diff --git a/examples/plot-vector-methods.py b/examples/plot-vector-methods.py
new file mode 100644
index 0000000..6af8d50
--- /dev/null
+++ b/examples/plot-vector-methods.py
@@ -0,0 +1,154 @@
+"""
+=======================
+Vector plotting methods
+=======================
+
+To plot vector quantities such as currents we can use a quiver plot in matplotlib.
+In the `GBR4` tutorial dataset
+the u and v variables contain the x and y components of the vector
+for each cell in the dataset.
+Plotting every cell is straight forward for small areas:
+"""
+
+import matplotlib.pyplot as plt
+import numpy
+import pandas
+import xarray
+from shapely import box
+
+import emsarray
+from emsarray import plot
+from emsarray.operations import point_extraction
+
+dataset_url = "https://thredds.nci.org.au/thredds/dodsC/fx3/gbr4_bgc_GBR4_H2p0_B3p1_Cfur_Dnrt/gbr4_bgc_simple_2024-01-16.nc"
+dataset = emsarray.open_dataset(dataset_url, decode_timedelta=False)
+
+surface_currents = dataset.ems.select_variables(["temp", "u", "v"]).isel(time=0, k=-1)
+
+# Plot the points
+figure = plt.figure(figsize=(8, 8), layout="constrained")
+axes = figure.add_subplot(projection=dataset.ems.data_crs)
+axes.set_title("Surface water temperature and currents near the Whitsundays")
+
+temp = surface_currents["temp"]
+temp.attrs['units'] = '°C'
+temp_artist = dataset.ems.make_artist(axes, temp, cmap="coolwarm", clim=(27, 30), edgecolor="face")
+
+current_artist = dataset.ems.make_artist(
+    axes, (surface_currents["u"], surface_currents["v"]),
+    scale=20, scale_units="width")
+
+plot.add_coast(axes)
+plot.add_gridlines(axes)
+
+# Just show a small area over the Whitsundays
+view_box = box(148.7, -20.4, 149.6, -19.8)
+axes.set_extent(plot.bounds_to_extent(view_box.bounds))
+axes.set_aspect("equal", adjustable="datalim")
+
+# %%
+# Plotting the entire dataset this way leads to the current vectors becoming a confusing mess however:
+
+dataset = emsarray.tutorial.open_dataset('gbr4')
+
+surface_currents = dataset.ems.select_variables(["temp", "u", "v"]).isel(time=0, k=-1)
+
+# Plot the points
+figure = plt.figure(figsize=(8, 10), layout="constrained")
+axes = figure.add_subplot(projection=dataset.ems.data_crs)
+axes.set_title("A bad plot of surface water temperature and currents over the entire reef")
+
+temp = surface_currents["temp"]
+temp.attrs['units'] = '°C'
+temp_artist = dataset.ems.make_artist(axes, temp, cmap="coolwarm")
+
+current_artist = dataset.ems.make_artist(
+    axes, (surface_currents["u"], surface_currents["v"]),
+    scale=20, scale_units="width")
+
+plot.add_coast(axes)
+plot.add_gridlines(axes)
+
+# Show the entire model domain
+axes.autoscale()
+axes.set_aspect("equal", adjustable="datalim")
+
+# %%
+# For gridded datasets like this we can sample the current data at regular intervals to display only a subset of the vectors:
+
+dataset = emsarray.tutorial.open_dataset('gbr4')
+
+# Make an empty array of the same shape as the data, then select every nth cell in there
+samples = xarray.DataArray(numpy.full(dataset.ems.grid_size[dataset.ems.default_grid_kind], False))
+samples = dataset.ems.wind(samples)
+samples[::10, ::10] = True
+samples = dataset.ems.ravel(samples)
+
+# Select the (x, y) coordinates and the (u, v) components of the sampled cells
+surface_currents = dataset.ems.select_variables(["temp", "u", "v"]).isel(time=0, k=-1)
+x, y = dataset.ems.face_centres[samples].T
+u = dataset.ems.ravel(surface_currents["u"]).values[samples]
+v = dataset.ems.ravel(surface_currents["v"]).values[samples]
+
+# Plot the points
+figure = plt.figure(figsize=(8, 10), layout="constrained")
+axes = figure.add_subplot(projection=dataset.ems.data_crs)
+axes.set_title("Surface water temperature and currents across the entire model domain")
+
+temp = surface_currents["temp"]
+temp.attrs['units'] = '°C'
+temp_artist = dataset.ems.make_artist(axes, temp, cmap="coolwarm")
+
+quiver = plt.quiver(
+    x, y, u, v,
+    scale=40, scale_units="width")
+axes.add_collection(quiver)
+
+plot.add_coast(axes)
+plot.add_gridlines(axes)
+
+# Show the entire model domain
+axes.autoscale()
+axes.set_aspect("equal", adjustable="datalim")
+
+# %%
+# Another approach is to plot vectors at regular points across the domain. This means that the vector locations are not tied to the grid geometry.
