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This imagery was collected and produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This imagery and associated metrics was produced using Landsat 5 and 7. This set of imagery and remote sensing metrics have the following file structure: 1. Each sub-folder in the Fires LC Map folder represents an individual fire. 2. Within the folder there are 8 raster tiffs. 1. XXX_post_refl.tif The at-sensor-reflectance of the postfire landsat scene, named with the PolyID unique identifier for the fire, stored in 8-bit i. Band 1 of the Tiff is Band 3 (Red) of Landsat ii. Band 2 of the Tiff is Band 4 (NIR) of Landsat iii. Band 3 of...
Solar radiation grids were produced for a set of large fires sampled from within the Great Northern Landscape Conservation Cooperative study area. This solar radiation grid was produced using the Area Solar Radiation tool in ArcGIS 10.1, using inputs of the associated 30m DEM.
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...
Soil moisture is a critical variable for understanding the impacts of drought on ecological, hydrological, and agricultural systems. Yet, key research gaps currently prevent existing soil moisture measurements from being used to assess drought conditions and mitigate drought impacts such as wildfire outbreaks, lost agricultural production, and degraded wildlife habitat. In fact, most scales used to characterize the severity of drought, known as “drought indices”, don’t include soil moisture measurements, relying instead on atmospheric data. Current barriers to the incorporation of soil moisture data include a lack of consensus regarding how to best construct soil moisture-based drought indices, the challenges associated...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2015,
CASC,
Completed,
Drought,
Drought,
As in many areas of high relief, debris flows are an important process linkage between hillslopes and the Green River in the canyons of the eastern Uinta Mountains, yet the physical conditions that lead to debris flow initiation are unknown. A recent episode of enhanced debris-flow and wildfire activity provided an opportunity to examine the geomorphic impact of fire and the processes by which weathered bedrock is transported to the Green River. Field investigations and analysis of elevation and precipitation data were undertaken in 15 catchments with recent debris flows to determine how surficial geology, wildfire, topography, bedrock strength, and meteorology influence hillslope processes. The recent debris flows...
Categories: Publication;
Types: Citation,
Journal Citation;
Tags: Geomorphology,
Green River,
bedrock,
debris flow,
eastern Uinta Mountains,
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,
This data release contains point clouds obtained from three terrestrial laser scanner (TLS) surveys of a hillslope burned by the 2016 Fish Fire in the San Gabriel Mountains, CA, USA. The TLS surveys were completed with a Leica ScanStation C10. All point data are in local coordinates and the units are in meters. The first survey was made on 19 November 2016 prior to the first post-wildfire rainstorm. The second survey was performed on 5 January 2017. Two runoff-generating rainstorms occurred between the first and second surveys. The two rainstorms had peak fifteen-minute average rainfall intensities of 27 mm/h and 10 mm/h, respectively. The third survey was performed on 22 February 2017, following five additional...
Conservation planning efforts for sagebrush ecosystems of western North America increasingly focus on enhancing operational resilience though decision-support tools that link spatially explicit variation in soil and plant processes to outcomes of biotic and abiotic disturbances spanning large spatial extents. However, failure to consider higher trophic-level fauna (e.g. wildlife) in these tools can hinder efforts to operationalize resilience owing to spatiotemporal lags between slower reorganization of plant and soil processes following disturbance, and faster behavioral and demographic responses of fauna to disturbance. These spatial products provide additional examples for managers of sagebrush ecosystems and...
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 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 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.
The FSim burn probability was used to determine the burn probability of the coldwater fish assemblage range in the ecoregion. This layer was used to examine wildfire risk to areas within the coldwater fish assemblage range.
The FSim burn probability was used to determine the burn probability of the bull trout range in the ecoregion. This layer was used to examine wildfire risk to areas within the bull trout 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.
Derived data layer based upon the MTBS data layer. The layer represents the distance to the mapped burns and is used to model invasive annual grasses and noxious forbs. 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,...
Types: Downloadable;
Tags: BLM,
Bureau of Land Management,
Burned Area Extent,
CBR 2010,
Central Basin and Range,
Burn probability (BP) models involve the simulation of multiple individual wildfires across a landscape to obtain estimates of fire likelihood at any given location based on ignition source, local terrain, fuels and weather. We used FlamMap software to generate BP for 10,000 simulated fires under the three ignition scenarios: human ignition scenario (HIS), lightning ignition scenario (LIS) and random ignition scenario (RIS) for 13 sky island mountain ranges in Arizona. The zipped folder contains 42 BP models in geotiff format. The naming convention for each tiff is: mountain_range_name + scenario type (human, lightning, or random) + bp.
This product is published on a provisional basis to provide necessary information to individuals assessing burn severity impacts on a time sensitive basis. This product was produced using the methods of the Monitoring Trends in Burn Severity (MTBS) Program; however, this fire may not meet the criteria for an MTBS initial assessment. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. MTBS typically maps fires using an initial assessment (immediately after the fire) or an extended assessment (peak of green the season...
The National Park Service (NPS) 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. The MTBS Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. 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...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: AK,
Alaska,
Burn severity,
Burned area,
CONUS,
The Rapid Assessment of Vegetation Condition after Wildfire (RAVG) program provides assessments of vegetation conditions following large fires on forested lands. Fire effects are represented by three metrics: percent change in live basal area (BA), percent change in canopy cover (CC), and the standardized Composite Burn Index (CBI). These data are derived from moderate resolution multi-spectral imagery (e.g., Landsat 8 Operational Land Imager or Sentinel-2 Multispectral Instrument). The Relative Differenced Normalized Burn Ratio (RdNBR), which is correlated to the variation of burn severity within a fire, is calculated from a pair of images (pre- and postfire), judiciously selected to capture fire effects. The three-severity...
The RAVG (Rapid Assessment of Vegetation Condition after Wildfire) program provides assessments of vegetation conditions following large fires on forested lands. Fire effects are represented by three metrics: percent change in live basal area (BA), percent change in canopy cover (CC), and the standardized Composite Burn Index (CBI). These data are derived from moderate resolution multi-spectral imagery (e.g., Landsat 8 Operational Land Imager or Sentinel-2 Multispectral Instrument). The Relative Differenced Normalized Burn Ratio (RdNBR), which is correlated to the variation of burn severity within a fire, is calculated from a pair of images (pre- and postfire), judiciously selected to capture fire effects. The three...
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