Project Grant NA23OAR0210334
- This National Science Foundation Project Grant of $274,929 will support Morphobotics LLC to develop an automated sub-canopy 3D forest mapping solution using uncrewed aerial vehicles. The goal is to produce a high-fidelity, open-source UAV exploration environment with 3D mapping capabilities meeting payload constraints for use in prescribed forest burn environmental assessments and spatial fire modeling. This addresses a need under the NSF Technology, Innovation, and Partnerships program's...
- This Project Grant award from the U.S. Department of Agriculture's National Institute of Food and Agriculture (NIFA), under the Agriculture and Food Research Initiative (AFRI) program, aims to conceptualize and develop an autonomous unmanned aerial vehicle (UAV) system capable of navigating dense forest environments to collect high-resolution 3D data on forest structure and function. The $299,937 award to Northern Arizona University (NAU) will fund the "Project ClearWing" initiative,...
- The Morphobotics LLC was awarded a $299,280 project grant from the National Oceanic and Atmospheric Administration (NOAA) Small Business Innovation Research (SBIR) Program to develop a wildfire fuel mapping capability for unmanned aircraft systems (UAS). The goal is to estimate live fuel moisture content and map additional common wildfire modeling variables, such as vegetation type and arrangement, with a focus on subcanopy forest surveys. This will provide higher resolution dynamic data...
- Skyward LTD received a $174,998 Small Business Innovation Research (SBIR) Project Grant from the United States Department of Agriculture National Institute of Food and Agriculture to develop an edge-computing device and machine learning algorithms to process aerial imagery of wildfires in real time. The SBIR program aims to support technological innovation through the investment of federal research funds. Under this award, Skyward will benchmark hardware, software, and machine learning...
- Carnegie Mellon University was awarded a $1,199,997 Project Grant from the United States Department of Agriculture's National Institute of Food and Agriculture to develop technologies enabling coordinated multi-UAS sensing for rapid wildland fire assessment. Funded under NIFA's Agriculture and Food Research Initiative competitive grants program (CFDA #10.310), the three-year project will integrate experts from robotics, computational imaging, and wildland fire management. The researchers aim...
- This $650,000 federal Project Grant award from the U.S. Department of Agriculture's National Institute of Food and Agriculture (NIFA) Small Business Innovation Research (SBIR) Program supports the development of the PyreCAst platform, an advanced wildfire forecasting and risk management tool. The project aims to enhance wildfire prediction capabilities by integrating cutting-edge weather-fire models and statistical methods to provide more reliable and detailed predictions of fire behavior. By...
- This $370,000 project grant from the National Science Foundation's Engineering program (CFDA 47.041) will fund research at The University of Alabama in Huntsville to improve understanding of wildfire behavior in heterogeneous fuel mixtures from July 2022 to June 2025. The research aims to identify key physical and chemical processes controlling ignition and spread of fire in mixtures of living and dead fuels through controlled experiments and computational simulations. Lasers and other...
- The National Science Foundation awarded a $150,000 Project Grant to the National Center for Atmospheric Research (NCAR) under the Computer and Information Science and Engineering program (CFDA 47.070). The award will support development of a closed-loop sensing, modeling, and communications system to aid in wildfire detection, mapping, and prediction from July 2022 through June 2025. The system aims to leverage detailed 3D environmental models incorporating fuel, terrain, weather and other...
- The U.S. Bureau of Land Management, through the Joint Fire Science Program (CFDA 15.232), awarded a $499,865 cooperative agreement to The Regents of the University of Colorado to conduct research on landscape-scale fuel reduction strategies for grassland ecosystems in the wildland-urban interface (WUI) of Boulder County, Colorado. The project aims to: Measure grassland fuel characteristics to develop a custom fuel model for the region Experimentally test mowing, grazing, and prescribed fire fuel...
- Geometric Data Analytics Inc. received a $174,836 Project Grant award from the United States Department of Agriculture National Institute of Food and Agriculture to improve wildland firefighting capabilities. Funded through the Small Business Innovation Research (SBIR) Program / Small Business Technology Transfer (STTR) Program (CFDA 10.212), Geometric Data Analytics will place satellite-connected sensors in remote wildfire regions to gather and release real-time environmental data to...
PRESCRIBED BURNS ARE A CRITICAL ASPECT OF LAND MANAGEMENT, BUT THEY REQUIRE VEGETATION DATA THAT IS HARD TO OBTAIN AT HIGH RESOLUTION AND ON THE TIMESCALE REQUIRED. OUR AUTONOMOUS UAV COLLECTS CRITICAL FIRE MODELING VARIABLES THROUGH SUBCANOPY FLIGHT, ENABLING RAPID SURVEYS FOR FASTER AND SAFER BURN PLANNING. IN PHASE I, WE PROVED THE FEASIBILITY OF MAPPING LIVE FUEL MOISTURE CONTENT (LFMC) WITH SUBCANOPY UAV DATA, INCLUDING NEAR AND SHORTWAVE INFRARED. TO BUILD ON THIS, IN PHASE II WE WILL ENABLE THE UAV TO MEASURE THE REMAINING REQUIRED VARIABLES FOR FIRE BEHAVIOR PREDICTION, E.G., CANOPY BASE HEIGHT, STAND HEIGHT, AND CANOPY COVER. WE ADDITIONALLY PROPOSE A METHOD FOR MULTI-UAV COLLABORATION TO REDUCE TOTAL SURVEY TIME, SINCE SUBCANOPY FLIGHT SPEEDS ARE LIMITED. THIS TECHNOLOGY WILL ENABLE BURN MANAGERS TO INCREASE THEIR ANNUAL ACREAGE TREATED WITH PRESCRIBED BURNS, REDUCING THE RISK OF CATASTROPHIC WILDFIRES AT A TIME WHEN THAT IS CRITICALLY NEEDED.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 9/5/25 | ||
| Not listed | $0 | 12/20/23 | ||
| Not listed | $650.0k | 8/3/23 | ||
| Not listed | $650.0k | 8/3/23 |