+
+dataset = emsarray.tutorial.open_dataset('gbr4')
+
+# Generate a mesh of points across the model domain
+domain = box(*dataset.ems.bounds)
+x = numpy.arange(domain.bounds[0], domain.bounds[2], 0.4)
+y = numpy.arange(domain.bounds[1], domain.bounds[3], 0.4)
+xx, yy = numpy.meshgrid(x, y)
+points = pandas.DataFrame({
+    'x': xx.flatten(),
+    'y': yy.flatten(),
+})
+
+# Extract the surface current components at these locations
+surface_currents = dataset.ems.select_variables(["temp", "u", "v"]).isel(time=0, k=-1)
+surface_currents.load()
+components = point_extraction.extract_dataframe(
+    surface_currents, points, ('x', 'y'), missing_points='drop')
+
+# Plot the points
+figure = plt.figure(figsize=(8, 10), layout="constrained")
+axes = figure.add_subplot(projection=dataset.ems.data_crs)
+axes.set_title("Surface water temperature and currents across the entire model domain")
+
+temp = surface_currents["temp"]
+temp.attrs['units'] = '°C'
+temp_artist = dataset.ems.make_artist(axes, temp, cmap="coolwarm")
+
+quiver = plt.quiver(
+    components['x'], components['y'], components['u'], components['v'],
+    scale=30, scale_units="width")
+axes.add_collection(quiver)
+
+plot.add_coast(axes)
+plot.add_gridlines(axes)
+
+axes.autoscale()
+axes.set_aspect("equal", adjustable="datalim")
+
diff --git a/tests/baseline_images/tests.test_transect.test_plot.png b/tests/baseline_images/tests.test_transect.test_plot.png
index 401ee76..d5233f6 100644
Binary files a/tests/baseline_images/tests.test_transect.test_plot.png and b/tests/baseline_images/tests.test_transect.test_plot.png differ
diff --git a/tests/baseline_images/tests.test_transect.test_plot_no_intersection.png b/tests/baseline_images/tests.test_transect.test_plot_no_intersection.png
index 9fcd311..70a0fc0 100644
Binary files a/tests/baseline_images/tests.test_transect.test_plot_no_intersection.png and b/tests/baseline_images/tests.test_transect.test_plot_no_intersection.png differ
diff --git a/tests/test_transect.py b/tests/test_transect.py
index de9d7f9..7993cad 100644
--- a/tests/test_transect.py
+++ b/tests/test_transect.py
@@ -44,7 +44,7 @@ def test_plot(
     figure = matplotlib.pyplot.gcf()
     axes = figure.axes[0]
     # This is assembled from the variable long_name and the time coordinate
-    assert axes.get_title() == 'Temperature\n2022-05-11T14:00'
+    assert axes.get_title() == 'Temperature\n2022-10-15T14:00'
     # This is the long_name of the depth coordinate
     assert axes.get_ylabel() == 'Z coordinate'
     # This is made up
@@ -86,7 +86,7 @@ def test_plot_no_intersection(
     figure = matplotlib.pyplot.gcf()
     axes = figure.axes[0]
     # This is assembled from the variable long_name and the time coordinate
-    assert axes.get_title() == 'Temperature\n2022-05-11T14:00'
+    assert axes.get_title() == 'Temperature\n2022-10-15T14:00'
     # This is the long_name of the depth coordinate
     assert axes.get_ylabel() == 'Z coordinate'
     # This is made up