NASA’s Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) has released new datasets collected via field, airborne, Unmanned Aerial System (UAS), and balloon-based platforms for the FireSense project. These include:
- Vertical atmospheric profiles collected in New York via UAS during the 2024 total solar eclipse, and balloon-borne radiosondes reaching 29 km in Montana to support smoke transport and artificial intelligence (AI) fire weather models;
- Airborne Level 1B calibrated multispectral imagery across 50 spectral bands gathered via the MODIS/ASTER Airborne Simulator (MASTER) onboard the NASA B-200 during flights over California and the southern United States;
- Field measurements of in situ soil moisture, soil temperature profiles, and live fuel moisture from California’s Sedgwick Reserve that were used to establish pre-fire baseline conditions for calibrating airborne sensors.
The FireSense project aims to improve U.S. wildland fire management by working with operational agencies to refine and deliver NASA’s unique Earth science and technological capabilities. FireSense focuses on four types of assessments to support decisions before, during, and after wildland fires: pre-fire fuel conditions, active fire dynamics, post-fire impacts and threats, and air quality forecasting. Each type of assessment is co-developed with wildland fire management stakeholders.
More information on these datasets and others like them can be found on the FireSense project landing page.