Vegetation Remote Sensing
We use a variety of remote sensing tools to map vegetation, retrieve biophysical properties, and investigate disturbance. We are developing new methods for mapping non-photosynthetic vegetation, an indicator of drought stress and fire danger, which are being used to develop capabilities for future Landsat and hyperspectral satellite missions. We are also using lidar, hyperspectral, multispectral, and drone data to examine how ecosystems are impacted by disturbances like drought, insect outbreaks, and fire.
We develop methods that use remote sensing and GIS to improve wildland firefighter safety. 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. Both can be mapped using lidar remote sensing. Geospatial modeling can then be used to assess safety zone and escape route attributes as well as characteristics like visibility and situational awareness.
Greenhouse 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.
Remote Sensing of Fuels and Fires
Our lab has had a long history of developing remote sensing methods to estimate fuel properties, examining links between climate and fire, and investigating vegetation recovery following fire and its links to climate. We are currently engaged in using hyperspectral remote sensing to improve estimation of active fire properties, including fire radiative power, fire temperature, and area of fire within a pixel.