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Landsat Burned Area Products Data Release - combined sensor products 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. Scene-level products include pixel-level burn probability (BP) and burn classification (BC) images, corresponding to each Landsat image in the ARD time series. Annual composite products are also available by summarizing the scene level products. Prior to generating annual composites, individual scenes that had > 0.010... Categories: Data; Tags: Burned area, Landsat, Prescribed fire, United States, Wildfire, All tags... Wildland fire, Fewer tags Gridded 20km Daily Reference Evapotranspiration for the State of Alaska from 1979 to 2017 Reference evapotranspiration (ET0), like potential evapotranspiration, is a measure of atmospheric evaporative demand. It was used in the context of this study to evaluate drought conditions that can lead to wildfire activity in Alaska using the Evaporative Demand Drought Index (EDDI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The ET0 data are on a 20km grid with daily temporal resolution and were computed using the meteorological inputs from the dynamically downscaled ERA-Interim reanalysis and two global climate model projections (CCSM4 and GFDL-CM3). The model projections are from CMIP5 and use the RCP8.5 scenario. The dynamically downscaled data are available at https://registry.opendata.aws/wrf-alaska-snap/.... Categories: Data; Types: NetCDF OPeNDAP Service; Tags: Alaska, climatologyMeteorologyAtmosphere, dataset, drought, reference evapotranspiration, All tags... service, wildfire, Fewer tags Change from Historical in Number of Days with High Fire Risk (Energy Release Component > 95th percentile), RCP8.5, 2050s The Energy Release Component (ERC) is a calculated output of the National Fire Danger Rating System (NFDRS). The ERC is a number related to the available energy (BTU) per unit area (square foot) within the flaming front at the head of a fire. The ERC is considered a composite fuel moisture index as it reflects the contribution of all live and dead fuels to potential fire intensity. As live fuels cure and dead fuels dry, the ERC will increase and can be described as a build-up index. The ERC has memory. Each daily calculation considers the past 7 days in calculating the new number. Daily variations of the ERC are relatively small as wind is not part of the calculation. The ERC is projected to the 2050s using three... Categories: Data, Map; Types: Downloadable, Map Service, Raster; Tags: Data Visualization & Tools, Idaho, Landscapes, Map Layer Package, NFRDS, All tags... Northwest CASC, Other Landscapes, Science Tools For Managers, Washington, fire, fuel moisture, humidity, weather data, wildfire, Fewer tags Conditional Flame Length predicted for 2080 to 2100 for Rio Grande study area Conditional Flame Length (CFL) is an estimate of the mean flame lengths for each pixel, and was predicted for the 2080-2100 period in the Rio Grande area using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway. CFL... Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: conditional flame length, fire, future climate, gis, rio grande, All tags... wildfire, Fewer tags Fire Intensity predicted for 2080 to 2100 for Rio Grande study area Fire Intensity raster dataset predicted for the 2080-2100 period in the Rio Grande area was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway. Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: fire, fire intensity, future climate, gis, rio grande, All tags... wildfire, Fewer tags The Wildfire Hazard and Risk Assessment Inventory The Department of the Interior (DOI) Office of Wildland Fire and USGS created the The Wildfire Hazard and Risk Assessment Inventory to meet the Monitoring, Maintenance, and Treatment Plan requirements under the Bipartisan Infrastructure Law (BIL). It provides an inventory of key national, regional, and state wildfire risk and fire hazard assessments useful for understanding different characterizations of fire risk. Some of the assessments may be useful for communicating contributions toward risk reduction of treatments funded by DOI, including investments under BIL. For each assessment, the inventory provides a description and information about the spatial extent, resolution, fire modeling approach, values considered... Categories: Data; Tags: Climatology, Ecology, Forestry, Geography, Information Sciences, All tags... Land Use Change, USGS Science Data Catalog (SDC), Water Quality, Water Resources, Wildlife Biology, biota, risk and hazard assessment, wildfire, wildland fire, Fewer tags Post-wildfire debris-flow monitoring data, 2014 Silverado Fire, Orange County, California, November 