Filters: Tags: Wildfire (X)
584 results (91ms)|
Filters
Date Range
Extensions (Less)
Types (Less)
Contacts (Less)
Categories (Less)
Tag Types
|
The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a thematic raster...
The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a thematic raster...
The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a thematic raster...
In California, increased wildfire activity has been linked to decreasing snowpack and earlier snowmelt. Not only has this translated into a longer fire season, but reduced snowpack has cascading effects that impact streamflow, water supplies, agricultural productivity, and ecosystems. California receives 80% of its precipitation during the winter, so mountain snowpack plays a critical role in replenishing the state’s water supply. One factor that affects the amount of winter precipitation (and therefore snowpack) in California is the North Pacific Jet (NPJ)—a current of strong, high altitude winds that occur over the northern Pacific Ocean. Winters when the NPJ is located further north than normal are drier than...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Report;
Tags: 2013,
CA,
CA-wide,
CASC,
Completed,
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...
This data release contains gridded estimates of postfire debris flow probability and magnitude for six different rainfall and wildfire scenarios in southern California. The scenarios represent the present and possible future precipitation and fire regimes for the region. The results are provided for 1 km2 cells across the study area. The data release accompanies the journal article Kean, J.W. and Staley, D.M. (2021). Forecasting the frequency and magnitude of postfire debris flow across southern California, Earth's Future, 2020EF001735.
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,
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...
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.
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.
The Monitoring Trends in Burn Severity (MTBS) project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2010. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This...
Types: Downloadable;
Tags: BLM,
Bureau of Land Management,
Burned Area Extent,
CBR 2010,
Central Basin and Range,
This dataset is a raster of predicted suitable bioclimate using statistical correlations between known habitat and current climate (1950-1999 average) , and then projecting that niche into the future. The future timeslices used are 2020's, which is an average of 2020-2029, and 2050's which is 2050-2059. The Values 1-6 show the degree of model agreement (For example: areas with a value of 1 is where only 1 GCM predicted suitability; pixels with a value of 6 are where 6 GCMs predicted suitability, ect). *see Maxent output pdfs for more details about model inputs and settings.
GeoMAC (Geospatial Multi-Agency Coordination) interactive map viewer. The Geospatial Multi-Agency Coordination or GeoMAC, is an internet-based mapping application originally designed for fire managers to access online maps of current fire locations and perimeters in the United States. Using a standard web browser, fire personnel can view this information to pinpoint the affected areas. With the growing concern of western wildland fires in the summer of 2000, this application also became available to the public.
The Monitoring Trends in Burn Severity (MTBS) project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2010. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This...
This dataset is a raster of predicted suitable bioclimate using statistical correlations between known habitat and current climate (1950-1999 average) , and then projecting that niche into the future. The future timeslices used are 2020's, which is an average of 2020-2029, and 2050's which is 2050-2059. The Values 1-6 show the degree of model agreement (For example: areas with a value of 1 is where only 1 GCM predicted suitability; pixels with a value of 6 are where 6 GCMs predicted suitability, ect). *see Maxent output pdfs for more details about model inputs and settings.
This presentation addressed issues confronting preservation and restoration of big sagebrush, focusing on climate, wildfire, and invasives. Preliminary and published insights on climate responses of sagebrush and implications for vulnerability assessments and post-fire restoration were described. Responses of big sagebrush and competitors such as cheatgrass to climate manipulations are providing important insight on the ways in which sagebrush may resist or respond to warming or shifts in precipitation. Big sagebrush is a remarkably diverse species, and preliminary findings from common-garden studies are suggesting how the diversity is important for its climate responses and for selection of appropriate seed sources....
Categories: Publication;
Types: Citation;
Tags: Grasslands and Plains,
Landscapes,
Northwest CASC,
climate,
invasives,
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,
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,
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,
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,
|
|
