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LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and...
LANDFIRE (LF) 2022 Fuel Vegetation Cover (FVC) represents the LF Existing Vegetation Cover (EVC) product, modified to represent pre-disturbance EVC in areas where disturbances have occurred over the past 10 years. EVC is mapped as continuous estimates of canopy cover for tree, shrub, and herbaceous lifeforms with a potential range from 10% to 100%. Continuous EVC values are binned to align with fuel model assignments when creating FVC. FVC is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes two new mean high water (MHW) shorelines extracted from lidar data collected in 2010 and 2017-2018. Previously published historical shorelines for South Carolina (Kratzmann and others, 2017)...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic Coast,
Atlantic Coast,
Baseline,
DSAS,
Digital Shoreline Analysis System,
Probability map of Cheatgrass occurrence in relation to vegetation, abiotic, and anthropogenic features. These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release.
Probability map of green-tailed towhee occurrence in relation to vegetation, abiotic, and anthropogenic features. These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release.
Probability map of Halogeton occurrence in relation to vegetation, abiotic, and anthropogenic features. These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release.
Probability map of least chipmunk occurrence in relation to vegetation, abiotic, and anthropogenic features. These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release.
Vegetation change is an important issue facing managers at Isle Royale National Park (ISRO). These data were created using high-resolution imagery collected in the winter of 2017 which was compared to the vegetation map of the National Park published in 2000 (project imagery collected in 1994 and 1996). These data review where vegetation cover type, density, and pattern have changed since imagery collection for the 2000 publication and provide a proposed reason for the change.
Airborne electromagnetic (AEM), magnetic, and radiometric data were acquired in late February to early March 2018 along 2,364 line-kilometers in the Shellmound, Mississippi study area. Data were acquired by CGG Canada Services, Ltd. with three different helicopter-borne sensors: the CGG Canada Services, Ltd. RESOLVE frequency-domain AEM instrument that is used to map subsurface geologic structure at depths up to 100 meters, depending on the subsurface resistivity; a Scintrex CS-3 cesium vapor magnetometer that detects changes in deep (hundreds of meters to kilometers) geologic structure based on variations in the magnetic properties of different formations; and a Radiation Solutions RS-500 spectrometer that detects...
Categories: Data;
Tags: GGGSC,
Geology, Geophysics, and Geochemistry Science Center,
Greenwood,
Leflore County,
MRVA,
Note: This data release has been superseded, available here: https://doi.org/10.5066/P9MYL7WJ This data release contains processed high-resolution multichannel sparker seismic-reflection (MCS) data that were collected aboard Humboldt State University’s R/V Coral Sea in October of 2018 on U.S. Geological Survey cruise 2018-658-FA on the shelf and slope between Cape Blanco, Oregon, and Cape Mendocino, California. MCS data were collected to characterize quaternary deformation and sediment dynamics along the southern Cascadia margin.
High-resolution single-channel Chirp and minisparker seismic-reflection data were collected by the U.S. Geological Survey in September and October 2006, offshore Bolinas to San Francisco, California. Data were collected aboard the R/V Lakota, during field activity L-1-06-SF. Chirp data were collected using an EdgeTech 512 chirp subbottom system and were recorded with a Triton SB-Logger. Minisparker data were collected using a SIG 2-mille minisparker sound source combined with a single-channel streamer, and both were recorded with a Triton SB-Logger.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Bathymetry and Elevation,
Bolinas,
CMHRP,
Coastal and Marine Hazards and Resources Program,
Elevation,
This portion of the data release presents a digital surface model (DSM) and hillshade image of the intertidal zone at Lone Tree Point, Kiket Bay, WA. The DSM has a resolution of 4 centimeters per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-05. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, data artifacts resulting from noise in the original imagery have not been removed. The raw imagery used to create the DSM was acquired using a UAS fitted with a Ricoh...
This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during the July 2021 unoccupied aerial system (UAS) surveys of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white cross patterns and "X" marks placed on the ground using temporary chalk. The GCP positions were measured using dual-frequency post-processed kinematic (PPK) GPS with corrections...
Categories: Data;
Tags: Bathymetry and Elevation,
Benson Beach,
CHMRP,
Cape Disappointment,
Clatsop County,
In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science Center made in-situ observations during 2018-2019 and 2022-2023 at two sites: Thompsons Beach, NJ and Stone Harbor, NJ. Marsh creek hydrodynamics and water quality including currents, waves, water levels, water...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic,
Hurricane Sandy,
National Fish and Wildlife Foundation,
New Jersey,
Stone Harbor,
These data were compiled for evaluating plant water use, or river-reach level evapotranspiration (ET) data, in the riparian corridor of the Colorado River delta as specified under Minute 319 of the 1944 Water Treaty. Additionally, these data were compiled for evaluating restoration-level data in Reach 2 and Reach 4, as specified under Minute 323 of the 1944 Water Treaty. Objectives of our study were to measure the peak growing season evapotranspiration (ET) for the average of months in summer-fall (May to October) for the seven reaches, for the full riparian corridor, and for four restoration sites, from 2013 through 2022. The seven reach areas from the Northerly International Boundary (NIB) to the end of the delta...
Water availability for human and ecosystem needs is a function of both water quantity and water quality, as described in the U.S. Geological Survey (USGS) Water Science Strategy (Evenson and others, 2013). Recently, a quantitative approach to prioritize candidate watersheds for monitoring investment was developed to understand changes in water availability and advance the objectives of new USGS programs (Van Metre and others, 2020). In this study design, the contiguous United States (CONUS) was divided into 18 regions (referred to here as “hydrologic regions” or “HRs”) with relatively homogeneous hydrologic drivers and processes to represent the wide diversity in conditions that exist across the CONUS. The gap analysis...
Categories: Data;
Tags: Ecology,
Geochemistry,
Hydrology,
USGS Science Data Catalog (SDC),
United States,
The LANDFIRE (LF) Canadian Forest Fire Danger Rating System (CFFDRS) product depicts fuel types as an identifiable association of fuel elements of distinctive species, form, size, arrangement, and continuity. CFFDRS exhibits characteristic fire behavior under the specified burn conditions. In LF 2022 Canadian fuel models are derived from the Fuel Model Guide to Alaska Vegetation (Alaska Fuel Model Guide Task Group, 2018) and subsequent updates. The LF CFFDRS product contains the fuel models used for the Fire Behavior Prediction (FBP) system fuel type inputs. Default values assigned to the Canadian Fuel Models required to run the Prometheus fire behavior software (Prometheus, 2021) are added as attributes to the...
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