2014 to January 2016 This data release includes time-series data from two monitoring stations in a small drainage basin burned in the 2014 Silverado Fire, Orange County, California. One station (upper station) is located in the headwaters of the study area (33 45’39.10”N, 117 35’17.48”W, WGS84). The other station (lower station) is located at the outlet of the study area (33 45’04.61”N, 117 35’12.54”W). The data were collected between November 15, 2014 and January 14, 2016. The data include continuous 1-minute time series of rainfall and soil water content recorded at the both stations and intermittent (during rain storms) 50-Hz time series of flow-induced ground vibrations recorded by geophones at the lower station. The soil water... Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: GHSC, Geologic Hazards Science Center, Landslides Hazards Program, Orange County, California, USGS, All tags... USGS Science Data Catalog (SDC), debris flow, drainage basin, earth science, fire, geophysics, heterogeneous infiltration capacity, infiltration capacity, landslide, landslide hazard, rainfall, seismology, soil water content, wildfire, Fewer tags Tadpole Fire Field Measurements following the 8 September 2020 Debris Flow, Gila National Forest, NM This data release contains data summarizing observations within and adjacent to the Tadpole Fire, which burned from 6 June to 4 July 2020 in the Gila National Forest, NM. This monitoring data were focused on debris flows triggered on 8 September 2020 in four drainage basins (TAD1, TAD2, TAD3, and TAD4). Rainfall data (1a_rain_geophones.csv) are provided in a comma-separated value (CSV) file. The columns in the csv file are: Index, GaugeID (name of rain gauge), StormID (the storm number starting at the first record, where a new storm is defined by 8 hours with no rainfall), TimeStamp (local time), Bin Accum (mm) (The total accumulated rainfall between timesteps in units of millimeters), TotalAccum (mm) (the cumulative... Categories: Data; Tags: Debris Flow, Geomorphology, Geomorphology, Hydrology, Hydrology, All tags... Tadpole Ridge, USGS Science Data Catalog (SDC), Wildfire, Fewer tags van Genuchten parameters near Hess Creek in interior Alaska This data release presents measurements and derived parameters for attributes of bulk density, loss on ignition, soil-water retention, and hydraulic conductivity for a site (Richardson) near Hess Creek in interior Alaska, USA. These measurements are useful for hydrologic modeling and predictions of water availability in this region. Categories: Data; Tags: Alaska, Dalton Highway, Hess Creek, hydraulic properties, interior Alaska, All tags... soil properties, wildfire, Fewer tags Data release for: Spatially explicit reconstruction of post-megafire forest recovery through landscape modeling This data release provides inputs needed to run the LANDIS PRO forest landscape model and the LINKAGES 3.0 ecosystem process model for the area burned by the Black Dragon Fire in northeast China in 1987, and simulation results that underlie figures and analysis in the accompanying publication. The data release includes the fire perimeter of Great Dragon Fire; input data for LINKAGES including soils, landtype, and climate data; initial conditions of stands in the study area before the Great Dragon Fire; and maps of LANDIS PRO output for each model grid cell including total trees, total biomass (Mg/ha), and tree density (trees/ha) in two-year timesteps. Categories: Data; Tags: China, Ecology, Forestry, Great Xing 'an Mountains, LANDIS PRO, All tags... Landsat, Landscape change model, Remote Sensing, USGS Science Data Catalog (SDC), Vegetation imputation, Wildfire, aboveground forest biomass, forest ecosystems, Fewer tags Water Quality of the Russian River Watershed After Sonoma and Napa County Fires, Beginning 2017 Note: This data release has been superseded by https://doi.org/10.5066/P9ZBZMFL. The Sonoma County Water Agency (SCWA) supplies drinking water to over 600,000 Sonoma County and Marin County, CA residents and relies on a combination of Russian River water and surrounding groundwater. SCWA employs natural removal processes of riverbank filtration (RBF) to provide pretreatment before the river water is chlorinated and distributed in the drinking water system. In addition, SCWA employs an inflatable damn on a seasonal basis to increase water supply at the RBF site. Changes in water quality due to recent and potential future fires within the Russian River water shed could lead to substantial drinking water management... Categories: Data; Tags: Aquatic Biology, Environmental Health, Water Quality, contaminants, surface water, All tags... water quality, wildfire, 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 