Hyperspectral image data and field measurements used for bathymetric mapping of the Snake River in Grand Teton National Park, WY
June 8, 2018
Hyperspectral image data and various field measurements were acquired from a reach of the Snake River in Grand Teton National Park, WY, August 19-24, 2015, to support research on remote sensing of rivers. This parent data release includes links to child pages for the following data sets: 1) hyperspectral image data; 2) ground-based depth measurements obtained by wading and with with an acoustic Doppler current profiler; 3) reflectance spectra acquired from a raft; and 4) an irradiance profile used to characterize attenuation of light by the water column. Please refer to the individual child pages for further detail about each data set. Overall, these data were used to develop improved methods of estimating water depth from remotely sensed data.
Citation Information
Publication Year | 2018 |
---|---|
Title | Hyperspectral image data and field measurements used for bathymetric mapping of the Snake River in Grand Teton National Park, WY |
DOI | 10.5066/F7D50KX6 |
Authors | Carl J Legleiter, Brandon T Overstreet |
Product Type | Data Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | National Research Program |
Rights | This work is marked with CC0 1.0 Universal |
Related
Sampling strategies to improve passive optical remote sensing of river bathymetry
Passive optical remote sensing of river bathymetry involves establishing a relation between depth and reflectance that can be applied throughout an image to produce a depth map. Building upon the Optimal Band Ratio Analysis (OBRA) framework, we introduce sampling strategies for constructing calibration data sets that lead to strong relationships between an image-derived quantity and...
Authors
Carl J. Legleiter, Brandon Overstreet, Paul J. Kinzel
Related
Sampling strategies to improve passive optical remote sensing of river bathymetry
Passive optical remote sensing of river bathymetry involves establishing a relation between depth and reflectance that can be applied throughout an image to produce a depth map. Building upon the Optimal Band Ratio Analysis (OBRA) framework, we introduce sampling strategies for constructing calibration data sets that lead to strong relationships between an image-derived quantity and...
Authors
Carl J. Legleiter, Brandon Overstreet, Paul J. Kinzel