Filters: Tags: Hydroacoustic (X)
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This dataset is comprised of three files containing northing, easting, and elevation ("XYZ") information for light detection and ranging (LiDAR) data representing beach topography and sonar data representing near-shore bathymetry of Lake Superior at Minnesota Point, Duluth, Minnesota. The point data is the same as that in LAS (industry-standard binary format for storing large point clouds) files that were used to create a digital elevation model (DEM) of the approximately 5.9 square kilometer (2.3 square mile) surveyed area. LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and methodology similar to that described by Huizinga and Wagner (2019). Multi-beam sonar data were collected...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry and Elevation,
DEM,
Duluth,
Great Lakes,
Hydroacoustic,
All gillnet data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and its partners. The Gillnet Tables contain data collected from the research vessel deploying various gear used for gillnet data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Gillnet are: GN_Annulus.csv, GN_Catch.csv, GN_Effort.csv, GN_Fish.csv, GN_L, GN_LF.csv, GN_OP.csv, GN_Prey.csv, GN_Stomach.csv, LMMB_Fish_Prey.csv, and LMMB_Invert_Prey.csv Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being...
This dataset is a digital elevation model (DEM) of the beach topography and near-shore bathymetry of Lake Superior at Minnesota Point, Duluth, Minnesota. The DEM has a 10-meter (m; 32.8084 feet) cell size and was created from a LAS (industry-standard binary format for storing large point clouds) dataset of terrestrial light detection and ranging (LiDAR) data representing the beach topography and sonar data representing the bathymetry to approximately 1.3 kilometers (0.8 miles) offshore. Average point spacing of the LAS files in the dataset are as follows: LiDAR, 0.137 m; multi-beam sonar, 1.029 m; single-beam sonar, 0.999 m. LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry and Elevation,
DEM,
Duluth,
Geomorphology,
Great Lakes,
All mensuration data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and its partners. The Mensuration Tables contain data collected from the research vessel deploying various gear used for mensuration data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Mensuration are: Mensuration.csv, MS_head_rope_depth.csv, MS_FOOT_ROPE_DEPTH, MS_Primary.csv, MS_Temperature.csv, and MS_Wingspread.csv Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being undertaken after the time...
This dataset is a LAS (industry-standard binary format for storing large point clouds) dataset containing light detection and ranging (LiDAR) data and sonar data representing the beach and near-shore topography of Lake Superior at Minnesota Point, Duluth, Minnesota. Average point spacing of the LAS files in the dataset are as follows: LiDAR, 0.137 meters (m); multi-beam sonar, 1.029 m; single-beam sonar, 0.999 m. The LAS dataset was used to create a 10-m (32.8084 feet) digital elevation model (DEM) of the approximately 5.9 square kilometer (2.3 square mile) surveyed area using the "LAS dataset to raster" tool in Esri ArcGIS, version 10.7. LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry and Elevation,
DEM,
Duluth,
Great Lakes,
Hydroacoustic,
Each line in the file “Lake Michigan fish acoustic data from 2011 to 2016.csv” represents the acoustic data and estimated fish density for a single depth layer of water. Surveys are conducted along transects, transects are divided horizontally into successive intervals, and then within an interval there are multiple successive depth layers. Area backscattering (ABC), mean acoustic size (sigma), and fish density are reported for each unique transect-interval – layer from Lake Michigan in the years 2011-2016. Area backscattering (PRC_ABC), mean acoustic size (sigma), and fish density in the intervals and layers of acoustic survey transects of Lake Michigan in the years 2011-2016. The survey is carried out using a...
Categories: Data;
Types: Citation;
Tags: Fish,
Fishery Resources,
Lake Michigan,
USGS Science Data Catalog (SDC),
environment,
A side scan image collected with Humminbird Helix 10 on November 14, 2019. Side scan sonar creates a picture or an image of the riverbed. To generate an image, side scanners measures the strength of how loud the return sonar pings are.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: DEM,
Hydroacoustic,
Illinois,
Iowa,
Lock and Dam 19,
A slope raster generated from multibeam bathymetry and terrestrial lidar collected simultaneously on November 14, 2019. Slope represents the rate of change of elevation under the water column.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: DEM,
Hydroacoustic,
Illinois,
Iowa,
Lock and Dam 19,
An XYZ generated from multibeam bathymetry and terrestrial lidar collected simultaneously on November 14, 2019. An XYZ is the raw point data that generated the original digital elevation model. This XYZ file contains latitude, longitude, elevation and intensity values for each point measured by the multibeam sonar.
A digital elevation model generated from multibeam bathymetry and terrestrial lidar collected simultaneously on November 14, 2019.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: DEM,
Hydroacoustic,
Illinois,
Iowa,
Lock and Dam 19,
The Great Lakes Research Vessel Catch (RVCAT) database is managed at the Great Lakes Science Center (GLSC). RVCAT has been used as the primary data collection tool aboard the GLSC’s research vessel operations across the Great Lakes. Content: The data set has been collected on various vessel operations on all the Great Lakes and select connecting waterways between the years 1930-2021. Data collection begins in early spring and ends in late fall. Each vessel operation was completed for a specific purpose, or target mission. Data Structure: These data are collected at the GLSC in the RVCAT Oracle database. This database has been broken down into comma separated value (csv) spreadsheets in order to facilitate greater...
These data have been collected on various vessel operations on the Great Lakes and select connecting waterways. This vessel operations data set is part of and connected to a larger database of Great Lakes research that includes trawl and gillnet catch data, sample information of fish species caught, as well as effort applied, operation conditions, and location details. The larger database also contains data on hydroacoustics, ichthyoplankton, zooplankton, zebra mussel, and benthos samples collected. Multiple operations were conducted on all Great Lakes each year (1958-2016) beginning in early spring and ending in late fall. Each vessel operation was completed for a specific purpose, or target mission, which are...
The Great Lakes Research Vessel Operations data release is taken from the Research Vessel Catch (RVCAT) database curated at the Great Lakes Science Center (GLSC). RVCAT has been used as the primary data collection tool aboard the GLSC’s research vessel operations. Content: The data set has been collected on various vessel operations on all the Great Lakes and select connecting waterways between the years 1958-2018. Data collection begins in early spring and ends in late fall. Each vessel operation was completed for a specific purpose, or target mission, which are enumerated in this data set. In addition to vessel operations data, RVCAT collects trawl and gillnet catch data, sample information of fish species caught,...
A digital elevation model hillshade generated from multibeam bathymetry and terrestrial lidar collected simultaneously on November 14, 2019. A hillshade is a grayscale 3D representation of a surface.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: DEM,
Hydroacoustic,
Illinois,
Iowa,
Lock and Dam 19,
A backscatter raster generated from multibeam bathymetry and terrestrial lidar collected simultaneously on November 14, 2019. Backscatter is the reflection of a signal and can help when determining bottom types. Harder bottom types (like rock) reflect more sound than softer bottom types (like mud), and smoother bottom types reflect more sound than rugged bottom types.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: DEM,
Hydroacoustic,
Illinois,
Iowa,
Lock and Dam 19,
All benthos data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and it’s partners. The Benthos Tables contain data collected from the research vessel deploying various gear used for benthos data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Benthos are: Benthos_Comments.csv, Benthos_Ponar.csv, and Benthos_LF Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being undertaken after the time of release. Also, a large section of this database includes legacy data that...
All mysis data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and its partners. The Mysis Tables contain data collected from the research vessel deploying various gear used for mysis data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Mysis are: Mysis_Catch.csv, Mysis_IND.csv, Mysis_OP.csv, and MY_IND Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being undertaken after the time of release. Also, a large section of this database includes legacy data that if issues...
All trawl data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and its partners. The Trawl Tables contain data collected from the research vessel deploying various gear used for trawl data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Trawl are: Bucket.csv, Prey_Length.csv, Prey_Total.csv, TR_Annulus.csv, TR_Catch.csv, TR_Fish.csv, TR_L.csv, TR_LF.csv, TR_LMMB_Fish_Prey.csv, TR_LMMB_Invert_Prey.csv, TR_OP.csv, TR_Prey.csv, TR_Sub.csv, sub_prey_total.csv, and sub_prey_length.csv Data Quality: Note that the following data release is a snapshot of the database...
The elevation contours in this dataset have a 2-foot (ft) interval and were derived from a digital elevation model (DEM) of beach topography and nearshore bathymetry of Lake Superior at Minnesota Point, Duluth, Minnesota. The DEM has a 10-meter (32.8084 ft) cell size and was created from LiDAR data representing beach topography and sonar data representing bathymetry to a distance of approximately 1.3 kilometers (0.8 miles) offshore. LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and methodology similar to that described by Huizinga and Wagner (2019). Multi-beam sonar data were collected August 7-11, 2019 using an R2Sonic 2024 sonar unit and methodology similar to that described...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry and Elevation,
DEM,
Duluth,
Great Lakes,
Hydroacoustic,
The RVCAT database contains data that have been collected on various vessel operations on the Great Lakes and select connecting waterways. This section of Reference Tables specifically handles repetitive or standardized information that is called upon in the main tables of the RVCAT database. Reference tables are used in database design in order to standardize often used values and to make the data file efficient. All of the terms defined in the reference tables have been determined by the United States Geological Survey, Great Lakes Science Center and it’s partners. Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being...
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