A Comparison of Multitemporal Airborne Laser Scanning Data and the Fuel Characteristics Classification System for Estimating Fuel Load and Consumption. Issue 5 (23rd May 2022)

• Record Type: Journal Article
• Authors: McCarley, T. Ryan; Hudak, Andrew T.; Restaino, Joseph C.; Billmire, Michael; French, Nancy H. F.; Ottmar, Roger D.; Hass, Bridget; Zarzana, Kyle; Goulden, Tristan; Volkamer, Rainer
• Is Part Of: Journal of geophysical research. Volume 127:Issue 5(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-23
• Subjects: wildfire -- biomass consumption -- rangeland -- forest -- airborne lidar -- FCCS -- LANDFIRE -- inland northwest USA; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1029/2021JG006733
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: Characterizing pre‐fire fuel load and fuel consumption are critical for assessing fire behavior, fire effects, and smoke emissions. Two approaches for quantifying fuel load are airborne laser scanning (ALS) and the Fuel Characteristic Classification System (FCCS). The implementation of multitemporal ALS (i.e., the use of two or more ALS datasets across time at a given location) in conjunction with empirical models trained with field data can be used to measure fuel and estimate fuel consumption from a fire. FCCS, adapted for use in LANDFIRE (LF), provides 30 m resolution estimates of fuel load across the contiguous United States and can be used to estimate fuel consumption through software programs such as Fuel and Fire Tools (FFT). This study compares the two approaches for two wildfires in the northwestern United States having predominantly sagebrush steppe and ponderosa pine savanna ecosystems. The results showed that the LF FCCS approach yielded higher pre‐fire fuel loads and fuel consumption than the ALS approach and that the coarser scale LF FCCS data did not capture as much heterogeneity as the ALS data. At Tepee, 50.0% of the difference in fuel load and 87.3% of the difference in fuel consumption were associated with distinguishing sparse trees from rangeland. At Keithly, this only accounted for 8.2% and 8.6% of the differences, demonstrating the significance of capturing heterogeneity in rangeland vegetation structure and fire effects. Our results suggest future opportunities to use ALS data to better parametrize fine‐scale fuel load variability that LF FCCS does not capture. Plain Language Summary: The ability to quantify live and dead vegetation, also known as fuel available to burn in a fire, is important for understanding fire behavior, fire effects, and smoke emissions. Our study compares two methods of measuring pre‐fire fuel and estimating the amount of fuel consumed at two wildfires in the northwestern U.S. dominated by sagebrush, grassland, and pine savanna. One method, airborne laser scanning (ALS), uses an aircraft mounted sensor to created detailed 3D maps of vegetation structure. Flights before and after the fire are used to estimate fuel consumption. The other method, the Fuel Characteristic Classification System (FCCS), is a predefined map of fuels and their distinguishing characteristics, which can be easily fed into existing mathematical models for estimating fuel consumption. In our results, we observed the FCCS method to overestimate fuel load and fuel consumption compared to the ALS method. We think this is mostly a result of the different levels of spatial detail between approaches, since the ALS method captured more of the variability that exists in sparse forest and rangeland fuels than FCCS. Future efforts may be able to combine these approaches to better quantify fuel. Key Points: This study compared two methods of determining fuel load and fuel consumption for two wildfires in the inland northwest LANDFIRE Fuel Characteristics Classification Systems overestimated fuel load and consumption compared to airborne laser scanning Much of the difference was attributed to the difference in scale between the two approaches