This project is carried our in the frame of KPP-CIP projects in 2018 and 2019. The project KPPCIP2018 IV INNO Satellieten en bathymetrie voor monitoring kustmorfologie proposed by Deltares has been awarded by Rijkswaterstaat in November 2017.


< 2020 2019

Introduction

Within this project, Deltares was asked to look at available satellite images in the period 2015-2017 and explore ways to derive bathymetry from those images. Eventually Deltares provided a calibrated bathymetry for two areas of interest and compared the obtained bathymetry with in-situ data collected via standard measurement methods.

2018


Areas of interest

The two areas are both located in the North Sea area: the inlet of Ameland island in the Wadden Sea and the Western Scheldt outerdelta. These areas are characterised by active coastal morphodynamics, especially in the shallow waters. The use of remote sensing images for these areas helps to capture higher frequency dynamics, too costly and spatially confined to be fully detected by standard in-situ measurements.

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Data availability

As a rich data country, The Netherlands is monitoring its 350 km of coast at a yearly rate. For the purpose of his study, several datasets of measurement observations are explored, analysed, and compared against remote sensing products. Here is a list of data used during the project.

In-situ data

Water levels Google Earth Engine code which imports shapefiles of water level data, and displays the locations of the buoys and plots a subset of this data.

Jarkus transects

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Jarkus transects for the a) Westerschelde and b) Ameland regions.

RWS Vaklodingen Data

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Vaklodingen data for the a) Westerschelde and b) Ameland regions. A total of 90 Vaklodingen images, measured annually, between 2010 and 2015 are combined to create a mosaic of bathymetry along the Dutch coastline.

Remote sensing data

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Examples of cloud-free satellite imagery of a) the Westerchelde and b) Ameland.

For this analysis, we have used Sentinel 2 and Landsat imagery up to present day. A sample of cloud-free satellite imagery from Sentinel 2 available for the regions of interest are displayed above.

Additional data

Methodology

With Google Earth Engine, images from Sentinel 2 and Landsat 8 available up to present day are used for analysis. This image collection is sorted by cloud cover, and the percentage of images filtered based on the annual cloud coverage for the regions (~66% for the Netherlands).

More information on the methodology available in this poster, presented at EGU.

Results

Bathymetry from Space, Wadenzee (2013-2018) from Gennadii Donchyts on Vimeo.

Validation and Comparison

Water levels

hi Water level measurements plotted in gray have been derived from a buoy off the coast of Nes, The Netherlands (5.7609, 53.4311). Corresponding cloud-free (<15% coverage) images between 2015 to the present from Landsat 8 and Sentinel 2 are plotted in red and blue, respectively. These images were then sorted by water level from in-situ Matroos data. Location in the Netherlands, along the North Sea (6.20, 53.41). The movies below provide a visualization of the intertidal zone and waterlevel changes within Ameland region.

False colour L8 and S2 sorted by water level from Christine Rogers on Vimeo.

False colour Landsat 8 and Sentinel 2 images, sorted by water levels recorded at Nes buoy.

RGB L8 and S2 sorted by water level from Christine Rogers on Vimeo.

RGB Landsat 8 and Sentinel 2 images, sorted by water levels recorded at Nes buoy.

Code which creates and exports above videos.

Jarkus transects


Transect 3002500

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Jarkus transect #3002500 and region selected for analysis. Region centered at (5.97, 53.46).

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Comparison of bathymetry from Jarkus transect #3002500 (z), Vaklodingen, and inverse-depth in selected region for analysis.


Transect 3000720

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Jarkus transect #3000720 and region selected for analysis. Region centered at (5.68, 53.47).

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Comparison of bathymetry from Jarkus transect #33000720 (z), Vaklodingen, and inverse-depth in selected region for analysis.


Transect 4005903

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Jarkus transect #4005903 and region selected for analysis. Region centered at (5.16, 53.35).

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Comparison of bathymetry from Jarkus transect #4005903 (z), Vaklodingen, and inverse-depth in selected region for analysis.


Transect 17000071

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Jarkus transect #17000071 and region selected for analysis. Region centered at (3.56, 51.40).

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Comparison of bathymetry from Jarkus transect #17000071 (z), Vaklodingen, and inverse-depth in selected region for analysis.


Transect 16001165

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Jarkus transect #16001165 and region selected for analysis. Region centered at (3.53, 51.58).

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Comparison of bathymetry from Jarkus transect #16001165 (z), Vaklodingen, and inverse-depth in selected region for analysis.


RWS Vaklodingen Data

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On the top left a sample of the reconstructed bathymetry of the Westerschelde is pictured. On the top right shows a visual representation of the absolute correlation between the Vaklodingen and the reconstructed bathymetry in the intertidal regions. Green represents areas of high correlation, and red represents areas of lower correlation between data.

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On the top left a sample of the reconstructed bathymetry near Ameland is pictured. On the top right shows a visual representation of the absolute correlation between the Vaklodingen and the reconstructed bathymetry. Green represents areas of high correlation and red represents areas of lower correlation between data. On the bottom left, 5000 points within the above image were randomly sampled between the Vaklodingen and reconstructed bathymetry. This provides a relationship between the probability of water occurrence and the measured bathymetry in the region. A strong correlation exists in shallow regions for the current algorithm. On the bottom right, when points are randomly sampled accross highly correlated regions (indicated by green regions), a more evident relationship is measured in both shallow and deeper areas. Improvements to the algorithm for deeper regions is ongoing, as well as determining the best regression method for relating the reconstructed bathymetry to measured bathymetry.

A regression of z = -6.3242 x4 + 33.965 x3 - 72.483 x2 + 74.831 x - 29.659 was found to best represent the relationship between derived water occurrence, x, and depth, z, with a correlation coeffecient R2 = 0.9156.

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Visual comparison of the Vaklodingen data and the reconstructed bathymetry from this project.

References

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