Birgit Peterson, PhD
Dr. Peterson received her PhD in Geography from the University of Maryland. She has been at USGS EROS for that last 10 plus years, supporting various fire science projects, including the LANDFIRE program.
Dr. Peterson received her PhD in Geography from the University of Maryland. She has been at USGS EROS for that last 10 plus years, supporting various fire science projects, including the LANDFIRE program. Her primary interest is in leverage remotely sensed data to assess vegetation structure, especially as it relates to wildland fire.
Science and Products
Filter Total Items: 24
LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure
LANDFIRE (LF) National (2001) was the original product suite of the LANDFIRE program, which included Existing Vegetation Cover (EVC), Height (EVH), and Type (EVT). Subsequent refinements after feedback from data users resulted in updated products, referred to as LF 2001, that now served as LANDFIRE’s baseline datasets and are the basis for all subsequent LANDFIRE updates. These updates...
Authors
Joshua J. Picotte, Daryn Dockter, Jordan Long, Brian L. Tolk, Anne Davidson, Birgit Peterson
Prototype downscaling algorithm for MODIS Satellite 1 km daytime active fire detections Prototype downscaling algorithm for MODIS Satellite 1 km daytime active fire detections
This work presents development of an algorithm to reduce the spatial uncertainty of active fire locations within the 1 km MODerate resolution Imaging Spectroradiometer (MODIS Aqua and Terra) daytime detection footprint. The algorithm is developed using the finer 500 m reflective bands by leveraging on the increase in 2.13 μm shortwave infrared reflectance due to the burning components as...
Authors
Sanath S. Kumar, Joshua J. Picotte, Birgit Peterson
Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction
To protect ecosystem services and the increasing wildland urban interface in a world with fire, comprehensive maps of wildland fuels are needed to predict fire behavior and effects. Traditionally, fuels have been categorized into a classification scheme whereby a single metric represents vegetation composition and structure, which can then be parameterized based on variable vegetation...
Authors
E. Natasha Stavros, Janice Coen, Birgit Peterson, Harshvardhan Singh, Kama Kennedy, Carlos Ramirez, David Schimel
LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response
The LANDFIRE Program produces national scale vegetation, fuels, fire regimes, and landscape disturbance data for the entire U.S. These data products have been used to model the potential impacts of fire on the landscape [1], the wildfire risks associated with land and resource management [2, 3], and those near population centers and accompanying Wildland Urban Interface zones [4], as...
Authors
Joshua J. Picotte, Jordan Long, Birgit Peterson, Kurtis Nelson
Enhanced canopy fuel mapping by integrating lidar data Enhanced canopy fuel mapping by integrating lidar data
Background The Wildfire Sciences Team at the U.S. Geological Survey’s Earth Resources Observation and Science Center produces vegetation type, vegetation structure, and fuel products for the United States, primarily through the Landscape Fire and Resource Management Planning Tools (LANDFIRE) program. LANDFIRE products are used across disciplines for a variety of applications. The...
Authors
Birgit E. Peterson, Kurtis J. Nelson
1984–2010 trends in fire burn severity and area for the conterminous US 1984–2010 trends in fire burn severity and area for the conterminous US
Burn severity products created by the Monitoring Trends in Burn Severity (MTBS) project were used to analyse historical trends in burn severity. Using a severity metric calculated by modelling the cumulative distribution of differenced Normalized Burn Ratio (dNBR) and Relativized dNBR (RdNBR) data, we examined burn area and burn severity of 4893 historical fires (1984–2010) distributed...
Authors
Joshua J. Picotte, Birgit E. Peterson, Gretchen Meier, Stephen M. Howard
Science and Products
Filter Total Items: 24
LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure
LANDFIRE (LF) National (2001) was the original product suite of the LANDFIRE program, which included Existing Vegetation Cover (EVC), Height (EVH), and Type (EVT). Subsequent refinements after feedback from data users resulted in updated products, referred to as LF 2001, that now served as LANDFIRE’s baseline datasets and are the basis for all subsequent LANDFIRE updates. These updates...
Authors
Joshua J. Picotte, Daryn Dockter, Jordan Long, Brian L. Tolk, Anne Davidson, Birgit Peterson
Prototype downscaling algorithm for MODIS Satellite 1 km daytime active fire detections Prototype downscaling algorithm for MODIS Satellite 1 km daytime active fire detections
This work presents development of an algorithm to reduce the spatial uncertainty of active fire locations within the 1 km MODerate resolution Imaging Spectroradiometer (MODIS Aqua and Terra) daytime detection footprint. The algorithm is developed using the finer 500 m reflective bands by leveraging on the increase in 2.13 μm shortwave infrared reflectance due to the burning components as...
Authors
Sanath S. Kumar, Joshua J. Picotte, Birgit Peterson
Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction
To protect ecosystem services and the increasing wildland urban interface in a world with fire, comprehensive maps of wildland fuels are needed to predict fire behavior and effects. Traditionally, fuels have been categorized into a classification scheme whereby a single metric represents vegetation composition and structure, which can then be parameterized based on variable vegetation...
Authors
E. Natasha Stavros, Janice Coen, Birgit Peterson, Harshvardhan Singh, Kama Kennedy, Carlos Ramirez, David Schimel
LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response
The LANDFIRE Program produces national scale vegetation, fuels, fire regimes, and landscape disturbance data for the entire U.S. These data products have been used to model the potential impacts of fire on the landscape [1], the wildfire risks associated with land and resource management [2, 3], and those near population centers and accompanying Wildland Urban Interface zones [4], as...
Authors
Joshua J. Picotte, Jordan Long, Birgit Peterson, Kurtis Nelson
Enhanced canopy fuel mapping by integrating lidar data Enhanced canopy fuel mapping by integrating lidar data
Background The Wildfire Sciences Team at the U.S. Geological Survey’s Earth Resources Observation and Science Center produces vegetation type, vegetation structure, and fuel products for the United States, primarily through the Landscape Fire and Resource Management Planning Tools (LANDFIRE) program. LANDFIRE products are used across disciplines for a variety of applications. The...
Authors
Birgit E. Peterson, Kurtis J. Nelson
1984–2010 trends in fire burn severity and area for the conterminous US 1984–2010 trends in fire burn severity and area for the conterminous US
Burn severity products created by the Monitoring Trends in Burn Severity (MTBS) project were used to analyse historical trends in burn severity. Using a severity metric calculated by modelling the cumulative distribution of differenced Normalized Burn Ratio (dNBR) and Relativized dNBR (RdNBR) data, we examined burn area and burn severity of 4893 historical fires (1984–2010) distributed...
Authors
Joshua J. Picotte, Birgit E. Peterson, Gretchen Meier, Stephen M. Howard