Paper
4 May 2011 Merging imagery and models for river current prediction
Cheryl Ann Blain, Robert S. Linzell, Paul McKay
Author Affiliations +
Abstract
To meet the challenge of operating in river environments with denied access and to improve the riverine intelligence available to the warfighter, advanced high resolution river circulation models are combined with remote sensing feature extraction algorithms to produce a predictive capability for currents and water levels in rivers where a priori knowledge of the river environment is limited. A River Simulation Tool (RST) is developed to facilitate the rapid configuration of a river model. River geometry is extracted from the automated processing of available imagery while minimal user input is collected to complete the parameter and forcing specifications necessary to configure a river model. Contingencies within the RST accommodate missing data such as a lack of water depth information and allow for ensemble computations. Successful application of the RST to river environments is demonstrated for the Snohomish River, WA. Modeled currents compare favorably to in-situ currents reinforcing the value of the developed approach.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cheryl Ann Blain, Robert S. Linzell, and Paul McKay "Merging imagery and models for river current prediction", Proc. SPIE 8030, Ocean Sensing and Monitoring III, 80300H (4 May 2011); https://doi.org/10.1117/12.884100
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image processing

Coastal modeling

Data modeling

Image segmentation

Data processing

Edge detection

Human-machine interfaces

RELATED CONTENT


Back to Top