Josh Takacs
Josh Takacs is a Information Technology Specialist with the Geosciences and Environmental Change Science Center
Science and Products
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
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
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
Mapping burned areas using dense time-series of Landsat data
Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, in many areas existing fire occurrence datasets are known to be incomplete. Consequently, the need to systematically collect burned area information has been re
Authors
Todd Hawbaker, Melanie K. Vanderhoof, Yen-Ju G. Beal, Joshua Takacs, Gail L. Schmidt, Jeff T. Falgout, Brad Williams, Nicole M. Brunner, Megan K. Caldwell, Joshua J. Picotte, Stephen M. Howard, Susan Stitt, John L. Dwyer
Science and Products
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
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
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
Mapping burned areas using dense time-series of Landsat data
Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, in many areas existing fire occurrence datasets are known to be incomplete. Consequently, the need to systematically collect burned area information has been re
Authors
Todd Hawbaker, Melanie K. Vanderhoof, Yen-Ju G. Beal, Joshua Takacs, Gail L. Schmidt, Jeff T. Falgout, Brad Williams, Nicole M. Brunner, Megan K. Caldwell, Joshua J. Picotte, Stephen M. Howard, Susan Stitt, John L. Dwyer