Filters: Tags: Wildfire (X) > partyWithName: U.S. Geological Survey - ScienceBase (X) > Types: Downloadable (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Extensions Raster (9) ArcGIS Service Definition (4) Shapefile (1) Types Map Service (14) GeoTIFF (9) Raster (9) ArcGIS REST Map Service (4) ArcGIS Service Definition (4) More... Contacts Michael C Stambaugh U.S. Geological Survey CERC Data Managers FRESC Science Data Coordinator Justin L Welty More... Categories Data (14) Tag Types Theme (14) Place (14) USGS Scientific Topic Keyword (2) Harvest Set (2) Tag Schemes None (14) Common geographic areas (12) USGS Thesaurus (14) ISO 19115 Topic Category (5) View Results as: JSON ATOM CSV

Combined wildland fire datasets for the United States and certain territories, 1800s-Present (summary rasters) First, we would like to thank the wildland fire advisory group. Their wisdom and guidance helped us build the dataset as it currently exists. Currently, there are multiple, freely available wildland fire datasets that identify wildfire and prescribed fire areas across the United States. However, these datasets are all limited in some way. Time periods, spatial extents, attributes, and maintenance for these datasets are highly variable, and none of the existing datasets provide a comprehensive picture of wildfires that have burned since the 1800s. Utilizing a series of both manual processes and ArcGIS Python (arcpy) scripts, we merged 40 of these disparate datasets into a single dataset that encompasses the known... Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: Fire, North America, Prescribed Burn, Prescribed Fire, Raster, All tags... United States, United States, Wildfire, Wildland Fire, burned area, environment, fire, fires, first year burned, geospatial datasets, most recent year burned, number of times burned, prescribed fire, raster, wildfire, Fewer tags Fire probability for 1900-1929 using GFDL baseline climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Combined wildfire datasets for the United States and certain territories, 1878-2019 ***This data set is superseded by Welty, J.L., and Jeffries, M.I., 2021, Combined wildland fire datasets for the United States and certain territories, 1800s-Present: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZXGFY3.*** This dataset is comprised of four different zip files. Zip File 1: A combined wildfire polygon dataset ranging in years from 1878-2019 (142 years) that was created by merging and dissolving fire information from 12 different original wildfire datasets to create one of the most comprehensive wildfire datasets available. Attributes describing fires that were reported in the various source data, including fire name, fire code, ignition date, controlled date, containment date, and... Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: Botany, Ecology, Forestry, Land Use Change, North America, All tags... USGS Science Data Catalog (SDC), United States, biota, burned area, count of times burned, environment, fire, fires, first year burned, geospatial datasets, most recent year burned, wildfire, Fewer tags Combined wildland fire datasets for the United States and certain territories, 1800s-Present (combined wildland fire polygons) First, we would like to thank the wildland fire advisory group. Their wisdom and guidance helped us build the dataset as it currently exists. Currently, there are multiple, freely available fire datasets that identify wildfire and prescribed fire burned areas across the United States. However, these datasets are all limited in some way. Their time periods could cover only a couple of decades or they may have stopped collecting data many years ago. Their spatial footprints may be limited to a specific geographic area or agency. Their attribute data may be limited to nothing more than a polygon and a year. None of the existing datasets provides a comprehensive picture of fires that have burned throughout the last... Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: Fire, North America, Prescribed Burn, Prescribed Fire, United States, All tags... United States, Wildfire, Wildland Fire, biota, burned area, environment, fire, fires, geospatial datasets, polygon, prescribed fire, wildfire, Fewer tags Fire probability for 1900-1929 using CGCM baseline climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags State Transition Model of Cumulative Burned Area to Annual Grass in the Great Basin Region of the Western U.S. A raster identifying previously burned areas as being 1) recovered (to sagebrush-dominant ecosystem), 2) recovering, or 3) transitioned to annual grass-dominated. Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: Annual grass, California, Great Basin, Idaho, Montana, All tags... Nevada, Oregon, Recovery, Resilience, Resistance, Sagebrush, Utah, Western United States, Wildfire, biota, fires, Fewer tags Change in fire probability from baseline to 2040-2069 using CGCM-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2040-2069 using HadCM3-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2040-2069 using GFDL-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2070-2099 using CGCM-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2070-2099 using GFDL-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2070-2099 using HadCM3-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags The Effect of Prolonged Drought on Chaparral Dieback within the Perimeters of the Thomas and Woolsey Fires in Southern California, USA This dataset contains data pertaining to chaparral vegetation dieback based on the difference or change in the Normalized Difference Vegetation Index (NDVI) prior to and 6 years into an extensive drought before the 2017 Thomas and 2018 Woolsey Fires in southern California. The difference in mean NDVI is provided for 9322 study plots as are values for a number of physical and climatological variables and burn severity following the two fires. These data support the following publication: Keeley, J.E., Brennan-Kane, T.J., and Syphard, A.D., 2022. The effects of prolonged drought on vegetation dieback and megafires in southern California chaparral. Ecosphere, 13(8), e4203. https://doi.org/10.1002/ecs2.4203. Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Chaparral, Climatology, Ecology, Environmental Health, Remote Sensing, All tags... Southern California, Thomas Fire, USGS Science Data Catalog (SDC), Wildfire, Woolsey Fire, biota, droughts, environment, fires, imageryBaseMapsEarthCover, vegetation, Fewer tags Fire probability for 1900-1929 using HadCM3 baseline climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags