Researchers from the University of Florida’s School of Forest, Fisheries, and Geomatics Sciences (SFFGS) completed a two-week field campaign across Fish Lake National Forest, Utah, and North Kaibab National Forest, Arizona, that will advance next-generation wildfire monitoring and decision-support systems. Scientists from the Forest Biometrics, Remote Sensing and Artificial Intelligence Laboratory (SilvaLab) collected field and Light Detection and Ranging (LiDAR) data from June 17 to July 2.
The SilvaLab field crew included UF Associate Professor of Quantitative Forest Science and Principal Investigator (PI) Carlos Alberto Silva, Ph.D., Postdoctoral Researcher and Field Crew Lead Inacio Bueno, Ph.D., Postdoctoral Researcher Cesar Alvites, Ph.D., Postdoctoral Researcher Nadeem Fareed, Ph.D., SilvaLab Manager Ana Terra, UF Master’s Student Alex Gaskins, UF Undergraduate Student Simon Caldwell, and Research Assistant Durga Siva Deepak.
The campaign also brought together Andrew Hudak, Ph.D., co-principal investigator from the USDA Forest Service, Rocky Mountain Research Station and collaborators from multiple institutions, including Mickey Campbell, Ph.D., University of Utah, Manuel Gomez Roux from University of Valladolid, Kathleen Clough from the Desert Research Institute, and Jake Howell from University of Utah.
This multidisciplinary collaboration highlights the importance of partnerships among universities, federal agencies, and research institutions in addressing one of the nation’s most pressing environmental challenges.
The campaign is part of the Ecosystem Monitoring System for 4D Fuel Mapping and Decision Support (EMS4D) project, led by Silva and Hudak.
The project aims to develop an open-source ecosystem monitoring system that combines field observations, terrestrial and mobile laser scanning (TLS and MLS), airborne and satellite LiDAR, artificial intelligence, and cloud computing to produce dynamic maps of vegetation structure and forest fuels across the western United States. The resulting products will help land managers assess wildfire risk, evaluate fuel treatment strategies, and improve forest resilience in an era of increasing wildfire activity.
Wildfire fuel consists of vegetation and organic materials that can burn including grass, shrubs, trees, dead leaves, sticks, logs, and organic soils such as peat or duff.
During the campaign, the team collected an extensive suite of field measurements, including detailed inventories of tree attributes (species, diameter at breast height, total height, crown characteristics, and crown base height) as well as surface, ladder, and canopy fuel measurements. In parallel, the team acquired high-resolution terrestrial laser scanning (TLS) and mobile laser scanning (MLS) datasets to capture the three-dimensional structure of post-fire forest ecosystems.
These field and LiDAR observations will be used to quantify fuel consumption following prescribed fire and wildfire, improve the characterization of forest fuel dynamics, and develop and validate next-generation artificial intelligence models for scalable mapping of forest structure, surface fuels, ladder fuels, canopy fuels, fuel consumption, and fire behavior across the western United States.
“Field data are the foundation of everything we build,” said PI Silva. “By integrating detailed field measurements with terrestrial and mobile LiDAR, satellite observations, and artificial intelligence, we are creating the next generation of tools that will help land managers better understand wildfire impacts, predict fuel dynamics, and make informed management decisions.”
Working across recently burned landscapes and diverse forest conditions, the team collected thousands of field observations and high-resolution LiDAR measurements that will support the development of new open-source tools for fuel mapping, wildfire behavior modeling, ecosystem monitoring, and decision support for forest management.
“Every successful field campaign represents months of planning and the dedication of an outstanding team,” Silva added. “The data collected this summer will help advance the science of wildfire management while providing practical, science-based tools that support forest managers in protecting communities, restoring resilient forests, and reducing future wildfire risk.”
The datasets collected during the 2026 summer campaign will directly contribute to the EMS4D platform, providing new capabilities for mapping forest fuels, estimating fuel consumption, monitoring ecosystem change through time, and supporting science-based wildfire management across the western United States.
Ultimately, EMS4D will provide land managers with an open, scalable framework for monitoring fuel dynamics, evaluating treatment effectiveness, and improving the resilience of forests facing increasingly frequent and severe wildfires.
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