosystems, such as those in the state of California, United States. Successful restorative management of forests in-line with ecologically beneficial fire regimes relies on a thorough understanding of wildfire impacts on forest structure and fuel loads. As these data are often difficult to comprehensively measure on the ground, remote sensing approaches can be used to estimate forest structure and fuel load parameters over large spatial extents. Here, we analyze the capabilities of one such methodology, unoccupied aerial system structure from motion (UAS-SfM) from digital aerial photogrammetry, for mapping forest structure and wildfire impacts in the Mediterranean forests of northern California. To determine the ability of UAS-SfM to map the structure of mixed oak and conifer woodlands and to detect persistent changes caused by fire, we compared UAS-SfM derived metrics of terrain height and canopy structure to pre-fire airborne laser scanning (ALS) measurements. We found that UAS-SfM was able to accurately capture the forest’s upper-canopy structure, but was unable to resolve mid- and below-canopy structure. The addition of a normalized difference vegetation index (NDVI) ground point filter to the DTM generation process improved DTM root-mean-square error (RMSE) by ~1 m with an overall DTM RMSE of 2.12 m. Upper-canopy metrics (max height, 95th percentile height, and 75th percentile height) were highly correlated between ALS and UAS-SfM (r > +0.9), while lower-canopy metrics and metrics of density and vertical variation had little to no similarity. Two years after the 2017 Sonoma County Tubbs fire, we found significant decreases in UAS-SfM metrics of bulk canopy height and NDVI with increasing burn severity, indicating the lasting impact of the fire on vegetation health and structure. These results point to the utility of UAS-SfM as a monitoring tool in Mediterranean forests, especially for post-fire canopy changes and subsequent recovery.

Comparing Remote Sensing and Field-Based Approaches to Estimate Ladder Fuels and Predict Wildfire Burn Severity

“…We thus find that there is some value in UAS-SfM, particularly in forests with gaps in the canopy or relatively low CBH, such as oak woodlands or managed stands, where some lower-canopy points are detected in the SfM process. In addition, our previous research found multispectral UAS-SfM to be useful for monitoring changes in upper-canopy structure and greenness after wildfires (Reilly et al, 2021). We also note that multi-angle views can improve detection of sub-canopy structure with UAS-SfM (Lamping et al, 2021), a factor that we could not explore as we were constrained to a nadir view by our UAS and sensor equipment.…”

“…Since ALS data collection occurred prior to both the Tubbs and Glass Fires, changes in both forest structure and ladder fuels could be expected by the time of our field and remote sensing surveys. Reilly et al (2021) compared canopy metrics at Pepperwood between 2019 UAS-SfM data to the 2013 ALS data and found significant relationships between these methods for unburned sites. However, they did detect changes in canopy attributes with increasing wildfire severity (RdNBR).…”

“…Each zone had two autonomous flights at 120-m above-canopy height, 75% along-and across-track overlap in a crosshatch grid pattern, and a nadir view angle for the sensor. For more detailed information about UAS methods see Reilly et al (2021).…”

“…When UAS are flown to capture images with sufficient overlap (e.g., 75-85%), Structure from Motion (SfM) data processing can generate 3D point clouds of vegetation structure, which has the potential to quantify fuel loads. Although UAS-SfM generally provides highly variable or unresolved data of below-canopy vegetation structure (Wallace et al, 2016;Graham et al, 2019;Hillman et al, 2021a,b;Reilly et al, 2021), the technology has been used to successfully estimate canopy height and cover, DBH, and stem count (Wallace et al, 2016;Shin et al, 2018;Puliti et al, 2020;Reilly et al, 2021).…”

Mathematical Simulation of Forest Fuel Pyrolysis and Crown Forest Fire Impact for Forest Fire Danger and Risk Assessment

“…Each group of tasks is important in terms of minimizing damage from forest fires. This is equally true for the Russian Federation, Canada, Australia or the countries of Southern Europe [111][112][113][114][115][116][117][118][119][120][121][122][123][124][125]. Perhaps, for the Mediterranean region, these tasks are even more important, since catastrophic forest fires have been observed there in recent years.…”