Filters: partyWithName: U.S. Geological Survey, MIDCONTINENT REGION (X)
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The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Iowa,
USGS-EMA-LOW-MR Landscape Ecology,
USGS-EMA-LOW-PL Mississippi River,
Wisconsin,
aquatic vegetation,
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. 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. Output from this code was used as an input feature in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
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 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...
Katahdin Woods and Waters National Monument was established on August 24, 2016. The monument spans mountains and forest lands in north central Maine. High-resolution aerial imagery was collected on October 5, 2019 with a Phase One iXU-R 180 RGB camera co-mounted with a Phase One iXU-RS 160 Achromatic camera. Images from the two cameras are merged to create 4-band imagery that can be displayed as either true-color (RGB) or color-infrared (CIR). The imagery has a resolution of approximately 0.15 meter/pixel (6 inches).
The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
This data release includes mercury concentrations and mercury stable isotope measurements measured in sediments and biological tissues collected from the Saint Louis River located in Minnesota. Sediments and biota were collected by the U.S. Geological Survey, U.S. Environmental Protection Agency, U.S. Army Corps of Engineers, and federal contractors (Battelle) from 2017-2021. Collection regions included nearshore zones within the main estuary, remedial sites within the lower river, and upstream reservoir sites. Sediments were analyzed for total mercury, methylmercury, and mercury stable isotopes by the U.S. Geological Survey Mercury Research Laboratory (MRL, Madison, Wisconsin). Biological samples were analyzed...
Categories: Data;
Tags: Environmental Health,
Geochemistry,
Saint Louis River, Minnesota,
USGS Science Data Catalog (SDC),
biota,
This mosaic was created using high-resolution aerial imagery collected on September 15, 2021 with a Phase One iXU-RS 1000 4-band aerial camera system (RGB and achromatic). The raw image files from the two cameras were combined to create 4-band imagery. The mission was flown at approximately 1,200 meters above ground level resulting in a ground sample distance of 0.15 meters/pixel (6 inches/pixel). The area of interest is the Emiquon Preserve in Illinois and the mosaic is for the purpose of habitat monitoring. 4-band imagery allows for displaying the image as either True Color (RGB) or Color Infrared (CIR). To display the mosaic as RGB the Red channel should be set to Band 1, the Green channel to Band 2 and the Blue...
This dataset includes U.S. Geological Survey (USGS) flood-frequency analysis software PeakFQ input and output files for 298 streamgages in Minnesota, Iowa, and South Dakota. Input files for each streamgage include text files with peak streamflow data through 2019 obtained from the USGS National Water Information System (NWIS) and PeakFQ specification information in a .psf file. Output files are in a .prt file with flood-frequency results.
This dataset is a collection of cropped avian images that pair with species identification annotation values.
This data release contains historical SnowModel (Liston and Elder, 2006) output for the Crown of the Continent and surrounding areas in Montana and Idaho, USA; and Alberta and British Columbia, Canada from September 1, 1981 through August 31, 2020. Fifteen daily variables were simulated or derived for this release: (1) snow water equivalent (swed), (2) liquid precipitation (rpre), (3) solid precipitation (spre), (4) albedo (albd), (5) glacial ice melt (glmt), (6) total precipitation (prec), (7) runoff (roff), (8) snow covered area (sca), (9) snow density (sden), (10) snowmelt (smlt), (11) snow depth (snod), (12) snow sublimation (ssub), (13) air temperature (tair), (14) wind speed (wspd), and (15) wind direction...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Alberta,
British Columbia,
Crown of the Continent,
Glacier National Park,
Idaho,
The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
Water quality and fish tissue samples were collected and measured for mercury concentrations in a total of 23 small to medium size lakes in Minnesota to assess the impact that zebra mussel (Dreissena polymorpha) invasion had on mercury bioaccumulation. Water samples were collected in October and November of 2021 from 22 lakes and analyzed for total mercury, methylmercury, dissolved organic carbon, and suspended particulate matter at the U.S. Geological Survey (USGS) Mercury Research Laboratory (MRL). Tissue samples of walleye (Sander vitreus) and yellow perch (Perca flavescens) were collected by researchers at the University of Minnesota, Twin Cities from July to October in 2019 and 2021 and June to October in 2020...
Categories: Data;
Tags: Aquatic Biology,
Environmental Health,
Minnesota,
USGS Science Data Catalog (SDC),
Water Quality,
Cladophora biomass and supporting data collected in the Great Lakes, 2018 (ver. 1.1, September 2020)
Note: An error was discovered in the BenthicBiomas Table, mostly in designation of BDLs and zeros. Data are undergoing further QC and the corrected dataset will be posted soon. This dataset records Cladophora and associated submerged aquatic vegetation (SAV) biomass collected approximately monthly during the growing season of 2018 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors...
Categories: Data,
Data Release - Revised;
Tags: Aquatic Biology,
CTD measurement,
Ecology,
Great Lakes Region,
Lake Erie,
The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
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 includes text files of well data and shapefiles of potentiometric contours of the Fort Union, Hell Creek, and Fox Hills aquifers within the Standing Rock Reservation. The data accompanies a USGS scientific investigations map from Anderson and Lundgren (2024). The Standing Rock Sioux Tribe (the Tribe) of North and South Dakota and the U.S. Geological Survey (USGS) completed a comprehensive assessment of groundwater resources within the Standing Rock Reservation.Generalized potentiometric surfaces of the Fort Union, Hell Creek, and Fox Hills aquifers were constructed to assess the groundwater resources of the Standing Rock Reservation. Water-level data from the U.S. Geological Survey Groundwater...
In the Great Lakes basin, there are numerous organizations undertaking scientific monitoring and research efforts with the goal of identifying threats and evaluating management strategies that will protect and restore the Great Lakes ecosystem. Coordination among all these stakeholders is a challenge, and having a centralized location where researchers and managers can identify relevant scientific activities and access fundamental information about these activities is crucial for efficient management. The Science in the Great Lakes (SiGL) Mapper was a map-based discovery tool that spatially displayed basin-wide multidisciplinary monitoring and research activities conducted by both USGS and partners from all five...
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