Vegetation Remote Sensing
We use a variety of remote sensing tools to map vegetation, retrieve biophysical properties, and investigate disturbance. We are using hyperspectral and multispectral time series data to examine how ecosystems are impacted by drought and how vegetation recovers in response to the combined pressures of wildfire and warming climate. We are using hyperspectral and multispectral remote sensing to map vegetation types and plant species, including invasive species. We are also testing methods of estimating variables like canopy water content. Some of this work involves developing methods and applications for a next-generation satellite hyperspectral mission, the National Academies designated Surface Biology and Geology (SBG) mission.
Safety zones protect wildland firefighters from dangerous heat exposure, reducing firefighter injuries and fatalities. Escape routes provide firefighters with a path to reach safety zones. We are using lidar remote sensing and geospatial modeling to map safety zone size and suitability. We are also using these tools to map the time required for firefighters to traverse escape routes based on slope, vegetation density, and surface roughness.
Trace Gas Plume Mapping
Carbon dioxide and methane are gases that occur at low concentrations within the atmosphere, but have substantial impacts on Earth's climate. Absorption by these gases at key wavelengths can be measured using imaging spectrometer (hyperspectral) data, revealing point sources and allowing concentration retrieval. We are working with data acquired by the Next-Generation Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) to map plumes from oil and natural gas infrastructure, landfills, waste treatment, and power plants. Our most recent project is using data from a joint NASA-ISRO campaign acquiring AVIRIS-NG data over India.
Remote Sensing of Fuels and Fires
The moisture, type, and amount of fuels have a big impact on wildfire behavior. Some of our work with fires has focused on developing methods for using time series multispectral data and hyperspectral data to map these fuel properties. For an NSF Coupled Natural-Human Systems project, we are using lidar data to map firewood resources in areas utilized by Navajo people in southern Utah. For active wildfires, we have developed new models that use hyperspectral data to map fire temperature and fractional area.
We are using time series remote sensing to examine links between climate and wildfire, including antecedent climate conditions in the months prior to large wildfires. We are also investigating how climate immediately following fires can impact recovery trajectories.