Mapping the world’s coastlines with satellite imagery — Part II
By: Cate Seale
Tags: Marine Data, Mapping, Coastline, Satellite, Satellite Imagery

The task

Assigning tidal information to satellite images has been successfully demonstrated by Robbi Bishop-Taylor, Stephen Sagar and colleagues at Geoscience Australia in their work modelling the intertidal zones of Australia. Satellite images can be attributed with a predicted tide height using the time, date and location of the images to query a global, gridded tidal model. Then, by deriving coastline over a long time-series of imagery the generated coastline vectors can be labelled with a predicted tidal height, resulting in a picture of the intertidal zone emerging and an estimate of the coastline’s position relative to mean sea level.

To choose a tidal model (there are a number of options out there, including TPXO9-atlas, FES2014 and DTU10) we teamed up with Chris Jones and Colin Shepherd from the UKHO Tides Team to assess various models against our own ADMIRALTY TotalTide software. ADMIRALTY TotalTide can be used to predict tidal heights and tidal streams at the locations of over 7,000 tidal stations, distributed globally (7,433 at the time of writing). All of these tidal stations will have been visited in order to measure in situ observations of sea level, which are then subsequently analysed to derive the necessary underlying data (i.e. the harmonic constituents and/or time and height differences from a reference port) in order to compute a predicted tidal curve.

We could use ADMIRALTY TotalTide to provide the satellite image tide predictions, however using a gridded, global model is preferential for our purposes to obtaining estimates using in situ stations because:

In-situ observed data may not be available at the specific location of the satellite images, thus the ‘next best thing’ is a tidal prediction.

data may not be available at the specific location of the satellite images, thus the ‘next best thing’ is a tidal prediction. There may also be a lack of ‘traditional’ tidal prediction stations available in the region, thus relying on tidal stations potentially quite distant from the required area (and therefore potentially unsuitable).

stations available in the region, thus relying on tidal stations potentially quite distant from the required area (and therefore potentially unsuitable). A tidal model (once validated and assured that the predictions are suitable) offers ‘seamless’ tidal predictions over the required region on a regularly gridded scale.

Assessing the tidal models against a number of metrics (these included root mean square error comparison with ADMIRALTY TotalTide, number of harmonics, ease of automation, resolution and others) concluded that FES2014 performed best in our tests. FES is available after registration on the CNES data centre website, and comes with a handy Python package.

Tidal predictions at Station 2940 (Eastern edge of Nova Scotia, outside Bay of Fundy) for March 2011 at 15-minute intervals.

In order to maximise the chance of getting a satellite image where the tide is at all the different stages in its range, we grab all the imagery for an area from Landsat 7, Landsat 8 and Sentinel-2 satellites (available in Earth Engine), which returns a 20 year time series. Coastline is detected on each of these images using our original classifier and, following the methodology of Bishop-Taylor et. al., we derive 10 coastline contours, covering the intertidal range visible on the satellite image series, and attributed with their height relative to mean sea level.