Kurtis Nelson
Kurtis Nelson is a Scientist with the USGS Earth Resources Observation and Science (EROS) Center in Sioux Falls, SD.
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
Fire Atlas
EROS work on fire activity in the United States includes the creation of an atlas of fire perimeters for fires occurring on U.S. National Wildlife Refuges from 1984 through 2013. Fire Atlas perimeter data provide information to refuge managers as they plan land management activities for their units. EROS analysts use data provided by the U.S. Fish and Wildlife Service (FWS), which include a name...
Fire Danger Forecast
USGS Earth Resources Observation and Science (EROS), in conjunction with the US Forest Service Pacific Southwest (PSW) Region, has developed several new products for understanding and forecasting the probability of large wildland fires on all land in the conterminous U.S.
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
Vegetation and Water Monitoring Datasets for selected locations in the Republic of the Marshall Islands from 2017-2022
The Republic of the Marshall Islands (RMI) is a sovereign Small Island State in the tropical central North Pacific Ocean. RMI is a nation of more than thirty atolls and islands, most of which are inhabited, dispersed across an exclusive economic zone (EEZ) over 2 million square kilometers. This data release contains raster datasets for vegetation and water monitoring including Normalized Differenc
Monthly Satellite-Estimated Precipitation Reports for the Republic of the Marshall Islands
The Republic of the Marshall Islands (RMI) is a nation of more than thirty low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone (EEZ) over 770,000 square miles in the tropical central North Pacific Ocean. Monitoring environmental conditions for potential drought risk is challenging in such a dispersed Island nation, and current drought hazard produ
Satellite precipitation estimates for selected locations in the Republic of the Marshall Islands
The Republic of the Marshall Islands (RMI) is a sovereign Small Island State in the tropical central North Pacific Ocean. RMI is a nation of more than thirty atolls and islands, most of which are inhabited, dispersed across an exclusive economic zone (EEZ) over 2 million square kilometers. This data release contains files of daily precipitation estimates beginning in 2001 for 23 inhabited sites in
Burn Severity Portal, a clearing house of fire severity and extent information (ver. 8.0, August 2024)
The various post-fire data products available on the Burn Severity Portal are produced using satellite imagery. The timing of the satellite imagery used, relative to the fire event, typically depends on the vegetation type and structure where the fire occurred. Each mapping program produces a suite of data products based on user intended user needs. You can find additional details in each of the a
Monitoring Trends in Burn Severity (ver. 9.0, August 2024)
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in th
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
Monitoring Trends in Burn Severity Thematic Burn Severity Mosaic (ver. 9.0, August 2024)
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S
Filter Total Items: 16
Developing version 2 of satellite-estimated precipitation monthly reports for selected locations in the Republic of the Marshall Islands
The Republic of the Marshall Islands (RMI; also known as the Marshall Islands) is a nation of more than 30 low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone over 770,000 square miles in the tropical central north Pacific Ocean. The study objectives and methods were originally presented in U.S. Geological Survey Data Report 1181 and are summarize
Authors
Gabriel B. Senay, David A. Helweg, Stefanie Kagone, Thomas Cecere, Tiare Eastmond, Amy Koch, Kurtis Nelson, Jack Randon
Developing satellite-estimated precipitation monthly reports for selected locations in the Republic of the Marshall Islands
The Republic of the Marshall Islands (also known as the Marshall Islands) is a nation of more than 30 low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone over 770,000 square miles in the tropical central north Pacific Ocean. Monitoring environmental conditions for potential drought risk is challenging in such a dispersed island nation, and current
Authors
Gabriel B. Senay, David A. Helweg, Stefanie Kagone, John B. Taylor, Thomas Cecere, Tiare Eastmond, Amy Koch, Kurtis Nelson, Lajikit Rufus
Changes to Monitoring Trends in Burn Severity Program’s production procedures and data products
The Monitoring Trends in Burn Severity (MTBS) program has been providing the fire science community with large fire perimeter and burn severity data for the past 14 years. As of October 2019, 22 969 fires have been mapped by the MTBS program and are available on the MTBS website (https://www.mtbs.gov). These data have been widely used by researchers to examine a variety of fire and climate science
Authors
Joshua J. Picotte, Krishna P. Bhattarai, Daniel Howard, Jennifer Lecker, Justin Epting, Brad Quayle, Nate Benson, Kurtis Nelson
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
An optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data
Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any dataset and identify an appropriate number of rules in the regression tree model that will improve
Authors
Yingxin Gu, Bruce K. Wylie, Stephen P. Boyte, Joshua J. Picotte, Danny Howard, Kelcy Smith, 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
LANDFIRE 2010—Updates to the national dataset to support improved fire and natural resource management
The Landscape Fire and Resource Management Planning Tools (LANDFIRE) 2010 data release provides updated and enhanced vegetation, fuel, and fire regime layers consistently across the United States. The data represent landscape conditions from approximately 2010 and are the latest release in a series of planned updates to maintain currency of LANDFIRE data products. Enhancements to the data products
Authors
Kurtis J. Nelson, Donald G. Long, Joel A. Connot
A comparison of NLCD 2011 and LANDFIRE EVT 2010: Regional and national summaries.
