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
Improving forest structure mapping and regeneration prediction with multi-scale lidar observations
To make informed decisions, land managers require knowledge about the state of the ecosystems present. Vegetation structure is a key indicator of the state of forested systems; it influences habitat suitability, water quality and runoff, microclimate, and informs wildfire-related characteristics such as fuel loads, burn severity, and post-fire regeneration. Field data used to derive vegetation st
Evaluation and testing of standardized forest vegetation metrics derived from lidar data
The USGS 3D Elevation Program (3DEP) is managing the acquisition of lidar data across the Nation for high resolution mapping of the land surface, useful for multiple applications. Lidar data is initially collected as 3-dimensional “point clouds” that map the interaction of the airborne laser with earth surface features, including vegetation, buildings, and ground features. Generally the product of
Black Hills Region South Dakota 2017 Legion Lake Fire Burned and Unburned Plot Measurements
U.S Geological Survey (USGS) scientists conducted field data collection efforts during the time periods of September 5 - 14, 2018, November 8 - 13, 2018, June 18 - 27, 2019, July 30 - August 8, 2019, September 13 - 19, 2019, and June 23 - July 1, 2020. These efforts used a combination of technologies to map twenty burned and twelve unburned forest plots at eleven sites in the Black Hills of South
Filter Total Items: 20
The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates
LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected
Authors
Sanath Sathyachandran Kumar, Brian Tolk, Ray Dittmeier, Joshua J. Picotte, Inga P. La Puma, Birgit Peterson, Timothy Duckett Hatten
Using simulated GEDI waveforms to evaluate the effects of beam sensitivity and terrain slope on GEDI L2A relative height metrics over the Brazilian Amazon Forest
The vertical structure of forests provides important parameters for estimating aboveground biomass (AGB) and it can be measured by LiDAR sensors. The Global Ecosystem Dynamics Investigation (GEDI) full-waveform LiDAR sensor collects data systematically over the Earth’s surface from the International Space Station. Since GEDI became operational, it has collected billions of ~25 m diameter footprint
Authors
Pedro V. C. Oliveira, Xiaoyang Zhang, Birgit Peterson, Jean P. Ometto
U.S. Geological Survey wildland fire science strategic plan, 2021–26
The U.S. Geological Survey (USGS) Wildland Fire Science Strategic Plan defines critical, core fire science capabilities for understanding fire-related and fire-responsive earth system processes and patterns, and informing management decision making. Developed by USGS fire scientists and executive leadership, and informed by conversations with external stakeholders, the Strategic Plan is aligned wi
Authors
Paul F. Steblein, Rachel A. Loehman, Mark P. Miller, Joseph R. Holomuzki, Suzanna C. Soileau, Matthew L. Brooks, Mia Drane-Maury, Hannah M. Hamilton, Jason W. Kean, Jon E. Keeley, Robert R. Mason,, Alexa McKerrow, James Meldrum, Edmund B. Molder, Sheila F. Murphy, Birgit Peterson, Geoffrey S. Plumlee, Douglas J. Shinneman, Phillip J. van Mantgem, Alison York
By
Ecosystems Mission Area, Natural Hazards Mission Area, Science Synthesis, Analysis and Research Program, Science Analytics and Synthesis (SAS) Program, Alaska Science Center, Earth Resources Observation and Science (EROS) Center , Forest and Rangeland Ecosystem Science Center, Fort Collins Science Center, Geologic Hazards Science Center, Geology, Geophysics, and Geochemistry Science Center, Western Ecological Research Center (WERC), Wildland Fire Science
Potential underestimation of satellite fire radiative power retrievals over gas flares and wildland fires
Fire Radiative Power (FRP) is related to fire combustion rates and is used to quantify the atmospheric emissions of greenhouse gases and aerosols. FRP over gas flares and wildfires can be retrieved remotely using satellites that observe in shortwave infrared (SWIR) to middle infrared (MIR) wavelengths. Heritage techniques to retrieve FRP developed for wildland fires using the MIR 4 μm radiances ha
Authors
Sanath S. Kumar, John Edward Hult, Joshua J. Picotte, Birgit Peterson
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 account for
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
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 compared
Authors
Sanath S. Kumar, Joshua J. Picotte, Birgit Peterson
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 well as many
Authors
Joshua J. Picotte, Jordan Long, Birgit Peterson, Kurtis Nelson
Enhanced canopy fuel mapping by integrating lidar data
BackgroundThe 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 LANDFIRE data reta
Authors
Birgit E. Peterson, Kurtis J. Nelson
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 across the
Authors
Joshua J. Picotte, Birgit E. Peterson, Gretchen Meier, Stephen M. Howard
Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska
Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) compos
Authors
Lei Ji, Bruce K. Wylie, Dana R. N. Brown, Birgit E. Peterson, Heather D. Alexander, Michelle C. Mack, Jennifer R. Rover, Mark P. Waldrop, Jack W. McFarland, Xuexia Chen, Neal J. Pastick
Automated integration of lidar into the LANDFIRE product suite
Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure. Although lidar data are increasingly avai
Authors
Birgit Peterson, Kurtis Nelson, Carl Seielstad, Jason M. Stoker, W. Matt Jolly, Russell Parsons
Mapping forest height in Alaska using GLAS, Landsat composites, and airborne LiDAR
Vegetation structure, including forest canopy height, is an important input variable to fire behavior modeling systems for simulating wildfire behavior. As such, forest canopy height is one of a nationwide suite of products generated by the LANDFIRE program. In the past, LANDFIRE has relied on a combination of field observations and Landsat imagery to develop existing vegetation structure products
Authors
