sandplover.plan.compute_shoreline_roughness_coefvar

sandplover.plan.compute_shoreline_roughness_coefvar(shore_mask, origin=(0, 0))

Compute shoreline roughness, as coefficient of variation.

Computes the shoreline roughness metric:

\[R = \sqrt{1/N \sum_{i=1}^N \left( \frac{r_{i}-\bar{r}}{\bar{r}}\right)^2}\]

where R is the roughness of the shoreline, N is the total number of pixels defining the shoreline, \(r_i\) is the individual distance measurement to each point of the shoreline, and \(\bar{r}\) is the mean distance from origin to the shoreline in shore_mask (after [1]). This metric is consistent with a measure of the coefficient of variation for distances from the channel inlet to the shoreline.

Note

Internally, compute_shoreline_distance is used to compute the distances to \(r_i\) and mean distance to the shoreline \(\bar{r}\).

See also

This function is similar to, but distinct from compute_shoreline_roughness_area, which uses an approach ased on the shoreline convexity to characterize the shoreline.

[1]

Straub, K. M., Q. Li, and W. M. Benson (2015), Influence of sediment cohesion on deltaic shoreline dynamics and bulk sediment retention: A laboratory study, Geophys. Res. Lett., 42, 9808–9815, doi:10.1002/2015GL066131.

Parameters:

• shore_mask (ShorelineMask, ndarray) – Shoreline mask. Can be a ShorelineMask object, or a binarized array.

• origin (tuple, np.ndarray, optional) – Origin from which the distance to all shoreline points is computed, specified in data dimensions (not indices) along dim1, dim2 of the data. Default (0, 0).

Returns:

roughness – Shoreline roughness, computed as described above.

Return type:

float

Examples

Calculate the shoreline roughness.

>>> from sandplover.mask import ShorelineMask
>>> from sandplover.plan import compute_shoreline_roughness_coefvar
>>> from sandplover.sample_data.sample_data import golf

>>> golf = golf()
>>> sm = ShorelineMask(
...     golf["eta"][-1, :, :], elevation_threshold=0, elevation_offset=-0.5
... )
>>> sm.trim_mask(length=golf.meta["L0"].data + 1)
>>> origin = (
...     np.array([golf.meta["L0"].data, golf.meta["CTR"].data])
...     * golf.meta["dx"].data
... )

Compute roughness

>>> rough = compute_shoreline_roughness_coefvar(sm, origin=origin)

>>> fig, ax = plt.subplots()
>>> sm.show(ax=ax)
>>> _ = ax.set_title("roughness = {:.2f}".format(rough))

(Source code, png, hires.png)

See also

See this example, which compares all of the “shoreline roughness” metrics implemented in sandplover.