In order to provide the land cover user community a summary of the similarity and differences between the 2011 National Land Cover Dataset (NLCD) and the Landscape Fire and Resource Management Planning Tools Program Existing Vegetation 2010 Data (LANDFIRE EVT), the two datasets were compared at a national (conterminous U.S.) and regional (Eastern, Midwestern, and Western) extents (Figure 1). The c
Authors
Alexa McKerrow, Jon Dewitz, Donald G. Long, Kurtis Nelson, Joel A. Connot, Jim Smith
A landsat data tiling and compositing approach optimized for change detection in the conterminous United States
Annual disturbance maps are produced by the LANDFIRE program across the conterminous United States (CONUS). Existing LANDFIRE disturbance data from 1999 to 2010 are available and current efforts will produce disturbance data through 2012. A tiling and compositing approach was developed to produce bi-annual images optimized for change detection. A tiled grid of 10,000 × 10,000 30 m pixels was defin
Authors
Kurtis Nelson, Daniel R. Steinwand
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
LANDFIRE 2010 - updated data to support wildfire and ecological management
Wildfire is a global phenomenon that affects human populations and ecosystems. Wildfire effects occur at local to global scales impacting many people in different ways (Figure 1). Ecological concerns due to land use, fragmentation, and climate change impact natural resource use, allocation, and conservation. Access to consistent and current environmental data is a constant challenge, yet necessary
Authors
Kurtis J. Nelson, Joel A. Connot, Birgit E. Peterson, Joshua J. Picotte
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
Fire Atlas
EROS work on fire activity in the United States includes the creation of an atlas of fire perimeters for fires occurring on U.S. National Wildlife Refuges from 1984 through 2013. Fire Atlas perimeter data provide information to refuge managers as they plan land management activities for their units. EROS analysts use data provided by the U.S. Fish and Wildlife Service (FWS), which include a name...
Fire Danger Forecast
USGS Earth Resources Observation and Science (EROS), in conjunction with the US Forest Service Pacific Southwest (PSW) Region, has developed several new products for understanding and forecasting the probability of large wildland fires on all land in the conterminous U.S.
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
Vegetation and Water Monitoring Datasets for selected locations in the Republic of the Marshall Islands from 2017-2022
The Republic of the Marshall Islands (RMI) is a sovereign Small Island State in the tropical central North Pacific Ocean. RMI is a nation of more than thirty atolls and islands, most of which are inhabited, dispersed across an exclusive economic zone (EEZ) over 2 million square kilometers. This data release contains raster datasets for vegetation and water monitoring including Normalized Differenc
Monthly Satellite-Estimated Precipitation Reports for the Republic of the Marshall Islands
The Republic of the Marshall Islands (RMI) is a nation of more than thirty low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone (EEZ) over 770,000 square miles in the tropical central North Pacific Ocean. Monitoring environmental conditions for potential drought risk is challenging in such a dispersed Island nation, and current drought hazard produ
Satellite precipitation estimates for selected locations in the Republic of the Marshall Islands
The Republic of the Marshall Islands (RMI) is a sovereign Small Island State in the tropical central North Pacific Ocean. RMI is a nation of more than thirty atolls and islands, most of which are inhabited, dispersed across an exclusive economic zone (EEZ) over 2 million square kilometers. This data release contains files of daily precipitation estimates beginning in 2001 for 23 inhabited sites in
Burn Severity Portal, a clearing house of fire severity and extent information (ver. 8.0, August 2024)
The various post-fire data products available on the Burn Severity Portal are produced using satellite imagery. The timing of the satellite imagery used, relative to the fire event, typically depends on the vegetation type and structure where the fire occurred. Each mapping program produces a suite of data products based on user intended user needs. You can find additional details in each of the a
Monitoring Trends in Burn Severity (ver. 9.0, August 2024)
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in th
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
Monitoring Trends in Burn Severity Thematic Burn Severity Mosaic (ver. 9.0, August 2024)
