데이터셋 상세
미국
Bathymetric LiDAR data from the upper Sacramento River in northern California, September 10-17, 2017
Bathymetric LiDAR data from the upper Sacramento River in northern California were acquired September 10-17, 2017, to support research on remote sensing of rivers, particularly mapping water depth, and to facilitate efforts to characterize salmon habitat conditions and geomorphic change along the upper Sacramento River. These data were collected using a Riefl VQ-880-Gairborne laser scanning system designed for combined hydrographic and topographic surveying. The flight was conducted by Quantum Spatial, Inc. (QSI); QSI also performed all processing of the raw LiDAR data. The data were acquired from fixed wing aircraft and were used to produce tiled point clouds in a .las format and interpolated topo-bathymetric raster Digital Elevation Models (DEM's) with a 1 m cell size in an Arc GRID format. The rasters provided in this data release are subsets focused on the reach of the Sacramento River where it is joined by its tributary Cottonwood Creek; supporting field data from this reach were collected in coordination with the acquisition of the remotely sensed data. Three files based on the LiDAR coverage are included in this data release: 1) a topographic DEM with water surface elevations in the channel; 2) a bathymetric DEM with channel bed elevations; and 3) a depth map produced by subtracting the bathymetric DEM from the topographic DEM to calculate the depth as the difference between the water surface elevation and the bed elevation. These data sets are provided as ENVI format files with associated header files.
데이터 정보
연관 데이터
Multispectral satellite image data from the upper Sacramento River in northern California, October 18, 2017
공공데이터포털
Multispectral satellite image data from the upper Sacramento River in northern California were acquired on October 18, 2017, to support research on remote sensing of rivers, particularly retrieval of water depth, and to facilitate efforts to characterize salmon habitat conditions and geomorphic change along the upper Sacramento River. These data were collected by the WorldView-3 (WV3) satellite, operated by DigitalGlobe and obtained through the EnhancedView license program administered by the National Geospatial-Intelligence Agency (NGA); the image data remain copyright of DigitalGlobe (2018). DigitalGlobe performed initial radiometric and geometric processing of the image. The data were acquired from the WorldView-3 satellite from an orbit with an altitude of 617 km and have a spatial resolution (pixel size) of 1.36 m. The data set consists of 8 spectral bands spanning the visible and near infrared wavelength range from 400-954 nanometers. The image pixel values represent raw digital counts and conversion to radiance, atmospheric correction, and reflectance retrieval have not been performed for the image included in this data release. The image is in a GeoTIFF format with pixel values stored as 16-bit unsigned integers. The image provided in this data release is a subset focused on the reach of the Sacramento River where it is joined by its tributary Cottonwood Creek. Supporting field data from this reach were collected in coordination with the acquisition of the remotely sensed data.
Swath bathymetric data from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
공공데이터포털
This part of the data release contains high-resolution swath bathymetry data collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, Middle River in March 2018, and Mokelumne River in March 2018 using an interferometric bathymetric sidescan sonar systems mounted to the USGS R/V Parke Snavely. Data are provided in 1-m resolution GeoTIFF formats. These data were collected as part of a study on the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta.
Swath bathymetric data from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
공공데이터포털
This part of the data release contains high-resolution swath bathymetry data collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, Middle River in March 2018, and Mokelumne River in March 2018 using an interferometric bathymetric sidescan sonar systems mounted to the USGS R/V Parke Snavely. Data are provided in 1-m resolution GeoTIFF formats. These data were collected as part of a study on the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta.
Bathymetric lidar data from the Colorado River, near Lees Ferry, Arizona, September 23, 2019
공공데이터포털
The U.S. Geological Survey contracted with Juniper Unmanned to conduct field tests of the ASTRALiTe bathymetric lidar system on the Colorado River near Lees Ferry, Arizona, on September 23, 2019. The objective of this project was to assess the potential to map river bathymetry (i.e., channel bed topography) using lidar data. The ASTRALiTe lidar instrument was mounted on a cataraft owned and operated by USGS Grand Canyon Monitoring and Research Center. This data release includes data delivered to the USGS by ASTRALite on November 1, 2019. The data are in *txt format and include bare earth (i.e., river bed) and water surface returns and have not been filtered or modified in any other way.
