This project addresses the critical need for improved calibration and validation (CAL/VAL) of the landfire program's fuel metrics which are essential for wildfire behavior modeling and land management

The National Aeronautics and Space Administration Shared Services Center awarded the Board of Regents of Nevada System of Higher Education (operating as University of Nevada, Reno) $268,130 on January 1, 2026, under the Science program (CFDA 43.001) to develop improved calibration and validation datasets for the LANDFIRE program's fuel metrics used in wildfire behavior modeling and land management.

The project builds a comprehensive standardized 3D fuels dataset using terrestrial laser scanning (TLS) and airborne laser scanning (ALS) technologies to improve LANDFIRE fuels maps at national scales and subannual frequency. The deliverables include regularly updated fuel data products with quantified uncertainties that support better wildfire risk and spread modeling and more informed land management decisions. Current nationwide LANDFIRE fuel datasets are limited by insufficient and inconsistent surface and ladder fuel calibration and validation data, resulting in poorly characterized uncertainties and inconsistent updates.

The award spans January 1, 2026, through December 31, 2028, with performance in Reno, Nevada. Colorado State University's Francis Lab serves as a sub-recipient, contributing to the project by estimating canopy fuel metrics using publicly available ALS data across the United States, estimating downed woody debris size classes using publicly available Brown's transect data, and participating in integration meetings with the University of Nevada, Reno principal investigator and practitioner partners to ensure processing workflows meet end-user needs.

Currently landfire's nationwide fuel datasets are limited by a lack of sufficient and consistent surface and ladder fuel CAL/VAL data resulting in poorly characterized uncertainties and inconsistent updates. Our objective is to build a comprehensive standardized 3D fuels dataset using terrestrial (TLS) and airborne (ALS) laser scanning technologies and to use these data to improve landfire fuels maps at national scales and at a subannual frequency. The end goal is to provide regularly updated fuel data products with quantified uncertainties that support better wildfire risk and spread modeling and more informed land management decisions.