Joshua Picotte, PhD
Joshua Picotte is a Biologist focusing on fire science at the Earth Resources Observation and Science Center in Sioux Falls, SD.
Joshua Picotte has worked at USGS EROS for 11 years, with his first 10 years as a contractor. Throughout his career at USGS he has worked on fire science projects, including the Monitoring Trends in Burn Severity (MTBS) and LANDFIRE projects.
Professional Experience
2022-present: Biologist; USGS
2011-2022: Fire Specialist; Contractor to the USGS
Education and Certifications
BS Environmental Science and Botany/Plant Pathology; Lyman Briggs College/Michigan State University; East Lansing, MI
MS Biology; Portland State University; Portland, OR
PhD ; University of Idaho; Natural Resources; Moscow, ID
Science and Products
The Landsat Collection 2 Burned Area Products for the conterminous United States (ver. 2.0, April 2024)
The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions.
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
Wetland burned area extent derived from Sentinel-2 across the southeastern U.S. (2016-2019)
Wildfires and prescribed fires are frequent but under-mapped across wetlands of the southeastern United States . High annual precipitation supports rapid post-fire recovery of wetland vegetation, while associated cloud cover limits clear-sky observations. In addition, the low burn severity of prescribed fires and spectral confusion between fluctuating water levels and burned areas have resulted in
The Landsat Burned Area products for the conterminous United States (ver. 3.0, March 2022)
The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions.
Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 -2015)
The U.S. Geological Survey (USGS) has developed and implemented an automated algorithm that identifies burned areas in temporally-dense time series of Landsat image stacks to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and
Filter Total Items: 21
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
A multimodal data fusion and deep learning framework for large-scale wildfire surface fuel mapping
Accurate estimation of fuels is essential for wildland fire simulations as well as decision-making related to land management. Numerous research efforts have leveraged remote sensing and machine learning for classifying land cover and mapping forest vegetation species. In most cases that focused on surface fuel mapping, the spatial scale of interest was smaller than a few hundred square kilometers
Authors
Mohamad Alipour, Inga P. La Puma, Joshua J. Picotte, Kasra Shamsei, Eric Rowell, Adam Watts, Branko Kosovic, Hamed Ebrahimian, Erugrul Taciroglu
Mapping wetland burned area from Sentinel-2 across the southeastern United States and its contributions relative to Landsat 8 (2016-2019)
Prescribed fires and wildfires are common in wetland ecosystems across the Southeastern United States. However, the wetland burned area has been chronically underestimated across the region due to (1) spectral confusion between open water and burned area, (2) rapid post-fire vegetation regrowth, and (3) high annual precipitation limiting clear-sky satellite observations. We developed a machine lea
Authors
Melanie K. Vanderhoof, Todd Hawbaker, Casey Teske, Andrea Ku, Joe Noble, Joshua J. Picotte
Determination of burn severity models ranging from regional to continental scales for the conterminous United States
Identifying meaningful measures of ecological change over large areas is dependent on the quantification of robust relationships between ecological metrics and remote sensing products. Over the past several decades, ground observations of wildfire and prescribed fire severity have been acquired across hundreds of wildland fires in the United States, primarily utilizing the Composite Burn Index (CB
Authors
Joshua J. Picotte, C. Alina Cansler, Crystal A. Kolden, James A. Lutz, Carl Key, Nathan Benson, Kevin Robertson
New operational national satellite burned area product
Introduction
Lack of consistent spatial and temporal fire information with relevant spatial resolution hinders land management and broad-scale assessments of fire activity, especially in the eastern United States and the Great Plains where fi re is important ecologically and culturally. Remote sensing can be used to monitor fi re activity, augment existing fi re data, and fill information gaps. In
Authors
Todd Hawbaker, Melanie K. Vanderhoof, Gail L. Schmidt, Yen-Ju G. Beal, Joshua J. Picotte, Joshua Takacs, Jeff T. Falgout, John L. Dwyer
Development of a new open-source tool to map burned area and burn severity
Accurate and complete geospatial fire occurrence records are important in determining postfire effects, emissions, hazards, and fuel loading inventories. Currently, the Monitoring Trends in Burn Severity (MTBS) project maps the fire perimeter and burn severity of all large fires on public lands. Although the MTBS project maps a large proportion of the fire acreage, it maps a smaller proportion of
Authors
Joshua J. Picotte
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
The Landsat Burned Area algorithm and products for the conterminous United States
Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Essential Climate Variable (BAECV) algorithm. Here, we present the BA algorithm and products, changes re
Authors
Todd Hawbaker, Melanie K. Vanderhoof, Gail L. Schmidt, Yen-Ju G. Beal, Joshua J. Picotte, Joshua Takacs, Jeff T. Falgout, John L. Dwyer
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
Geospatial data mining for digital raster mapping
We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural n
Authors
Bruce K. Wylie, Neal J. Pastick, Joshua J. Picotte, Carol Deering
Non-USGS Publications**
Xu, Q., Westerling, A.L., Notohamiprodjo, A., Wiedinmyer, C., Picotte, J.J., Parks, S.A., Hurteau, M.D., Marlier, M.E., Kolden, C.A., Sam, J.A., and Baldwin, W.J., 2022. Wildfire burn severity and emissions inventory: an example implementation over California. Environmental Research Letters, 17(8), p.085008.
