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This dataset consists of Structure-from-Motion (SfM) - derived point clouds and highly detailed orthomosaic images of four roadcut exposures covering the upper part of the Harrell Shale, the full Brallier Formation, the full Foreknobs Formation, and the lower part of the Hampshire Formation at Baker, West Virginia. For each roadcut exposure, two datasets are published: an orthomosaic raster image and a point cloud. The orthomosaic raster image is a vertical outcrop orthomosaic constructed from multiple orthophotos to create a geometrically rectified image. This facilitates a detailed visual inspection of the stratigraphic succession outside of a GIS environment, unlike georefrenced orthomosaics derived from aerial...
Note: this data release is currently being revised and is temporarily unavailable. This data release contains two point clouds derived from structure-from-motion photogrammetry. The first survey was conducted on 10 September 2015 and the second survey was conducted on 1 June 2016. Each survey was designed to capture a 35-meter channel reach using digital photos (1187 photos were taken in the first survey and 1085 photos were taken in the second survey). Twenty-five bolts were drilled into the bedrock channel to serve as ground control points. We used a local coordinate system to create a reference frame, but the location of all of the ground control points are attached in the file called: GCPs_exported.txt. Agisoft...
A series of field measurements of surface water velocity derived from video and Doppler velocity radar collected by small unoccupied aircraft systems (sUAS) and portable sensors were collected at seven locations in Colorado, USA, during the summer of 2023. The measurements were utilized to compute surface velocity and discharge using the Probability Concept, Large-Scale Particle Image Velocimetry (LSPIV), and Space-Time Image Velocimetry (STIV) methods. This data release includes the original videos, radar spectra, and ancillary data necessary to produce the surface water velocity and streamflow results. Data are grouped into sections (child items) based on the data type and purpose: Ancillary Scripts: this child...
Tags: Anthracite Creek, Gunnison County, Colorado, United States of America,
Aspen, Pitkin County, Colorado, United States of America,
Blue River, Summit County, Colorado, United States of America,
Colorado River, Garfield County, Colorado, United States of America,
Dillon, Summit County, Colorado, United States of America,
This is an antiquated version of the North American Breeding Bird Survey (BBS) dataset that has been superseded by a more recent release. Unless visitors have a specific need for these archived data, they should return to the Main BBS Dataset Page and choose the most recent data release, as that one will include all BBS data released to date The 1966-2022 North American Breeding Bird Survey (BBS) dataset contains avian point count data for more than 700 North American bird taxa (species, races, and unidentified species groupings). These data are collected annually during the breeding season, primarily in June, along thousands of randomly established roadside survey routes in the United States and Canada. Routes...
In late September 2017, intense precipitation associated with Hurricane Maria caused extensive landsliding across Puerto Rico. Much of the Utuado municipality in central Puerto Rico was severely impacted by landslides. Landslide density in this region was mapped as greater than 25 landslides/km2 (Bessette-Kirton et al., 2019). In order to better understand the controlling variables of landslide occurrence and runout in this region, four 2.5-km2 study areas were selected and all landslides within were mapped in detail using remote-sensing data. Included in the data release are five separate shapefiles: geographic areas representing the mapping extent of the four distinct areas (map areas, filename: map_areas), initiation...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Hurricane Maria,
Landslides,
Puerto Rico,
USGS Science Data Catalog (SDC),
Utuado,
This dataset was developed to estimate point-source total nitrogen and phosphorous loads to streams in the conterminous United States (U.S.) from December 1999 to November 2020. This dataset uses discharge and concentration information from point sources to streams in the conterminous United States from the U.S. Environmental Protection Agency (EPA) Integrated Compliance Information System - Permit Compliance System (ICIS-PCS) database. Nutrient concentrations were used to calculate point source loads. However, measured concentration data was often not available so “typical pollutant concentrations” (TPCs) were developed using concentration data from the same facility but a different time or from similar facilities....
National watershed boundary (HUC12) dataset for the conterminous United States, retrieved 10/26/2020
This child item provides a snapshot of the watershed boundary dataset which consists of a shapefile with 87,020 12-digit hydrologic unit codes (HUC12) for the conterminous United States retrieved 10/26/2020. The National Watershed Boundary Dataset (WBD) is a comprehensive set of digital spatial data that represents the surface drainages areas of the United States. Although versions of the WBD are published as part of U.S. Geological Survey National Hydrography Products, the version used to produce the water-use reanalysis was not archived and is provided here. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Public-supply...
This child item describes Python code used to retrieve gridMET climate data for a specific area and time period. Climate data were retrieved for public-supply water service areas, but the climate data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the climate data collector code were used as input feature variables in the public supply delivery and water use machine learning models. This page includes the following file: climate_data_collector.zip - a zip file containing the climate data collector Python code used to retrieve...
This child item describes R code used to determine public supply consumptive use estimates. Consumptive use was estimated by scaling an assumed fraction of deliveries used for outdoor irrigation by spatially explicit estimates of evaporative demand using estimated domestic and commercial, industrial, and institutional deliveries from the public supply delivery machine learning model child item. This method scales public supply water service area outdoor water use by the relationship between service area gross reference evapotranspiration provided by GridMET and annual continental U.S. (CONUS) growing season maximum evapotranspiration. This relationship to climate at the CONUS scale could result in over- or under-estimation...
