Data Overview
Mapped attributes:
- Fuel consumption derived from ALS data
- Post-fire fuel load derived from ALS data
- Pre-fire fuel load derived from ALS data
- Fuel consumption derived from FCCS data
- Post-fire fuel load derived from FCCS data
- Pre-fire fuel load derived from FCCS data
Supplements:
- ALS data extent
- Keithly fire perimeter
- Keithly AOI fire perimeter
Description
Landscape scale estimates of pre-fire fuel load and fuel consumption are valuable resources for land managers and scientists. We used multitemporal airborne laser scanning (ALS), combined with field data, to empirically model these variables at fine scales (5 m resolution). We acquired Fuel Characteristic Classification System (FCCS) estimates of fuel load through LANDFIRE (30 m resolution) and estimated fuel consumption using CONSUME in the software program Fuel and Fire Tools (FFT). This data publication contains pre/post fire fuel load and fuel consumption for the 2018 Keithly Fire (Idaho, USA) using each of the ALS and FCCS approaches. We used these data to compare the approaches and to examine the effect of differing spatial resolution. The data may also be used for studying fire behavior, fire effects, and smoke emissions at these fires. Further detail on these data can be found in McCarley et al. 2022.
Units
The units for all fuel estimates are megagrams per hectare. Negative consumption estimates in the ALS data correspond to vegetation growth.
Coordinate Reference System
Data is projected in WGS84 UTM Zone 11N for Keithly (EPSG 32611).
Credit
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use either the data citation or the journal article citation:
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. 2022. Keithly Fire Fuel and Fuel Consumption. WIFIRE. https://doi.org/10.48792/W2RP4S
McCarley, T.R., A.T. Hudak, J.C. Restaino, N.H. French, M. Billmire, R.D. Ottmar, B. Haas, T. Goulden and R. Volkamer. (2022) A comparison of multitemporal airborne laser scanning data and the Fuel Characteristics Classification System for estimating fuel load and consumption. Journal of Geophysical Research – Biogeosciences 127, e2021JG006733. https://doi.org/10.1029/2021JG006733.