Automated monitoring of river ice processes using shore-based imagery

Automated monitoring of river ice processes using shore-based imagery River hydraulics is drastically influenced by the presence of river ice, which inevitably occurs in cold regions. Terrestrial monitoring of river ice, using a time-lapse camera system on the Lower Nelson River, northern Manitoba, Canada, was conducted for a comprehensive study of the effects of river ice cover on hydraulic characteristics. An automated image processing algorithm was developed to analyze the time series of terrestrial images. The presented image processing algorithm consists of five main steps: preprocessing, image registration, geo-rectification, target detection and final quantitative river ice cover calculations. The developed algorithm was able to detect and quantify important river ice cover characteristics such as the percentage of area covered by ice, the location of the leading edge, and the speed of border ice growth and recession. Potentially, these observations may be used to improve the ice formation and break-up algorithms in river ice models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Cold Regions Science and Technology Elsevier

Automated monitoring of river ice processes using shore-based imagery

Loading next page...
 
/lp/elsevier/automated-monitoring-of-river-ice-processes-using-shore-based-imagery-RdPCGc0KPj
Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier B.V.
ISSN
0165-232X
D.O.I.
10.1016/j.coldregions.2017.06.011
Publisher site
See Article on Publisher Site

Abstract

River hydraulics is drastically influenced by the presence of river ice, which inevitably occurs in cold regions. Terrestrial monitoring of river ice, using a time-lapse camera system on the Lower Nelson River, northern Manitoba, Canada, was conducted for a comprehensive study of the effects of river ice cover on hydraulic characteristics. An automated image processing algorithm was developed to analyze the time series of terrestrial images. The presented image processing algorithm consists of five main steps: preprocessing, image registration, geo-rectification, target detection and final quantitative river ice cover calculations. The developed algorithm was able to detect and quantify important river ice cover characteristics such as the percentage of area covered by ice, the location of the leading edge, and the speed of border ice growth and recession. Potentially, these observations may be used to improve the ice formation and break-up algorithms in river ice models.

Journal

Cold Regions Science and TechnologyElsevier

Published: Oct 1, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off