Cross-section along a transect

pygmt.project and pygmt.grdtrack can be used to focus on a quantity and its variation along a desired survey line. In this example, the elevation is extracted from a grid provided via pygmt.datasets.load_earth_relief. The figure consists of two parts, a map of the elevation in the study area showing the survey line and a Cartesian plot showing the elevation along the survey line.

This example is orientated on an example in the GMT/China documentation: https://docs.gmt-china.org/latest/examples/ex026/

import pygmt

# Define region of study area
# lon_min, lon_max, lat_min, lat_max in degrees East and North
region_map = [122, 149, 30, 49]

# Create a new pygmt.Figure instance
fig = pygmt.Figure()

# ----------------------------------------------------------------------------
# Bottom: Map of elevation in study area

# Set up basic map using a Mercator projection with a width of 12 centimeters
fig.basemap(region=region_map, projection="M12c", frame="af")

# Download grid for Earth relief with a resolution of 10 arc-minutes and gridline
# registration [Default]
grid_map = pygmt.datasets.load_earth_relief(resolution="10m", region=region_map)

# Plot the downloaded grid with color-coding based on the elevation
fig.grdimage(grid=grid_map, cmap="oleron")

# Add a colorbar for the elevation
fig.colorbar(
    # Place the colorbar inside the plot (lower-case "j") in the Bottom Right (BR)
    # corner with an offset ("+o") of 0.7 centimeters and 0.3 centimeters in x or y
    # directions, respectively; move the x label above the horizontal colorbar ("+ml")
    position="jBR+o0.7c/0.8c+h+w5c/0.3c+ml",
    # Add a box around the colobar with a fill ("+g") in "white" color and a
    # transparency ("@") of 30 % and with a 0.8-points thick, black, outline ("+p")
    box="+gwhite@30+p0.8p,black",
    # Add x and y labels ("+l")
    frame=["x+lElevation", "y+lm"],
)

# Choose a survey line
fig.plot(
    x=[126, 146],  # Longitude in degrees East
    y=[42, 40],  # Latitude in degrees North
    # Draw a 2-points thick, red, dashed line for the survey line
    pen="2p,red,dashed",
)

# Add labels "A" and "B" for the start and end points of the survey line
fig.text(
    x=[126, 146],
    y=[42, 40],
    text=["A", "B"],
    offset="0c/0.2c",  # Move text 0.2 centimeters up (y direction)
    font="15p",  # Use a font size of 15 points
)

# ----------------------------------------------------------------------------
# Top: Elevation along survey line

# Shift plot origin to the top by the height of the map ("+h") plus 1.5 centimeters
fig.shift_origin(yshift="h+1.5c")

fig.basemap(
    region=[0, 15, -8000, 6000],  # x_min, x_max, y_min, y_max
    # Cartesian projection with a width of 12 centimeters and a height of 3 centimeters
    projection="X12c/3c",
    # Add annotations ("a") and ticks ("f") as well as labels ("+l") at the west or
    # left and south or bottom sides ("WSrt")
    frame=["WSrt", "xa2f1+lDistance+u°", "ya4000+lElevation / m"],
)

# Add labels "A" and "B" for the start and end points of the survey line
fig.text(
    x=[0, 15],
    y=[7000, 7000],
    text=["A", "B"],
    no_clip=True,  # Do not clip text that fall outside the plot bounds
    font="10p",  # Use a font size of 10 points
)

# Generate points along a great circle corresponding to the survey line and store them
# in a pandas.DataFrame
track_df = pygmt.project(
    center=[126, 42],  # Start point of survey line (longitude, latitude)
    endpoint=[146, 40],  # End point of survey line (longitude, latitude)
    generate=0.1,  # Output data in steps of 0.1 degrees
)

# Extract the elevation at the generated points from the downloaded grid and add it as
# new column "elevation" to the pandas.DataFrame
track_df = pygmt.grdtrack(grid=grid_map, points=track_df, newcolname="elevation")

# Plot water masses
fig.plot(
    x=[0, 15],
    y=[0, 0],
    fill="lightblue",  # Fill the polygon in "lightblue"
    # Draw a 0.25-points thick, black, solid outline
    pen="0.25p,black,solid",
    close="+y-8000",  # Force closed polygon
)

# Plot elevation along the survey line
fig.plot(
    x=track_df.p,
    y=track_df.elevation,
    fill="gray",  # Fill the polygon in "gray"
    # Draw a 1-point thick, black, solid outline
    pen="1p,black,solid",
    close="+y-8000",  # Force closed polygon
)

fig.show()