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| Titel |
Technical Note: Semi-automated effective width extraction from time-lapse RGB imagery of a remote, braided Greenlandic river |
| VerfasserIn |
C. J. Gleason, L. C. Smith, D. C. Finnegan, A. L. LeWinter, L. H. Pitcher, V. W. Chu |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 6 ; Nr. 19, no. 6 (2015-06-26), S.2963-2969 |
| Datensatznummer |
250120754
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| Publikation (Nr.) |
 copernicus.org/hess-19-2963-2015.pdf |
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| Zusammenfassung |
| River systems in remote environments are often challenging to monitor and
understand where traditional gauging apparatus are difficult to install or
where safety concerns prohibit field measurements. In such cases, remote
sensing, especially terrestrial time-lapse imaging platforms, offer a means
to better understand these fluvial systems. One such environment is found at
the proglacial Isortoq River in southwestern Greenland, a river with a
constantly shifting floodplain and remote Arctic location that make gauging
and in situ measurements all but impossible. In order to derive relevant
hydraulic parameters for this river, two true color (RGB) cameras were
installed in July 2011, and these cameras collected over 10 000 half hourly
time-lapse images of the river by September of 2012. Existing approaches for
extracting hydraulic parameters from RGB imagery require manual or supervised
classification of images into water and non-water areas, a task that was
impractical for the volume of data in this study. As such, automated image
filters were developed that removed images with environmental obstacles
(e.g., shadows, sun glint, snow) from the processing stream. Further image
filtering was accomplished via a novel automated histogram similarity
filtering process. This similarity filtering allowed successful (mean
accuracy 79.6 %) supervised classification of filtered images from
training data collected from just 10 % of those images. Effective width,
a hydraulic parameter highly correlated with discharge in braided rivers, was
extracted from these classified images, producing a hydrograph proxy for the
Isortoq River between 2011 and 2012. This hydrograph proxy shows agreement
with historic flooding observed in other parts of Greenland in July 2012 and
offers promise that the imaging platform and processing methodology presented
here will be useful for future monitoring studies of remote rivers. |
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