Bathymetry data collected in 2008 offshore Tijuana River Estuary, California during USGS Field Activity S-5-08-SC
공공데이터포털
These metadata describe bathymetry data collected during a 2008 SWATHPlus-M survey offshore Tijuana River Estuary, California. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number S-5-08-SC. The bathymetry data are provided as GeoTIFF images in UTM, zone 11, NAD83 coordinates, vertically referenced to both NAVD88 and WGS84. A standard deviation grid is also provided.
Bathymetry data collected in 2008 offshore Tijuana River Estuary, California during USGS Field Activity S-5-08-SC
공공데이터포털
These metadata describe bathymetry data collected during a 2008 SWATHPlus-M survey offshore Tijuana River Estuary, California. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number S-5-08-SC. The bathymetry data are provided as GeoTIFF images in UTM, zone 11, NAD83 coordinates, vertically referenced to both NAVD88 and WGS84. A standard deviation grid is also provided.
Bathymetric lidar data from the Blue River, Colorado, October 18, 2018
공공데이터포털
The U.S. Geological Survey contracted with Juniper Unmanned to conduct field tests of the ASTRALiTe bathymetric lidar system on the Blue River just upstream of its confluence with the Colorado River near Kremmling, Colorado, on October 18, 2018. The objective of this project was to assess the potential to map river bathymetry (i.e., channel bed topography) using lidar data collected from an unmanned aircraft system (UAS). The ASTRALiTe lidar instrument was mounted on a DJI Matrice 600 Pro UAS owned and operated by Juniper Unmanned. As part of the study, Juniper's pilot flew the ASTRALiTe instrument across 2 river transects (cross-stream) on the Blue River. This data release includes data delivered to the USGS by ASTRALite on November 15, 2018. The data have been parsed into separate text files for bare earth (i.e., river bed) and water surface returns for each cross-section but have not been filtered or modified in any other way.
Bathymetric lidar data from the Colorado River, near Parshall, Colorado, June 13, 2019
공공데이터포털
The U.S. Geological Survey contracted with Juniper Unmanned to conduct field tests of the ASTRALiTe bathymetric lidar system on the Colorado River near Parshall, Colorado, on June 13, 2019. The objective of this project was to assess the potential to map river bathymetry (i.e., channel bed topography) using lidar data collected from an unmanned aircraft system (UAS). The ASTRALiTe lidar instrument was mounted on a DJI Matrice 600 Pro UAS owned and operated by Juniper Unmanned. As part of the study, Juniper's pilot flew the ASTRALiTe instrument across 2 river transects (cross-stream) on the Colorado River. This data release includes data delivered to the USGS by ASTRALite on August 1, 2019. The data have been parsed into separate text files for bare earth (i.e., river bed) and water surface returns for each cross-section but have not been filtered or modified in any other way.
Bathymetric change analyses of the Sacramento River near Rio Vista, California, and the junction of Cache and Steamboat sloughs, from 1992 to 2004
공공데이터포털
Bathymetric change grids covering the periods of time from 1992 to 1998 and from 1994 to 2004 are presented. The grids cover a portion of the Sacramento River near Rio Vista, California, extending partially upstream on Cache and Steamboat sloughs by the Ryer Island Ferry, as well as continuing up the Sacramento River towards Isleton. Positive grid values indicate accretion, or a shallowing of the surface bathymetric surface, and negative grid values indicate erosion, or a deepening of the bathymetric surface. Bathymetry data sources include the U.S. Army Corps of Engineers, California Department of Water Resources, and NOAA’s National Ocean Service.
Bathymetry data for Jenkinson Lake, California collected during USGS field activity 2023-634-FA
공공데이터포털
Here July 2023 1-m resolution bathymetry data of Jenkinson Lake, California are provided for the entire lake and 0.5-m resolution bathymetry data are provided for the shallower upper basin. Bathymetry data were collected during three separate SWATHPlus surveys of Jenkinson Lake. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity numbers 2022-604-FA (January 2022), 2022-649-FA (August 2022), and 2023-634-FA (July 2023). Data are provided as GeoTIFF images.