Quantifying vulnerability of quaking aspen woodlands and associate bird communities to global climate change in the northern Great Basin FY2011Aspen populations are in decline across western North America due to altered fire regimes, herbivory, drought, pathogens, and competition with conifers. Aspen stands typically support higher avian biodiversity than surrounding habitats, and maintaining current distributions of several avian species is likely tied to persistence of aspen on the landscape. We are examining effects of climate change on aspen and associated avian communities in isolated mountain ranges of the northern Great Basin, by coupling empirical models of avian-habitat relationships with spatially-explicit landscape simulations of vegetation and disturbance dynamics (using LANDIS-II) under various climate change scenarios. We are addressing... Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Academics & scientific researchers, Data Acquisition and Development, Federal resource managers, LANDIS-II, LANDIS-II, All tags... LANDIS-II, LCC Network Science Catalog, Monitoring, Nevada, Nevada, Nevada, Population & Habitat Evaluation/Projection, Project, State agencies, aspen, avian, avian, avian, biodiversity, biodiversity, biodiversity, birds, birds, birds, climate change, climate change, climate change, completed, empirical models, empirical models, empirical models, fire, fire, fire, northern great basin, populus tremuloides, populus tremuloides, populus tremuloides, wildfire, wildfire, wildfire, Fewer tags Burn Probability for Fireline Intensity Class 3, predicted for 2020 to 2040 for Rio Grande study area Burn probability (BP) for Fireline Intensity Class 3 (FIL3) with flame lengths in the range of 1.2-1.8 m predicted for the 2020-2040 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the... Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: burn probability, fire, fireline intensity, future climate, gis, All tags... rio grande, wildfire, Fewer tags Burn Probability for Fireline Intensity Class 5, predicted for 2020 to 2040 for Rio Grande study area Burn probability (BP) for Fireline Intensity Class 5 (FIL5) with flame lengths in the range of 2.4-3.7 m predicted for the 2020-2040 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the... Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: burn probability, fire, fireline intensity, future climate, gis, All tags... rio grande, wildfire, Fewer tags Debris Flow, Precipitation, and Volume Measurements in the Grizzly Creek Burn Perimeter June 2021-September 2022, Glenwood Canyon, Colorado (ver. 1.1, October 2023) This data release contains data summarizing observations within and adjacent to the Grizzly Creek Fire, which burned from 10 August to 18 December 2020. This monitoring data summarizes precipitation, observations of debris flows, and the volume of sediment eroded during debris flows triggered during the summer monsoonal period in 2021 and 2022. Summary rainfall data 2021 (1a_Storm_matrix_2021_gr1mmhr.csv) are provided in a comma-separated value (CSV) file. These data represent the maximum measured rainfall intensities during the monsoon months of 2021 (June-Sept). The columns in the csv file are: Date (m/dd/yy), Name (11 columns have unique gage names), Max 15 min (the maximum 15-minute rainfall intensity in mm/h... Categories: Data; Tags: Colorado, Garfield County, Geomorphology, Glenwood Canyon, Hydrology, All tags... Hydrology, Sediment, USGS Science Data Catalog (SDC), Wildfire, biota, Fewer tags Supporting data for "Evaluating the Factors Responsible for Post-Fire Water Quality Response in Forests of the Western USA" Spatially-referenced data used in the study "Rust, A.J., Saxe, S., McCray, J., Rhoades, C.C., Hogue, T.S., 2019. Evaluating the factors responsible for post-fire water quality response in forests of the western USA. Int. J. Wildland Fire.": Wildfires commonly increase nutrient, carbon, sediment, and metal inputs to streams yet the factors responsible for the type, magnitude and duration of water quality effects are poorly understood. Prior work by the current authors found increased nitrogen, phosphorus and cation exports were common the first 5 post-fire years from a synthesis of 159 wildfires across the western United States. In the current study, an analysis is undertaken to determine factors that best explain... Categories: Data; Tags: CONUS, Continental United States, Environmental Health, Hydrogeology, Land Use Change, All tags... USGS Science Data Catalog (SDC), United States, Water Quality, Water Resources, fire, runoff, streamflow, water, water quality, wildfire, 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 « 1 2 3 4 5 6 »