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This dataset is a file of contour lines representing the estimated altitude of the water table in western Sarpy County. This dataset was developed as part of a cooperative study between the Papillion-Missouri River Natural Resources District (PMRNRD) and USGS which began in 2017. The goal of this study was to develop a hydrogeologic visualization model of western Sarpy County using GeoScene3D. In 2016, the PMRNRD contracted airborne electromagnetic surveys (AEM) of the area to be completed to better understand the stratigraphy and hydrogeology of the western Sarpy County area. The PMRNRD determined that they wanted to incorporate the AEM data into a visualization tool that would allow PMRNRD staff to easily interact...
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...
Time series data of water surface elevation and wave height were acquired at ten locations for 517 days (in three separate deployments) off the north coast of Roi-Namur Island, Kwajalein Atoll, Marshall Islands, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reefs were as follows: ROI13W1 and ROI13E1 – fore reef ROI13W2 and ROI13E2 – outer reef flat ROI13W1 and ROI13E1 – middle reef flat ROI13W1 and ROI13E1 – inner reef flat
This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. These data represent the flowline network in the Green Bay Restoration Assessment (GBRA). It is attributed with the number of disconnections (e.g., road crossings) between the reach and Lake Ontario. The more road crossings on a flowline the more disconnected that area is from the lake and the less suitable it will be for restoration. These data help identify the condition of hydrologic separation between potential restoration areas and Lake Ontario. Low numbers represent fewer disconnections, such as culverts, between the reach and the water body requiring no flow network modification...
These data were compiled to provide a resource for other researchers interested in water-surface elevations and flow velocity across a wide range of discharge in the study reach for the project. Objective(s) of our study were to construct a two-dimensional hydrodynamic model for the 15.8 mile tailwater reach of the Colorado River in Glen Canyon between Glen Canyon Dam and Lees Ferry, Arizona. These data represent the results of the two-dimensional modeling effort with each data table (50) including the results of each run of the model. Additionally, other data represent a comparison of modeled water surface elevations to measured water surface elevations for historic Bureau of Reclamation cross sections in the study...
These data represent total vegetation and surface water along approximately 12 kilometers of the Paria River upstream from the confluence of the Colorado River at Lees Ferry, Arizona. They are derived from airborne, multispectral imagery obtained in late May 2009, 2013, and 2021, collected with a push-broom sensor with 4 spectral bands depicting Blue, Green, Red and Near-Infrared wavelengths at a spatial resolution of 20 centimeters. The vegetation classification data were created using a supervised classification algorithm provided by Harris Geospatial in ENVI version 5.6.3 (Exelis Visual Information Solutions, Boulder, Colorado). The water data were created using a Green Normalized Difference Vegetation Index...
These data were compiled to create models that estimate entrainment rates and population growth rates of smallmouth bass below Glen Canyon Dam. Objective(s) of our study were to predict smallmouth bass entrainment rates and population growth under different future scenarios of Lake Powell elevations and management. These data represent parameters needed for associated models and data needed to produce figures. These data were collected from publicly available online sources including published papers and federal government datasets. These data were assembled by researchers from U.S. Geological Survey, Utah State University, Colorado State University, U.S. Fish and Wildlife Service. These data can be used to run...
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 High Plains aquifer extends from approximately 32 to 44 degrees north latitude and 96 degrees 30 minutes to 106 degrees west longitude. The aquifer underlies about 175,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This digital dataset consists of a raster of water-level changes for the High Plains aquifer, predevelopment (about 1950) to 2019. It was created using water-level measurements from 2,741 wells measured in both the predevelopment period (about 1950) and in 2019, the latest available static water level measured in 2015 to 2018 from 71 wells in New Mexico and using other published information on water-level change in areas with few water-level...
In May 2021, the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey’s (USGS), Southwest Biological Science Center (SBSC) acquired airborne multispectral high resolution data for the Colorado River in Grand Canyon in Arizona, USA. The imagery data consist of four bands (Band 1 – red, Band 2 – green, Band 3 – blue, and Band 4 – near infrared) with a ground resolution of 20 centimeters (cm). These image data are available to the public as 16-bit GeoTIFF files, which can be read and used by most geographic information system (GIS) and image-processing software. The spatial reference of the image data are in the State Plane (SP) map projection using the central Arizona zone (FIPS 0202)...
