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Topo-bathymetric digital elevation models of the upper Merced and Tuolumne Rivers in California derived from hyperspectral image data and near-infrared LiDAR acquired in 2014

Metadata Updated: July 6, 2024

This child data release includes fused topo-bathymetric digital elevation models of the Merced and Tuolumne Rivers in California used to support research on anadromous salmonids. The purpose of this study was to calculate the capacity for reintroduction of salmonids above impassable barriers. Airborne, near-infrared (NIR) LiDAR and hyperspectral imagery were acquired simultaneously in September 2014 from a Cessna Caravan, with the LiDAR data used to map topography of dry land and the imagery used to map water depth in the wetted channel. Topo-bathymetric DEMs of channels and floodplains with 1-m resolution were constructed for the study reaches by using remotely sensed hyperspectral image data to estimate water depths within the below-water portion of the channel and using remotely-sensed LiDAR for the above-water portion of the channel. Water depths were subtracted from water-surface elevations measured by the LiDAR to obtain bed elevations within the wetted channel.
The digital elevation model above the water surface was created using the LiDAR data. We used a Leica Airborne Laser Scanner ALS50, with mean point densities >12 points/m2 and reported horizontal and vertical accuracies of 2 cm and 7 cm, respectively. The raw LiDAR point cloud was processed into bare-earth DEMs with 1 m grid cells. The digital elevation model for areas below the water surface was created using the hyperspectral imagery. Hyperspectral imagery was collected using a Compact Airborne Spectographic Imager (CASI) 1500 (ITRES 2014), producing imagery with 48 spectral bands (wavelengths 380 to 1050 nm). Raw image flight strips were geometrically and radiometrically corrected with ITRES software, then atmospherically corrected using ATCOR4 (ReSe 2014). The final images were in units of reflectance for each band, with a spatial resolution of 0.5 m. Water depths were estimated from the imagery using the Optimal Band Ratio Analysis (OBRA) depth retrieval algorithm, a calibration technique that relates field-measured water depths (d) to an image-derived quantity defined as the natural logarithm of the ratio of two spectral bands (Legleiter et al. 2009).

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Maintainer
@Id http://datainventory.doi.gov/id/dataset/a490701b9daaea082d664e1799bc6879
Identifier USGS:5f861c8e82cebef40f14c750
Data Last Modified 20210923
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 00cc2d59-eb4a-412d-8829-94f39262f0d8
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -120.5228,37.4203,-118.9847,38.1086
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash 264285b04f6060b4ba78ec288ae7ef02b93141985d87198985bce825532c9fa5
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -120.5228, 37.4203, -120.5228, 38.1086, -118.9847, 38.1086, -118.9847, 37.4203, -120.5228, 37.4203}

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