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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of their availability. Utilizing a previously developed crop classification model (CCM), which was used to generate historical annual crop cover maps (classifying nine major crops: corn, cotton, sorghum, soybeans, spring wheat, winter wheat, alfalfa, other hay/non alfalfa, fallow/idle cropland, and ‘other’ as one class for remaining crops), we hypothesized that such crop cover maps could be generated in near real time (NRT). The CCM was trained on 14 temporal and 15 static geospatial datasets, known as predictor variables, and...
A raster dataset representing the soil organic carbon content of surface soil horizons (top 15 cm or ~6 inches) in the conterminous United States. Soil organic carbon is a readily component of soil organic matter, which plays an important role the functioning of soils, including formation of soil structure, soil nutrient content, soil moisture retention, and carbon sequestration. Soil carbon content here is measured as percent by mass. This dataset was created using the soil percent organic carbon 100 m spatial resolution predictive rasters for 0, 5, and 15 cm depths developed by Ramcharan et al. (2018). The average soil organic carbon over the top 15 cm was calculated using the trapezoidal rule, and then put into...
A raster dataset representing multi-year mean (1998-2018) capacity factors (CF) for a solar photovoltaic system based on current technology, for the Conterminous United States. These data are calculated using ½ hourly irradiance values from the National Solar Radiation Database (NSRDB) Sengupta et al. (2018), and the Systems Advisor Model (Blair et al. 2014). Cell values represent the estimated capacity factor (a ratio of net generation to the maximum generation) for photovoltaic energy production for a 1-axis tracking system (technology details found in Maclaurin et al. 2019). The continuous raster were put into 8 quantile bins for interpretation and reporting. For more information and further data, please visit...
This metadata record describes a series of tabular datasets containing metrics used to characterize drought for select United States Geological Survey (USGS) streamgages for the climate years (April 1 – March 31) 1921 to 2020. These streamgages are a subset of those used in Geospatial Attributes of Gages for Evaluating Streamflow, version 2 (GAGES-II, Falcone, 2011) in the conterminous United States (CONUS). These metrics include streamflow percentiles, identified drought events, annual low streamflow, and drought statistics for each event.
Raw sequencing data as generated by the five different methods used are provided for each of the three samples used in the comparison. The files are in FASTQ format as exported from the Oxford Nanopore’s MK1C using MinION flowcells. Files are labeled according to the method (as described in the paper) and the Sample ID). The MK1C exports data in blocks of 6000 reads per FASTQ file and all the FASTQ files from each method and sample are grouped in a common folder.
Categories: Data;
Tags: CONUS,
Emerging Infectious Disease,
Highly Pathogenic Avian Influenza Virus,
Methods Comparison,
Methods Development,
These tabular data sets represent daily climate metrics processed from 4 kilometer GridMET data (Abatzoglou, 2013) for the period of record 1980 through 2020 and compiled for three spatial components: select United States Geological Survey stream gage basins (Staub and Wieczorek, 2023), 2) individual reach flowline catchments of the Upper and Lower Colorado (ucol) portions of the Geospatial Fabric for the National Hydrologic Model, version 1.1 (nhgfv11, Bock and others, 2020 ), and 3) the upstream watersheds of each individual nhgfv11 flowline catchments. Flowline reach catchment information characterizes data at the local scale using the python tool set called gdptools (McDonald, 2021). Reach catchments accumulated...
Categories: Data;
Tags: CONUS,
Conterminous United States,
Coterminous United States,
Geospatial Fabric,
GridMET,
This product ("Prairie fires") presents burned area boundaries for The Flint Hills Ecoregion (KS and OK), one of the most fire prone ecosystems in the United States where hundreds of thousands of acres burn annually as prescribed fire and wildfire. The prairie fire products provide the extent of larger prairie fires in the Flint Hills to record the occurrence of fire and can be used to identify individual burned areas within the perimeters. This product is published to provide fire information of the most fire prone ecosystems to individuals and land management communities for assessing burn extent and impacts on a time sensitive basis. The methods used to produce the prairie fire products from 2019 to present are...
This map layer is a vector polygon shapefile of the perimeters of all currently inventoried fires occurring between calendar year 2021 and 2021 that do not meet standard MTBS size criteria. These data are published to augment the data that are available from the MTBS program. This product was produced using the methods of the Monitoring Trends in Burn Severity Program (MTBS); however, these fires do not meet the size criteria for a standard MTBS 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...
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 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 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 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 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 Monitoring Trends in Burn Severity (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 scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
The Monitoring Trends in Burn Severity (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 scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
The Monitoring Trends in Burn Severity (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 scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of their availability. Utilizing a previously developed crop classification model (CCM), which was used to generate historical annual crop cover maps (classifying nine major crops: corn, cotton, sorghum, soybeans, spring wheat, winter wheat, alfalfa, other hay/non alfalfa, fallow/idle cropland, and ‘other’ as one class for remaining crops), we hypothesized that such crop cover maps could be generated in near real time (NRT). The CCM was trained on 14 temporal and 15 static geospatial datasets, known as predictor variables, and...
Peak ground velocity (PGV) gridded probabilistic seismic hazard data for the updated 2018 National Seismic Hazard Model (NSHM) for the Conterminous United States (CONUS). PGV hazard curves and ground motions have been calculated on a 0.05 by 0.05 degree grid using the NSHM CONUS 2018 earthquake source model. PGV support has been incorporated into the NSHM using a newly developed PGV model conditioned on pseudo-spectral acceleration (Abrahamson and Bhasin, 2020, PEER Report No. 2020/05). See Powers et al. (in press) for implementation details. This dataset complements the "Data Release for Additional Period and Site Class Data for the 2018 National Seismic Hazard Model for the Conterminous United States (ver. 1.2,...
Integrating data into a spatial framework After acquiring data, variables were attributed to a national stream coverage for use in assessment following Wang et al. (2011). The National Hydrography Dataset Version 1 (NHDV1) is a 1:100,000 scale representation of streams from throughout the conterminous United States. The NHDV1 identifies stream reaches as sections of streams occurring between confluences (Figure 2). We attributed all data to stream reaches (i.e., fish data, fragmentation metrics by dams) or to local catchments and 90m buffers draining to stream reaches (i.e., human land uses, mining activities, impervious surfaces, etc.). Local catchments (watersheds) and buffers are the land areas draining directly...
Knowledge of where energy resources occur and where there is existing development or new development potential, in conjunction with model-predicted golden eagle relative nest site density (Dunk et al. 2019), can be used to identify areas with higher or lower potential resource conflict. Depicted on the map is a 16-class raster that displays the spatial overlap of wind resources (4 classes, low to high) and golden eagle relative nest site density (4 classes, lower to higher). This raster displays the intersection of multi-year mean capacity factors (MCF) for wind turbines and the golden eagle relative nest site density within ecoregion raster. We have divided each probability into equal intervals, and then intersected...
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