Groundwater age distributions and susceptibility to natural and anthropogenic contaminants were assessed for selected wells, streambed piezometers, and springs in southeastern Minnesota. The data provide information to understand how long it will take to observe groundwater quality improvements from best management practices implemented at land surface to reduce losses of nitrate (and other chemicals) from agricultural practices. Nineteen water samples were collected from ten wells, three streambed piezometers, and four springs between August 2020 and September 2022. Two of these samples are field replicate samples collected from a spring site and a well site. A child item contains historical data from 15 water...
This dataset contains a thematic [classified] image derived from supervised classification of WorldView-3 satellite imagery. This data release contains a geospatial thematic (raster) image derived from a supervised classification of WorldView-3 satellite imagery obtained during 2020–21. Arundo donax (Arundo cane, giant reed, or Carrizo cane), is an invasive bamboo-like perennial grass most common to riparian areas throughout the southwestern United States. Because it displaces native riparian vegetation, Arundo cane has greatly disrupted the health of riparian ecosystems in the southwestern United States and northern Mexico during the past 50 years. Arundo cane also has created border security problems along the...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Arundo cane,
Arundo donax,
Carrizo cane,
Giant Reed,
Rio Grande,
This dataset contains a thematic [classified] image derived from supervised classification of WorldView-3 satellite imagery. This data release contains a geospatial thematic (raster) image derived from a supervised classification of WorldView-3 satellite imagery obtained during 2020–21. Arundo donax (Arundo cane, giant reed, or Carrizo cane), is an invasive bamboo-like perennial grass most common to riparian areas throughout the southwestern United States. Because it displaces native riparian vegetation, Arundo cane has greatly disrupted the health of riparian ecosystems in the southwestern United States and northern Mexico during the past 50 years. Arundo cane also has created border security problems along the...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Arundo cane,
Arundo donax,
Carrizo cane,
Giant Reed,
Rio Grande,
This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon in 2014 (USGS Field Activity Number 2014-631-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9 degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry and Elevation,
CMHRP,
Clatsop County,
Coastal and Marine Hazards and Resources Program,
Columbia River,
These data address experimental evaluations of dietary preference by captive brown treesnakes on Guam. Snakes were collected from the wild in areas with birds present and in areas without birds present 2018–2019. Snakes were then run through preference trials during which they were offered first live lures (mouse and finch) in snake traps on opposite sides of the arena. On the second night, snakes were offered dead carrion (baits) of each prey type (mouse, chicken chick) equal to 30% of their mass. Choices were monitored overnight using game cameras and then transcribed the following day. Individuals were classified as BIRD or NOBIRD snakes based on whether they had birds in their gut contents at the time of capture....
Categories: Data;
Tags: Ecology,
Guam,
Guam National Wildlife Refuge,
Preference,
USGS Science Data Catalog (SDC),
This data release includes data and metadata on 1) the coverage and composition of plants 2) species specific plant traits 3) sampling locations and 4) environmental data. All sites were within Hawaii Volcanoes National Park on Hawaii Island. Plant cover data were obtained from National Park Service Inventory and Monitoring Program. Plant trait data was collected for these plots in 2014. This study aims to evaluate how traits of native and exotic plant species change along environmental gradients and what this suggests for plant competition and invasion.
Categories: Data;
Tags: Ecology,
Hawaii,
Hawaii Volcanoes National Park,
USGS Science Data Catalog (SDC),
botany,
Hawaiian hoary bats (Lasiurus cinereus semotus) were captured at multiple locations on the east side of Hawaii Island from May 2019 to October 2019. Radio transmitters were affixed to captured bats and, when possible, radio telemetry was used to locate bats in trees used for day-roosts. In 2019, three maternity roosts were identified however only two were suitable for video recording. Thermal video recording at two maternal roosts was used to identify the time of bat departure and arrival at a roost. We examined an average of 2 hours during sunset and sunrise (range = 0.9 to 5.4 hours). The time of bat departure from a roost ranged from 53 minutes before sunset to 20 minutes after sunset (n = 48, mean = 2.7 minutes...
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