Coupling Terrestrial Laser Scanning with 3D Fuel Biomass Sampling for Advancing Wildland Fuels Characterization

Abstract

The spatial pattern of surface fuelbeds in fire-dependent ecosystems are rarely captured using long-standing fuel sampling methods. New techniques, both field sampling and remote sensing, that capture vegetation fuel type, biomass, and volume at super fine-scales (cm to dm) in three-dimensions (3D) are critical to advancing forest fuel and wildland fire science. This is particularly true for computational fluid dynamics fire behavior models that operate in 3D and have implications for wildland fire operations and fire effects research. This study describes the coupling of new 3D field sampling data with terrestrial laser scanning (TLS) data to infer finescale fuel mass in 3D. We found that there are strong relationships between fine-scale mass and TLS occupied volume, porosity, and surface area, which were used to develop fine-scale prediction equations using TLS across vegetative fuel types, namely grasses and shrubs. The application of this novel 3D sampling technique to high resolution TLS data in this study represents a major advancement in understanding fire-vegetation feedbacks in highly managed fire-dependent ecosystems.

Terrestrial laser scan metrics predict surface vegetation biomass and consumption in a frequently burned southeastern U.S. ecosystem

“…x 10 -2 m 3 scale [27,32]. These methods use high-resolution TLS instrumentation that requires extensive processing to merge several TLS scans together and manually crop out each 3D vegetation plot or individual plant from the resulting merged 3D point cloud.…”

“…Furthermore, our single-scan and linear modeling approach is relatively simple compared to other more direct one-to-one coupled methods. Other methods include linking fine-scale mass and volume of understory vegetation down to the 1.0 m 3 and 6.25 × 10 −2 m 3 scale [27,32]. These methods use high-resolution TLS instrumentation that requires extensive processing to merge several TLS scans together and manually crop out each 3D vegetation plot or individual plant from the resulting merged 3D point cloud.…”

“…Over a decade ago, Loudermilk et al (2009) illustrated that traditional estimates of volume (sphere, cylinder) significantly overestimates the volume of vegetation, and that fine-scale volume estimated from TLS (voxel-based method) can be linked directly to fine-scale leaf area and mass of two common southeastern shrub species. Since then, field sampling has transitioned from 2D to 3D (Hawley et al 2018) and examples of using TLS to characterize understory vegetation while linking to estimates of biomass or leaf area have increased [28,[30][31][32][33].…”

Enabling AI innovation via data and model sharing: An overview of the NSF Convergence Accelerator Track D

“…2020; Rowell et al. 2020), this effort is developing BurnPro3D , a decision support platform to help the fire response and mitigation community understand risks and tradeoffs quickly and accurately to manage wildfires and conduct controlled burns more effectively. The project is developing knowledge management techniques for fusing and preparing diverse data for use in fire modeling; physics‐based ML for use in fire models and use of deep learning to understand complex fire behavior processes; constraint optimization methods addressing complex tradeoffs in the decision process for the placement and timing of controlled burns; and explainable AI for better interpretability of data and models by diverse users including fire managers, municipal leaders, and educators.…”

Seasonal weather and climate prediction over area burned in grasslands of northeast China

“…Burned grassland extent is influenced by regional climate change through increasing temperature which reduces fuel moisture and, thereby, increases flammability [13][14][15][16] , but climate change also alters productivity, biomass abundance, and carbon emissions 17,18 , all factors which drive fuel accumulation dynamics 13,19,20 . Further, effects of changing climates on fire activity may only manifest once critical thresholds are crossed 21,22 .…”