Birgit Peterson, Kurtis Nelson
Science and Products
Improving forest structure mapping and regeneration prediction with multi-scale lidar observations
To make informed decisions, land managers require knowledge about the state of the ecosystems present. Vegetation structure is a key indicator of the state of forested systems; it influences habitat suitability, water quality and runoff, microclimate, and informs wildfire-related characteristics such as fuel loads, burn severity, and post-fire regeneration. Field data used to derive vegetation st
Evaluation and testing of standardized forest vegetation metrics derived from lidar data
The USGS 3D Elevation Program (3DEP) is managing the acquisition of lidar data across the Nation for high resolution mapping of the land surface, useful for multiple applications. Lidar data is initially collected as 3-dimensional “point clouds” that map the interaction of the airborne laser with earth surface features, including vegetation, buildings, and ground features. Generally the product of
Black Hills Region South Dakota 2017 Legion Lake Fire Burned and Unburned Plot Measurements
U.S Geological Survey (USGS) scientists conducted field data collection efforts during the time periods of September 5 - 14, 2018, November 8 - 13, 2018, June 18 - 27, 2019, July 30 - August 8, 2019, September 13 - 19, 2019, and June 23 - July 1, 2020. These efforts used a combination of technologies to map twenty burned and twelve unburned forest plots at eleven sites in the Black Hills of South
Filter Total Items: 20
The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates
LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected
Authors
Sanath Sathyachandran Kumar, Brian Tolk, Ray Dittmeier, Joshua J. Picotte, Inga P. La Puma, Birgit Peterson, Timothy Duckett Hatten
Using simulated GEDI waveforms to evaluate the effects of beam sensitivity and terrain slope on GEDI L2A relative height metrics over the Brazilian Amazon Forest
The vertical structure of forests provides important parameters for estimating aboveground biomass (AGB) and it can be measured by LiDAR sensors. The Global Ecosystem Dynamics Investigation (GEDI) full-waveform LiDAR sensor collects data systematically over the Earth’s surface from the International Space Station. Since GEDI became operational, it has collected billions of ~25 m diameter footprint
Authors
Pedro V. C. Oliveira, Xiaoyang Zhang, Birgit Peterson, Jean P. Ometto
U.S. Geological Survey wildland fire science strategic plan, 2021–26
The U.S. Geological Survey (USGS) Wildland Fire Science Strategic Plan defines critical, core fire science capabilities for understanding fire-related and fire-responsive earth system processes and patterns, and informing management decision making. Developed by USGS fire scientists and executive leadership, and informed by conversations with external stakeholders, the Strategic Plan is aligned wi
Authors
Paul F. Steblein, Rachel A. Loehman, Mark P. Miller, Joseph R. Holomuzki, Suzanna C. Soileau, Matthew L. Brooks, Mia Drane-Maury, Hannah M. Hamilton, Jason W. Kean, Jon E. Keeley, Robert R. Mason,, Alexa McKerrow, James Meldrum, Edmund B. Molder, Sheila F. Murphy, Birgit Peterson, Geoffrey S. Plumlee, Douglas J. Shinneman, Phillip J. van Mantgem, Alison York
By
Ecosystems Mission Area, Natural Hazards Mission Area, Science Synthesis, Analysis and Research Program, Science Analytics and Synthesis (SAS) Program, Alaska Science Center, Earth Resources Observation and Science (EROS) Center , Forest and Rangeland Ecosystem Science Center, Fort Collins Science Center, Geologic Hazards Science Center, Geology, Geophysics, and Geochemistry Science Center, Western Ecological Research Center (WERC), Wildland Fire Science
Potential underestimation of satellite fire radiative power retrievals over gas flares and wildland fires
Fire Radiative Power (FRP) is related to fire combustion rates and is used to quantify the atmospheric emissions of greenhouse gases and aerosols. FRP over gas flares and wildfires can be retrieved remotely using satellites that observe in shortwave infrared (SWIR) to middle infrared (MIR) wavelengths. Heritage techniques to retrieve FRP developed for wildland fires using the MIR 4 μm radiances ha
Authors
Sanath S. Kumar, John Edward Hult, Joshua J. Picotte, Birgit Peterson
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 account for
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
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 compared
Authors
Sanath S. Kumar, Joshua J. Picotte, Birgit Peterson
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 well as many
Authors
Joshua J. Picotte, Jordan Long, Birgit Peterson, Kurtis Nelson
Enhanced canopy fuel mapping by integrating lidar data
BackgroundThe 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 LANDFIRE data reta
Authors
Birgit E. Peterson, Kurtis J. Nelson
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 across the
Authors
Joshua J. Picotte, Birgit E. Peterson, Gretchen Meier, Stephen M. Howard
Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska
Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) compos
Authors
Lei Ji, Bruce K. Wylie, Dana R. N. Brown, Birgit E. Peterson, Heather D. Alexander, Michelle C. Mack, Jennifer R. Rover, Mark P. Waldrop, Jack W. McFarland, Xuexia Chen, Neal J. Pastick
Automated integration of lidar into the LANDFIRE product suite
Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure. Although lidar data are increasingly avai
Authors
Birgit Peterson, Kurtis Nelson, Carl Seielstad, Jason M. Stoker, W. Matt Jolly, Russell Parsons
Mapping forest height in Alaska using GLAS, Landsat composites, and airborne LiDAR
Vegetation structure, including forest canopy height, is an important input variable to fire behavior modeling systems for simulating wildfire behavior. As such, forest canopy height is one of a nationwide suite of products generated by the LANDFIRE program. In the past, LANDFIRE has relied on a combination of field observations and Landsat imagery to develop existing vegetation structure products
Authors
Birgit Peterson, Kurtis Nelson