Sampling along tracks

The pygmt.grdtrack function samples a raster grid’s value along specified points. We will need to input a 2D raster to grid which can be an xarray.DataArray. The points parameter can be a pandas.DataFrame table where the first two columns are x and y (or longitude and latitude). Note also that there is a newcolname parameter that will be used to name the new column of values we sampled from the grid.

Alternatively, we can provide a NetCDF file path to grid. An ASCII file path can also be accepted for points, but an outfile parameter will then need to be set to name the resulting output ASCII file.

Out:

earth_relief_60m: Download file from the GMT data server [data set size is 106K].
earth_relief_60m: Earth Relief at 60x60 arc minutes obtained by Gaussian Cartesian filtering (111 km fullwidth) of SRTM15+V2 [Tozer et al., 2019].

<IPython.core.display.Image object>

import pygmt

# Load sample grid and point datasets
grid = pygmt.datasets.load_earth_relief()
points = pygmt.datasets.load_ocean_ridge_points()
# Sample the bathymetry along the world's ocean ridges at specified track points
track = pygmt.grdtrack(points=points, grid=grid, newcolname="bathymetry")

fig = pygmt.Figure()
# Plot the earth relief grid on Cylindrical Stereographic projection, masking land areas
fig.basemap(region="g", frame=True, projection="Cyl_stere/150/-20/8i")
fig.grdimage(grid=grid, cmap="gray")
fig.coast(land="#666666")
# Plot using circles (c) of 0.15cm, the sampled bathymetry points
# Points are colored using elevation values (normalized for visual purposes)
fig.plot(
    x=track.longitude,
    y=track.latitude,
    style="c0.15c",
    cmap="terra",
    color=(track.bathymetry - track.bathymetry.mean()) / track.bathymetry.std(),
)
fig.show()