This child item describes a machine learning model that was developed to estimate public-supply water use by water service area (WSA) boundary and 12-digit hydrologic unit code (HUC12) for the conterminous United States. This model was used to develop an annual and monthly reanalysis of public supply water use for the period 2000-2020. This data release contains model input feature datasets, python codes used to develop and train the water use machine learning model, and output water use predictions by HUC12 and WSA. Public supply water use estimates and statistics files for HUC12s are available on this child item landing page. Public supply water use estimates and statistics for WSAs are available in public_water_use_model.zip....
This child item describes R code used to determine water source fractions (groundwater (GW), surface water (SW), or spring (SP)) for public-supply water service areas, counties, and 12-digit hydrologic unit codes (HUC12) using information from a proprietary dataset from the U.S. Environmental Protection Agency. Water-use volumes per source were not available from public-supply systems so water source fractions were calculated by the number of withdrawal source types (GW/SW). For example, for a public supply system with three SW intakes and one GW well, the fractions would be 0.75 SW and 0.25 GW. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic...
Freshwater salinization is an emerging water quality issue for non-tidal streams and rivers in the Chesapeake Bay watershed (CBW), USA region. A model was developed to predict specific conductance (SC; a proxy for salinity) conditions across the CBW and departures from background SC. Discrete observations of SC from 1999-2016 were acquired from a published SC data inventory and explanatory variables describing sources of SC were compiled from several sources. Random forests modeling was conducted to predict SC at four time periods (1999-2001, 2004-2006, 2009-2011, and 2014-2016) at all non-tidal National Hydrography Dataset Plus Version 2.1 (NHDPlusV2.1; 1:100K scale) stream reaches. These predictions were then...
Categories: Data;
Tags: Chesapeake Bay watershed,
Delaware,
District of Columbia,
Ecology,
Geochemistry,
This data release includes raw detrital zircon U-Pb data for Paleoproterozoic metasedimentary rocks of the Gunnison block, central Colorado, USA. Detrital zircon U-Pb data for five samples of metasedimentary rock (totaling 1459 zircon U-Pb dates) were acquired via laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) at the University of Arizona LaserChron Center. The data provide constraints on the sediment provenance, maximum depositional age, and timing of metamorphism of these metasedimentary rocks, providing insights on the crustal and tectonic evolution of the Gunnison block and Yavapai Province.
In late September 2017, intense precipitation associated with Hurricane Maria caused extensive landsliding across Puerto Rico. Much of the Lares municipality in central-western Puerto Rico was severely impacted by landslides. Landslide density in this region was mapped as greater than 25 landslides/km2 (Bessette-Kirton et al., 2019). In order to better understand the controlling variables of landslide occurrence and runout in this region, three 2.5-km2 study areas were selected and all landslides within were mapped in detail using remote-sensing data. Included in the data release are five separate shapefiles: geographic areas representing the mapping extent of the four distinct areas (map areas, filename: map_areas),...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Geomorphology,
Hurricane Maria,
Puerto Rico,
USGS Science Data Catalog (SDC),
Utuado,
These data were compiled to investigate the distribution and breeding status of yellow-billed cuckoos (Coccyzus americanus) in southeastern Arizona xeroriparian habitat by comparing the results of standardized call-playback surveys to the results of nest searching efforts in the same sites from 2018 to 2020. The primary purpose of the study associated with these data was to determine and document the occurrence and extent of nesting in these poorly studied xeroriparian habitats. These data represent breeding evidence for yellow-billed cuckoos at 54 documented sites from 2018-2020 and the results of yellow-billed cuckoo surveys collected at 163 sites from 2013-2020 in xeroriparian habitats in southeastern Arizona....
The U.S. Geological Survey is developing national water-use models to support water resources management in the United States. Model benefits include a nationally consistent estimation approach, greater temporal and spatial resolution of estimates, efficient and automated updates of results, and capabilities to forecast water use into the future and assess model uncertainty. The term “reanalysis” refers to the process of reevaluating and recalculating water-use data using updated or refined methods, data sources, models, or assumptions. In this data release, water use refers to water that is withdrawn by public and private water suppliers and includes water provided for domestic, commercial, industrial, thermoelectric...
This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input...
This child item describes a public-supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following...
This child item describes R code used to determine whether public-supply water systems buy water, sell water, both buy and sell water, or are neutral (meaning the system has only local water supplies) using water source information from a proprietary dataset from the U.S. Environmental Protection Agency. This information was needed to better understand public-supply water use and where water buying and selling were likely to occur. Buying or selling of water may result in per capita rates that are not representative of the population within the water service area. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020....
This data release contains reflectance spectra of residue (senesced vegetation) for common row crops (corn, soybean, winter wheat) as well as diverse cover crops (cereals, legumes, brassicas) collected in the laboratory using Analytical Spectral Devices (ASD) spectrophotometers (n = 296) and collected in the field using the Italian Space Agency's spaceborne PRecursore IperSpettrale della Missione Applicativa (PRISMA) imaging spectrometer (n = 65). The data release also contains biochemical trait concentrations (nitrogen, nonstructural carbohydrates, holocellulose, and lignin) from physical samples used to evaluate biochemical trait mapping of cash crop and cover crop residue. Data collection occurred at the USDA-ARS...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beltsville, MD place #597069,
Ecology,
Environmental Health,
Land Use Change,
Remote Sensing,
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