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S
Filter Total Items: 16
Developing version 2 of satellite-estimated precipitation monthly reports for selected locations in the Republic of the Marshall Islands
The Republic of the Marshall Islands (RMI; also known as the Marshall Islands) is a nation of more than 30 low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone over 770,000 square miles in the tropical central north Pacific Ocean. The study objectives and methods were originally presented in U.S. Geological Survey Data Report 1181 and are summarize
Authors
Gabriel B. Senay, David A. Helweg, Stefanie Kagone, Thomas Cecere, Tiare Eastmond, Amy Koch, Kurtis Nelson, Jack Randon
Developing satellite-estimated precipitation monthly reports for selected locations in the Republic of the Marshall Islands
The Republic of the Marshall Islands (also known as the Marshall Islands) is a nation of more than 30 low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone over 770,000 square miles in the tropical central north Pacific Ocean. Monitoring environmental conditions for potential drought risk is challenging in such a dispersed island nation, and current
Authors
Gabriel B. Senay, David A. Helweg, Stefanie Kagone, John B. Taylor, Thomas Cecere, Tiare Eastmond, Amy Koch, Kurtis Nelson, Lajikit Rufus
Changes to Monitoring Trends in Burn Severity Program’s production procedures and data products
The Monitoring Trends in Burn Severity (MTBS) program has been providing the fire science community with large fire perimeter and burn severity data for the past 14 years. As of October 2019, 22 969 fires have been mapped by the MTBS program and are available on the MTBS website (https://www.mtbs.gov). These data have been widely used by researchers to examine a variety of fire and climate science
Authors
Joshua J. Picotte, Krishna P. Bhattarai, Daniel Howard, Jennifer Lecker, Justin Epting, Brad Quayle, Nate Benson, Kurtis Nelson
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
An optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data
Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any dataset and identify an appropriate number of rules in the regression tree model that will improve
Authors
Yingxin Gu, Bruce K. Wylie, Stephen P. Boyte, Joshua J. Picotte, Danny Howard, Kelcy Smith, 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
LANDFIRE 2010—Updates to the national dataset to support improved fire and natural resource management
The Landscape Fire and Resource Management Planning Tools (LANDFIRE) 2010 data release provides updated and enhanced vegetation, fuel, and fire regime layers consistently across the United States. The data represent landscape conditions from approximately 2010 and are the latest release in a series of planned updates to maintain currency of LANDFIRE data products. Enhancements to the data products
Authors
Kurtis J. Nelson, Donald G. Long, Joel A. Connot
A comparison of NLCD 2011 and LANDFIRE EVT 2010: Regional and national summaries.
In order to provide the land cover user community a summary of the similarity and differences between the 2011 National Land Cover Dataset (NLCD) and the Landscape Fire and Resource Management Planning Tools Program Existing Vegetation 2010 Data (LANDFIRE EVT), the two datasets were compared at a national (conterminous U.S.) and regional (Eastern, Midwestern, and Western) extents (Figure 1). The c
Authors
Alexa McKerrow, Jon Dewitz, Donald G. Long, Kurtis Nelson, Joel A. Connot, Jim Smith
A landsat data tiling and compositing approach optimized for change detection in the conterminous United States
Annual disturbance maps are produced by the LANDFIRE program across the conterminous United States (CONUS). Existing LANDFIRE disturbance data from 1999 to 2010 are available and current efforts will produce disturbance data through 2012. A tiling and compositing approach was developed to produce bi-annual images optimized for change detection. A tiled grid of 10,000 × 10,000 30 m pixels was defin
Authors
Kurtis Nelson, Daniel R. Steinwand
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
LANDFIRE 2010 - updated data to support wildfire and ecological management
Wildfire is a global phenomenon that affects human populations and ecosystems. Wildfire effects occur at local to global scales impacting many people in different ways (Figure 1). Ecological concerns due to land use, fragmentation, and climate change impact natural resource use, allocation, and conservation. Access to consistent and current environmental data is a constant challenge, yet necessary
Authors
Kurtis J. Nelson, Joel A. Connot, Birgit E. Peterson, Joshua J. Picotte