Plotting Open Data Cube xarray data with two or more measurement parameters in the same axis

Question

How can I plot the two measurement parameters (seasonal cover and permanent water cover) in the same axis as I want to compare them?

I have this code:

#load the cgls product
ds_cgls_builtcover = dc.load(product='cgls_landcover', time='2019', 
                             measurements=['seasonalwater_cover_fraction','permanentwater_cover_fraction'], 
                             like=ds_cgls.geobox).squeeze()

#plot the dataset
fig, (ax0, ax1) = plt.subplots(1,2, figsize=(24,9), sharex=True, sharey=True)
ds_cgls_builtcover.seasonalwater_cover_fraction.plot(ax=ax[0])
ds_cgls_builtcover.permanentwater_cover_fraction.plot(ax=ax[0])
plot_lulc(ds_cgls[measurements], product='CGLS', legend=True, ax=ax[1])

ax[0].set_title('seasonalwater_cover %')
ax[1].set_title('CGLS Landcover')
plt.tight_layout();

Answer 1

To overlay the two measurements on a plot, you can try the following code:

# Load the cgls product.
ds_cgls_builtcover = dc.load(product='cgls_landcover', time='2019', 
                             measurements=['seasonalwater_cover_fraction','permanentwater_cover_fraction'], 
                             like=ds_cgls.geobox).squeeze()


# For both measurements the no data value is 255. 
# Based on the Digital Earth Africa CGLS data catalogue page
# https://docs.digitalearthafrica.org/en/latest/data_specs/CGLS_LULC_specs.html
# Mask the no data values. 
ds_cgls_builtcover = ds_cgls_builtcover.where(ds_cgls_builtcover != 255)

# Plot the measurements on the same axis.
fig, ax = plt.subplots(figsize=(24,9))
# Plot the first measurement with a different colormap from the second.
cmap1="Blues"
cmap2="Greens"
ds_cgls_builtcover.seasonalwater_cover_fraction.plot(cmap=cmap1, ax=ax)
# Make the second plot slightly transparent. 
ds_cgls_builtcover.permanentwater_cover_fraction.plot(cmap=cmap2, ax=ax, alpha=0.5)

The above code produces this plot:

To plot the measurements side by side you can try the following code:

# Load the cgls product.
ds_cgls_builtcover = dc.load(product='cgls_landcover', time='2019', 
                             measurements=['seasonalwater_cover_fraction','permanentwater_cover_fraction'], 
                             like=ds_cgls.geobox).squeeze()


# For both measurements the no data value is 255. 
# Based on the Digital Earth Africa CGLS data catalogue page
# https://docs.digitalearthafrica.org/en/latest/data_specs/CGLS_LULC_specs.html
# Mask the no data values. 
ds_cgls_builtcover = ds_cgls_builtcover.where(ds_cgls_builtcover != 255)

# Plot the measurements side by side.
fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(24,9), sharex=True, sharey=True)
ds_cgls_builtcover.seasonalwater_cover_fraction.plot(cmap="viridis", ax=ax0)
ds_cgls_builtcover.permanentwater_cover_fraction.plot(cmap="viridis", ax=ax1)

Which results in the following plot: