New Toolbox will aid in remotely sensing river bathymetry
USGS Scientist and SurfBoard member, Carl Legleiter has release a new toolset for processing multi-spectral imagery of shallow rivers. The Optical River Bathymetry Toolkit, ORByT, is an publicly available application to facilitate mapping water depth in river channels from passive optical image data. ORByT provides an integrated workflow for image processing, depth retrieval, and export of results.
Carl has done an excellent job of building a nice code base over on the USGS Gitlab, and you can download the Toolkit, documentation, and training here:
There is even a DOI Talent self-lead course (this is available to DOI employees only) on the usage of the Toolkit:
Legleiter, C.J., 2020, ORByT - Optical River Bathymetry Toolkit (ver. 1.1, June, 2020): U.S. Geological software release, https://doi.org/10.5066/P9GXRJ3K.
Poster Session: Community for Data Integration Workshop
Boulder, Colorado June 3–7, 2019
Thanks for your interest in our poster! Here you can download a copy of the poster, see links on how you can get more information on our IoT project, or directly interact with the USGS Surfboard. Also, be sure to comment on this blog post if you have questions or comments! The SurfBoard is striving to serve the USGS the best we can, and the more interaction with users in interested folks like you we get, the better.
The USGS Surface Velocity Workgroup (SurfBoard) is developing and testing computerized video-based approaches to measuring streamflow during floods from video-derived stream velocities (image velocimetry). Often, hydrographers cannot safely capture flood streamflow data at streamgages during the event because of dangerous site conditions or event timing. Image velocimetry offers a solution to this need for measurement of flood streamflows because it allows hydrographers to measure streamflow remotely. To this aim, the SurfBoard has partnered with USGS Cloud Hosting Solutions to develop an Internet of Things (IoT) provisioned image velocity streamgage that applies existing equipment and processing elements to edge computing using the Amazon Web Services (AWS) IoT and GreenGrass Core software. The work has two objectives:
- Prepare and test an IoT framework that replicates the existing image streamgage workflows in the AWS cloud.
- Translate selected existing processing algorithms into cloud-based programs (AWS Lambda functions) within the IoT framework.
Insights gained are being used to build a decision matrix aimed at leveraging IoT applications for other streamgages and sensors in the network. Image velocimetry measurements using an IoT approach are being tested at 2 gages. Initial development and testing results have been promising.
John Parks, USGS Office of Enterprise Information
Jennifer Erxleben, USGS Cloud Hosting Solutions
Jay Cederberg, USGS Arizona Water Science Center
This information is preliminary and is subject to revision. It is being provided to meet the need for timely best science. The information is provided on the condition that neither the U.S. Geological Survey nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the information.
Full Proposal Narrative
More information about...
- The Surfboard and what we do
- Surface Velocity Gaging concepts for image velocimetry and continuous Doppler velocity radar
- Our work with CDI
- Forums for surface velocity general discussion and software help, and idea sharing (requires registration)
- Why does this poster look strange? Check out this video on improving the poster UX: