An unmanned aerial system (UAS) was used to acquire red/green/blue (RGB) and hyperspectral image data from the American River in California November 5-7, 2018, to support research on remote sensing of rivers, specifically mapping salmon spawning locations (redds) as part of an overall salmon habitat assessment program. The RGB images were acquired uisng a DJI MAtrice 210 equipped with a Zenmuse 4S optical camera. Imagery was collected along several parallel flight lines to ensure full coverage of the study reach. Raw Zenmuse images were georeferenced using real-time kinematic (RTK) global positioning system (GPS) and inertial motion unit (IMU) data recorded onboard the UAS and individual flight strips were combined into an orthorectified mosaic using Agisoft Metashape. The resulting orthoimage had a pixel size of 0.15 m. The georeferenced RGB ortho-image had accurate image coregistration with surveyed ground control targets used as checkpoints. The hyperspectral data were collected by the Nano-Hyperspec imaging system, manufactured by Headwall Photonics, Inc. The flight was conducted by the NOAA Southwest Fisheries Science Center and colleagues from the University of California Santa Barbara who also performed the initial radiometric and geometric data processing. The data were acquired from a DJI Matrice M600 UAS and have a spatial resolution (pixel size) of 0.15 m. The data set consists of 252 spectral bands spanning the visible and near infrared wavelength range from 398 - 956 nanometers. Reflectance retrieval was performed using a calibration tarp as an in-scene white reference. The image pixel values represent reflectances and are stored as floating point 32-bit single precision numbers. The image data file has a band sequential (BSQ) interleave and is in an ENVI-compatible file format with an associated header (*.hdr) text file. The initial hyperspectral ortho-image had poor alignment with field-surveyed ground control points (GCPs) and required additional georeferencing to improve horizontal accuracy. We used ENVI software tools to perform image-to-image registration using the RGB ortho-image as the base image and the hyperspectral image as the warp image. Following this initial radiometric and geometric processing, the hyperspectral ortho-mosaic was masked to include only the water area within the river channel. The images provided in this data release is focuses on the reach of the American River immediarely below Nimbus Dam. Supporting field data from this reach were collected in coordination with the acquisition of the remotely sensed data.

This child data release includes field spectra obtained as part of a study focused on mapping salmon spawning locations along the American River near Sacramento, California, via remote sensing; the data were collected November 5-7, 2018. The purpose of this study was to develop and test a spectrally based technique for identifying salmon spawning locations, known as redds, from various types of remotely sensed data. Traditionally, redds have been mapped by eye while walking the bank or from a boat, or by an observer in an aircraft or an interpreter visually examining aerial images. The goal of this proof-of-concept investigation was to assess the potential for more efficient, objective, and automated redd mapping from conventional true color (RGB, or red/green/blue) and hyperspectral images. The field spectra were recorded from above the water surface at redds mapped in the field using an ASD HandHeld2 Pro spectroradiometer in reflectance mode, with periodic measurements from a Spectralon panel serving as the white reference. For each redd location, spectra were recorded for the pot and tail of each redd and the adjacent undisturbed substrate. The data consist of reflectance measurements over the wavelength range from 325 to 1075 nm, along with the spatial coordinates and water depth for the redd. Field spectra from 20 redds are compiled in a single file, ReddSpectra.csv, and organized by redd, with a pot, tail, and undisturbed spectrum from each redd. The file also includes colums for the easting and northing spatial coordinates, bed elevations, and water depths. The reflectance at each wavelength from 325 to 1075 nm is given in a separate column of the file. No post-processing of the raw spectra measured in the field was performed. These data were used to assess the potential for identifying salmon spawning locations from various types of remotely sensed data.

This child data release includes field spectra obtained as part of a study focused on mapping salmon spawning locations along the American River near Sacramento, California, via remote sensing; the data were collected November 5-7, 2018. The purpose of this study was to develop and test a spectrally based technique for identifying salmon spawning locations, known as redds, from various types of remotely sensed data. Traditionally, redds have been mapped by eye while walking the bank or from a boat, or by an observer in an aircraft or an interpreter visually examining aerial images. The goal of this proof-of-concept investigation was to assess the potential for more efficient, objective, and automated redd mapping from conventional true color (RGB, or red/green/blue) and hyperspectral images. The field spectra were recorded from above the water surface at redds mapped in the field using an ASD HandHeld2 Pro spectroradiometer in reflectance mode, with periodic measurements from a Spectralon panel serving as the white reference. For each redd location, spectra were recorded for the pot and tail of each redd and the adjacent undisturbed substrate. The data consist of reflectance measurements over the wavelength range from 325 to 1075 nm, along with the spatial coordinates and water depth for the redd. Field spectra from 20 redds are compiled in a single file, ReddSpectra.csv, and organized by redd, with a pot, tail, and undisturbed spectrum from each redd. The file also includes colums for the easting and northing spatial coordinates, bed elevations, and water depths. The reflectance at each wavelength from 325 to 1075 nm is given in a separate column of the file. No post-processing of the raw spectra measured in the field was performed. These data were used to assess the potential for identifying salmon spawning locations from various types of remotely sensed data.