Picotte, J.J. and K.M. Robertson 2011. Validation of burn severity within southeastern U.S. ecosystems. International Journal of Wildland Fire. International Journal of Wildland Fire 20:453-464.
Picotte, J.J. and K.M. Robertson. 2010. Remote sensing of wildland fire burned area in southeastern U.S. coastal plain habitats. Pages 86-93 in K.M. Robertson, R.E. Masters and K.E.M Gallery (Eds.). Proceedings of the 24th Tall Timbers Fire Ecology Conference: The Future of Fire: Public Awareness, Health, and Safety. Tall Timbers Research Station, Tallahassee, FL, USA.
Picotte, J. J., and K. M. Robertson. 2010. Accuracy of remote sensing wildland fire-burned area in southeastern US Coastal plain habitats. Tall Timbers Fire Ecol. Proc, 24:86-93
Picotte, J.J., J.M. Rhode, and M.B. Cruzan. 2009. Leaf morphological
responses to variation in water availability for plants in the Piriqueta caroliniana complex. Plant Ecology. 200:267-275.
Picotte, J. J., D. M. Rosenthal, J. M. Rhode, and M. B. Cruzan. 2007. Plastic responses to temporal variation in moisture availability: consequences for water use efficiency and plant performance. Oecologia 153:821-832.
Picotte, J.J. and K.M. Robertson 2011. Validation of burn severity within southeastern U.S. ecosystems. International Journal of Wildland Fire. International Journal of Wildland Fire 20:453-464.
Picotte, J.J. and K.M. Robertson. 2010. Remote sensing of wildland fire burned area in southeastern U.S. coastal plain habitats. Pages 86-93 in K.M. Robertson, R.E. Masters and K.E.M Gallery (Eds.). Proceedings of the 24th Tall Timbers Fire Ecology Conference: The Future of Fire: Public Awareness, Health, and Safety. Tall Timbers Research Station, Tallahassee, FL, USA.
Picotte, J. J., and K. M. Robertson. 2010. Accuracy of remote sensing wildland fire-burned area in southeastern US Coastal plain habitats. Tall Timbers Fire Ecol. Proc, 24:86-93
Picotte, J.J., J.M. Rhode, and M.B. Cruzan. 2009. Leaf morphological
responses to variation in water availability for plants in the Piriqueta caroliniana complex. Plant Ecology. 200:267-275.
Picotte, J. J., D. M. Rosenthal, J. M. Rhode, and M. B. Cruzan. 2007. Plastic responses to temporal variation in moisture availability: consequences for water use efficiency and plant performance. Oecologia 153:821-832.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
The Landsat Collection 2 Burned Area Products for the conterminous United States (ver. 2.0, April 2024)
The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions.
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
Wetland burned area extent derived from Sentinel-2 across the southeastern U.S. (2016-2019)
Wildfires and prescribed fires are frequent but under-mapped across wetlands of the southeastern United States . High annual precipitation supports rapid post-fire recovery of wetland vegetation, while associated cloud cover limits clear-sky observations. In addition, the low burn severity of prescribed fires and spectral confusion between fluctuating water levels and burned areas have resulted in
The Landsat Burned Area products for the conterminous United States (ver. 3.0, March 2022)
The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions.
Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 -2015)
The U.S. Geological Survey (USGS) has developed and implemented an automated algorithm that identifies burned areas in temporally-dense time series of Landsat image stacks to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and
Filter Total Items: 21
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
A multimodal data fusion and deep learning framework for large-scale wildfire surface fuel mapping
Accurate estimation of fuels is essential for wildland fire simulations as well as decision-making related to land management. Numerous research efforts have leveraged remote sensing and machine learning for classifying land cover and mapping forest vegetation species. In most cases that focused on surface fuel mapping, the spatial scale of interest was smaller than a few hundred square kilometers
Authors
Mohamad Alipour, Inga P. La Puma, Joshua J. Picotte, Kasra Shamsei, Eric Rowell, Adam Watts, Branko Kosovic, Hamed Ebrahimian, Erugrul Taciroglu
Mapping wetland burned area from Sentinel-2 across the southeastern United States and its contributions relative to Landsat 8 (2016-2019)
Prescribed fires and wildfires are common in wetland ecosystems across the Southeastern United States. However, the wetland burned area has been chronically underestimated across the region due to (1) spectral confusion between open water and burned area, (2) rapid post-fire vegetation regrowth, and (3) high annual precipitation limiting clear-sky satellite observations. We developed a machine lea
Authors
Melanie K. Vanderhoof, Todd Hawbaker, Casey Teske, Andrea Ku, Joe Noble, Joshua J. Picotte
Determination of burn severity models ranging from regional to continental scales for the conterminous United States
Identifying meaningful measures of ecological change over large areas is dependent on the quantification of robust relationships between ecological metrics and remote sensing products. Over the past several decades, ground observations of wildfire and prescribed fire severity have been acquired across hundreds of wildland fires in the United States, primarily utilizing the Composite Burn Index (CB
Authors
Joshua J. Picotte, C. Alina Cansler, Crystal A. Kolden, James A. Lutz, Carl Key, Nathan Benson, Kevin Robertson
New operational national satellite burned area product
Introduction
Lack of consistent spatial and temporal fire information with relevant spatial resolution hinders land management and broad-scale assessments of fire activity, especially in the eastern United States and the Great Plains where fi re is important ecologically and culturally. Remote sensing can be used to monitor fi re activity, augment existing fi re data, and fill information gaps. In
Authors
Todd Hawbaker, Melanie K. Vanderhoof, Gail L. Schmidt, Yen-Ju G. Beal, Joshua J. Picotte, Joshua Takacs, Jeff T. Falgout, John L. Dwyer
Development of a new open-source tool to map burned area and burn severity
Accurate and complete geospatial fire occurrence records are important in determining postfire effects, emissions, hazards, and fuel loading inventories. Currently, the Monitoring Trends in Burn Severity (MTBS) project maps the fire perimeter and burn severity of all large fires on public lands. Although the MTBS project maps a large proportion of the fire acreage, it maps a smaller proportion of
Authors
Joshua J. Picotte
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
The Landsat Burned Area algorithm and products for the conterminous United States
Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Essential Climate Variable (BAECV) algorithm. Here, we present the BA algorithm and products, changes re
Authors
Todd Hawbaker, Melanie K. Vanderhoof, Gail L. Schmidt, Yen-Ju G. Beal, Joshua J. Picotte, Joshua Takacs, Jeff T. Falgout, John L. Dwyer
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
Geospatial data mining for digital raster mapping
We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural n
Authors
Bruce K. Wylie, Neal J. Pastick, Joshua J. Picotte, Carol Deering
Non-USGS Publications**
Xu, Q., Westerling, A.L., Notohamiprodjo, A., Wiedinmyer, C., Picotte, J.J., Parks, S.A., Hurteau, M.D., Marlier, M.E., Kolden, C.A., Sam, J.A., and Baldwin, W.J., 2022. Wildfire burn severity and emissions inventory: an example implementation over California. Environmental Research Letters, 17(8), p.085008.
Picotte, J.J. and K.M. Robertson 2011. Validation of burn severity within southeastern U.S. ecosystems. International Journal of Wildland Fire. International Journal of Wildland Fire 20:453-464.
Picotte, J.J. and K.M. Robertson. 2010. Remote sensing of wildland fire burned area in southeastern U.S. coastal plain habitats. Pages 86-93 in K.M. Robertson, R.E. Masters and K.E.M Gallery (Eds.). Proceedings of the 24th Tall Timbers Fire Ecology Conference: The Future of Fire: Public Awareness, Health, and Safety. Tall Timbers Research Station, Tallahassee, FL, USA.
Picotte, J. J., and K. M. Robertson. 2010. Accuracy of remote sensing wildland fire-burned area in southeastern US Coastal plain habitats. Tall Timbers Fire Ecol. Proc, 24:86-93
Picotte, J.J., J.M. Rhode, and M.B. Cruzan. 2009. Leaf morphological
responses to variation in water availability for plants in the Piriqueta caroliniana complex. Plant Ecology. 200:267-275.
Picotte, J. J., D. M. Rosenthal, J. M. Rhode, and M. B. Cruzan. 2007. Plastic responses to temporal variation in moisture availability: consequences for water use efficiency and plant performance. Oecologia 153:821-832.
Picotte, J.J. and K.M. Robertson 2011. Validation of burn severity within southeastern U.S. ecosystems. International Journal of Wildland Fire. International Journal of Wildland Fire 20:453-464.
Picotte, J.J. and K.M. Robertson. 2010. Remote sensing of wildland fire burned area in southeastern U.S. coastal plain habitats. Pages 86-93 in K.M. Robertson, R.E. Masters and K.E.M Gallery (Eds.). Proceedings of the 24th Tall Timbers Fire Ecology Conference: The Future of Fire: Public Awareness, Health, and Safety. Tall Timbers Research Station, Tallahassee, FL, USA.
Picotte, J. J., and K. M. Robertson. 2010. Accuracy of remote sensing wildland fire-burned area in southeastern US Coastal plain habitats. Tall Timbers Fire Ecol. Proc, 24:86-93
Picotte, J.J., J.M. Rhode, and M.B. Cruzan. 2009. Leaf morphological
responses to variation in water availability for plants in the Piriqueta caroliniana complex. Plant Ecology. 200:267-275.
Picotte, J. J., D. M. Rosenthal, J. M. Rhode, and M. B. Cruzan. 2007. Plastic responses to temporal variation in moisture availability: consequences for water use efficiency and plant performance. Oecologia 153:821-832.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.