Calculating grid gradient and radiance

The pygmt.grdgradient method calculates the gradient of a grid file. In the example shown below we will see how to calculate a hillshade map based on a Data Elevation Model (DEM). As input pygmt.grdgradient gets a xarray.DataArray object or a path string to a grid file, calculates the respective gradient and returns it as an xarray.DataArray object. We will use the radiance parameter in order to set the illumination source direction and altitude.

Out:

grdblend [NOTICE]: Remote data courtesy of GMT data server oceania [http://oceania.generic-mapping-tools.org]
grdblend [NOTICE]: Earth Relief at 3x3 arc seconds tiles provided by SRTMGL3 (land only) [NASA/USGS].
grdblend [NOTICE]:   -> Download 1x1 degree grid tile (earth_relief_03s_g): N37W120
<IPython.core.display.Image object>

import pygmt

# Define region of interest around Yosemite valley
region = [-119.825, -119.4, 37.6, 37.825]

# Load sample grid (3 arc second global relief) in target area
grid = pygmt.datasets.load_earth_relief(resolution="03s", region=region)

# calculate the reflection of a light source projecting from west to east
# (azimuth of 270 degrees) and at a latitude of 30 degrees from the horizon
dgrid = pygmt.grdgradient(grid=grid, radiance=[270, 30])

fig = pygmt.Figure()
# define figure configuration
pygmt.config(FORMAT_GEO_MAP="ddd.x", MAP_FRAME_TYPE="plain")

# --------------- plotting the original Data Elevation Model -----------

pygmt.makecpt(cmap="gray", series=[200, 4000, 10])
fig.grdimage(
    grid=grid,
    projection="M12c",
    frame=['WSrt+t"Original Data Elevation Model"', "xa0.1", "ya0.1"],
    cmap=True,
)

fig.colorbar(position="JML+o1.4c/0c+w7c/0.5c", frame=["xa1000f500+lElevation", "y+lm"])

# --------------- plotting the hillshade map -----------

# Shift plot origin of the second map by 12.5 cm in x direction
fig.shift_origin(xshift="12.5c")

pygmt.makecpt(cmap="gray", series=[-1.5, 0.3, 0.01])
fig.grdimage(
    grid=dgrid,
    projection="M12c",
    frame=['lSEt+t"Hillshade Map"', "xa0.1", "ya0.1"],
    cmap=True,
)

fig.show()