This data release includes images and field measurements used to map salmon spawning locations along the American River near Sacramento, California, via remote sensing; the data were collected November 5-7, 2018. The purpose of this study was to develop and test a spectrally based technique for identifying salmon spawning locations, known as redds, from various types of remotely sensed data. Traditionally, redds have been mapped by eye while walking the bank or from a boat, or by an observer in an aircraft or an interpreter visually examining aerial images. The goal of this proof-of-concept investigation was to assess the potential for more efficient, objective, and automated redd mapping from conventional true color (RGB, or red/green/blue) and hyperspectral images. This child page provides redd locations mapped in the field, with their coordinates defined by surveying the redd centers with real-time kinematic (RTK) GPS receivers. The field-mapped redds were used to train and validate various image-based approaches to mapping salmon spawning locations.

This data release includes images and field measurements used to map salmon spawning locations along the American River near Sacramento, California, via remote sensing; the data were collected November 5-7, 2018. The purpose of this study was to develop and test a spectrally based technique for identifying salmon spawning locations, known as redds, from various types of remotely sensed data. Traditionally, redds have been mapped by eye while walking the bank or from a boat, or by an observer in an aircraft or an interpreter visually examining aerial images. The goal of this proof-of-concept investigation was to assess the potential for more efficient, objective, and automated redd mapping from conventional true color (RGB, or red/green/blue) and hyperspectral images. This child page provides redd locations mapped in the field, with their coordinates defined by surveying the redd centers with real-time kinematic (RTK) GPS receivers. The field-mapped redds were used to train and validate various image-based approaches to mapping salmon spawning locations.

An unmanned aerial system was used to acquire hyperspectral image data from the upper Sacramento River in northern California on September 13, 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 Nano-Hyperspec imaging system, manufactured by Headwall Photonics, Inc. The flight was conducted by Headwall Photonics, Inc.; Headwall also performed the initial radiometric and geometric data processing. The data were acquired from a DJI Matrice M600 UAS and have a spatial resolution (pixel size) of 0.178 m. The data set consists of 276 spectral bands spanning the visible and near infrared wavelength range from 396.025 - 1005.09 nanometers. Reflectance retrieval was performed by Headwall using their SpectralView software package. The image pixel values represent reflectances and are stored as floating point 32-bit single precision numbers. The image data file has a band sequential (BSQ) interleave and is in an ENVI-compatible file format with an associated header (*.hdr) text file. The image provided in this data release is focuses 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.

An unmanned aerial system was used to acquire hyperspectral image data from the upper Sacramento River in northern California on September 13, 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 Nano-Hyperspec imaging system, manufactured by Headwall Photonics, Inc. The flight was conducted by Headwall Photonics, Inc.; Headwall also performed the initial radiometric and geometric data processing. The data were acquired from a DJI Matrice M600 UAS and have a spatial resolution (pixel size) of 0.178 m. The data set consists of 276 spectral bands spanning the visible and near infrared wavelength range from 396.025 - 1005.09 nanometers. Reflectance retrieval was performed by Headwall using their SpectralView software package. The image pixel values represent reflectances and are stored as floating point 32-bit single precision numbers. The image data file has a band sequential (BSQ) interleave and is in an ENVI-compatible file format with an associated header (*.hdr) text file. The image provided in this data release is focuses 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.

Airborne hyperspectral image data from the upper Sacramento River in northern California were acquired on September 14, 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 Compact Airborne Spectrographic Imager (CASI) 1500H, manufactured by ITRES Research Limited. The flight was conducted by Quantum Spatial, Inc. (QSI); QSI also performed the initial radiometric and geometric data processing. The data were acquired from fixed wing aircraft and have a spatial resolution (pixel sizes) of 0.5 m. The data set consists of 48 spectral bands spanning the visible and near infrared wavelength range from 0.373 - 1.043 micrometers. Atmospheric correction and reflectance retrieval were performed by QSI using the ATCOR4 software package. The image pixel values represent reflectance with a scale factor of 10,000 and are stored as 16-bit signed integers. The image data file has a band sequential (BSQ) interleave and is in an ENVI-compatible *.bsq file format with an associated header (*.hdr) text file. 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.

Salmon spawning locations (redds) were mapped to characterize habitat use along two reaches of the lower Merced River in California's Central Valley and thus support research intended to evaluate the extent to which large-scale restoration projects provided improved salmon spawning habitat. A related goal of this study was to improve our understanding of the geomorphic factors influencing spawning site selection by salmon. Salmon redds were mapped during the fall of 2016 at the Merced River Ranch and Robinson Reach field sites using real-time kinematic (RTK) GPS. The location of the center of each redd was surveyed in the UTM Zone 10/NAD83 coordinate system, with easting and northing coordinates recorded in units of meters.

Salmon spawning locations (redds) were mapped to characterize habitat use along two reaches of the lower Merced River in California's Central Valley and thus support research intended to evaluate the extent to which large-scale restoration projects provided improved salmon spawning habitat. A related goal of this study was to improve our understanding of the geomorphic factors influencing spawning site selection by salmon. Salmon redds were mapped during the fall of 2016 at the Merced River Ranch and Robinson Reach field sites using real-time kinematic (RTK) GPS. The location of the center of each redd was surveyed in the UTM Zone 10/NAD83 coordinate system, with easting and northing coordinates recorded in units of meters.