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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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Floodplain inundation is believed to be the dominant physical driver of an array of ecosystem patterns and processes in the Upper Mississippi River System (UMRS). Here, we present a time series of daily surface water inundation depths (in feet) for floodplain surfaces in the UMRS. The time series data are for the months of April through September of every year since 1940. These months were chosen because it approximates the period during which most biophysical processes such as vegetation metabolism and biogeochemical cycling are likely to be strongest across the longitudinal gradient of the UMRS. Data were derived from a geospatial model of surface water inundation developed for the UMRS and described in Van Appledorn...
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Floodplain inundation is believed to be the dominant physical driver of an array of ecosystem patterns and processes in the Upper Mississippi River System (UMRS). Here, we present a time series of daily surface water inundation depths (in feet) for floodplain surfaces in the UMRS. The time series data are for the months of April through September of every year since 1940. These months were chosen because it approximates the period during which most biophysical processes such as vegetation metabolism and biogeochemical cycling are likely to be strongest across the longitudinal gradient of the UMRS. Data were derived from a geospatial model of surface water inundation developed for the UMRS and described in Van Appledorn...
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Floodplain inundation is believed to be the dominant physical driver of an array of ecosystem patterns and processes in the Upper Mississippi River System (UMRS). Here, we present the relative elevation of a slope-detrended floodplain terrain surface and river mile location used to map surface water depths derived from gaging locations along UMRS, as described in Van Appledorn et al. (2021; doi: 10.1002/rra.3628). We excluded areas permanently wetted (aquatic areas), surfaces in agricultural production, roads, and developed areas. The data are intended for use in geospatial analyses of UMRS floodplain ecosystem patterns and processes.
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Floodplain inundation is believed to be the dominant physical driver of an array of ecosystem patterns and processes in the Upper Mississippi River System (UMRS). Here, we present the relative elevation of a slope-detrended floodplain terrain surface and river mile location used to map surface water depths derived from gaging locations along UMRS, as described in Van Appledorn et al. (2021; doi: 10.1002/rra.3628). We excluded areas permanently wetted (aquatic areas), surfaces in agricultural production, roads, and developed areas. The data are intended for use in geospatial analyses of UMRS floodplain ecosystem patterns and processes.
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Floodplain inundation is believed to be the dominant physical driver of an array of ecosystem patterns and processes in the Upper Mississippi River System (UMRS). Here, we present the relative elevation of a slope-detrended floodplain terrain surface and river mile location used to map surface water depths derived from gaging locations along UMRS, as described in Van Appledorn et al. (2021; doi: 10.1002/rra.3628). We excluded areas permanently wetted (aquatic areas), surfaces in agricultural production, roads, and developed areas. The data are intended for use in geospatial analyses of UMRS floodplain ecosystem patterns and processes.
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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...
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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.
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This dataset is a collection of cropped avian images that pair with species identification annotation values.
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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...
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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...
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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...


map background search result map search result map PeakFQ input and output files for 298 streamgages in Minnesota, Iowa, and South Dakota through water year 2019. Walleye (Sander vitreus), Yellow Perch (Perca flavescens) and Surface Water Mercury Concentrations in Minnesota Lakes Katahdin Woods and Waters National Monument 4-Band Aerial Imagery Mosaics - Three Rivers and Lunksoos Camps Units Python code used to download U.S. Census Bureau data for public-supply water service areas Machine learning model that estimates public-supply deliveries for domestic and other use types Images to automate the classification of avian species UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 12 2021 Emiquon Preserve 4-Band Mosaic Assessment of Mercury and Mercury Stable Isotopes in Sediments and Biota from Reservoirs and Remedial Zones within the Saint Louis River, Minnesota Python code used to determine average yearly and monthly tourism per 1000 residents for public-supply water service areas HUC12-Monthly Summaries UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 11 UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 07 UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 03 UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 01 UMRS Floodplain Inundation Model - Illinois River - La Grange Pool UMRS Floodplain Inundation Depths - Pool 3 UMRS Floodplain Inundation Model - Pool 7 UMRS Floodplain Inundation Model - Pool 12 UMRS Floodplain Inundation Depths - Pool 26 2021 Emiquon Preserve 4-Band Mosaic UMRS Floodplain Inundation Model - Pool 7 UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 07 UMRS Floodplain Inundation Depths - Pool 3 UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 12 UMRR LTRM 2020 4-Band Aerial Imagery Mosaic - Mississippi River Pool 03 UMRS Floodplain Inundation Model - Pool 12 UMRR LTRM 2020 LCU Mapping - Mississippi River Pool 11 Assessment of Mercury and Mercury Stable Isotopes in Sediments and Biota from Reservoirs and Remedial Zones within the Saint Louis River, Minnesota UMRS Floodplain Inundation Depths - Pool 26 UMRS Floodplain Inundation Model - Illinois River - La Grange Pool Walleye (Sander vitreus), Yellow Perch (Perca flavescens) and Surface Water Mercury Concentrations in Minnesota Lakes HUC12-Monthly Summaries PeakFQ input and output files for 298 streamgages in Minnesota, Iowa, and South Dakota through water year 2019. Images to automate the classification of avian species Python code used to download U.S. Census Bureau data for public-supply water service areas Machine learning model that estimates public-supply deliveries for domestic and other use types Python code used to determine average yearly and monthly tourism per 1000 residents for public-supply water service areas