Automated extraction of beach bathymetries from video images

Laura Uunk

MSc Thesis

prof. dr. S.J.M.H. Hulscher

dr. K.M.Wijnberg

ir. R. Morelissen

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Contents

Beach bathymetries by shoreline mapping

Manually mapping shorelines (IBM)

Automatically mapping shorelines (ASM)

Problems encountered

Automated quality control

Automatically vs. manually obtained bathymetries

Beach behaviour

Conclusions

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Beach bathymetries by shoreline mapping

Argus images• Time exposure images

10 minute average• Every half hour

Beach bathymetry mapped• Shoreline location• Shoreline elevation• Throughout tidal cycle • Elevation data between

low and high waterTimex image of Egmond Coast 3D site, camera 1

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Manually mapping shorelines (IBM)

Interface of the Intertidal Beach Mapper (IBM)

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Manually mapping shorelines (IBM)

Requires many man-hours

• up to 4 hours for one day for one station (5 cameras)

Therefore no daily bathymetries, but monthly

Opportunities of Argus not completely used

Automated version was developed (ASM)

• Plant

• Cerezo and Harley Dutch beach

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Automatically mapping shorelines (ASM)

Human steps are automated

• Definition of the region of interest> based on expected shoreline

location on bench-mark bathymetry

• Quality control> compare detected points

against bench-mark bathymetry

Bench-mark bathymetry

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Automatically mapping shorelines (ASM)

Database withshoreline points

Shoreline pointswithin time window

Bench-mark bathymetry Shoreline elevation

Region of interest

Detected shoreline points

Acceptedshoreline points

Acceptance criterion

Detection method

Elevation model

start / next time step

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Problems encountered

Bad bench-mark bathymetry> bad definition ROI> bad quality control

Start of a downward spiral

Bad bench mark bathymetry

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Problems encountered - downward spiral

Database withshoreline points

Shoreline pointswithin time window

Bench-mark bathymetry Shoreline elevation

Region of interest

Detected shoreline points

Acceptedshoreline points

Acceptance criterion

Detection method

Elevation model

start / next time step

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Problems encountered - solutions

Better definition of the Region of Interest

• large smoothing scales loess interpolation> better expected shoreline location

• extension to edge of image> inclusion of entire shoreline

• avoid zigzagging> inclusion of entire shoreline

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Problems encountered - solutions

Better expected shoreline location

larger smoothing scales

longer time window

small smoothing scales

short time window

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Problems encountered - solutions

Better definition of the Region of Interest

• large smoothing scales loess interpolation> better expected shoreline location

• extension to edge of image> inclusion of entire shoreline

• avoid zigzagging> inclusion of entire shoreline

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Problems encountered - solutions

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Problems encountered - solutions

Double quality control

• Two bench-mark bathymetries> 1: small smoothing scales, small time window> 2: large smoothing scales, large time window

Shoreline points first compared to first bathymetryPoints that could not be checked are then compared to

second bathymetry

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Problems encountered - solutions

small smoothing scale more detail more gaps

large smoothing scale less detail less gaps

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Automated quality control

Fixed vertical criterion: Zdif

• Sometimes accept points that are wrong

• Sometimes reject points that are good

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Automated quality control

What value should be used?

ASM was run with three values for Zdif

• 0.10 m;

• 0.25 m;

• 0.50 m

ASM bathymetries compared to IBM bathymetries

• Coastal State Indicators (CSIs)> Contours (-0.50 m NAP; 0 m NAP; 0.50 m NAP)> MICL

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Automated vs. manual

0 m contour for May 7th to 12th 2006

IBM 0.10 m 0.25 m 0.50 m continued 0.25 m

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Automated vs. manual

0.10 m 0.25 m 0.50 m continued 0.25 m

No real differences for the different values of Zdif

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Automated vs. manual – in time

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Beach behaviour

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Conclusions

• Man-hours are saved by automatically mapping shorelines• Results automated version (ASM) correspond well with results

manual version (IBM)• 0 m contour by ASM shows immediate response of the beach to

changes in wave height

• this was not visible with monthly IBM bathymetries• Opportunities provided by half-hourly Argus images can now be

fully exploited• ASM data could be used to e.g.

• study storm impact

• study influence of nourishments

• support management decisions

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Questions