66 cartoee legend

Uncomment the following line to install geemap and cartopy if needed. Keep in mind that cartopy can be challenging to install. If you are unable to install cartopy on your computer, you can try Google Colab with this the notebook example.

See below the commands to install cartopy and geemap using conda/mamba:

conda create -n carto python=3.8
conda activate carto
conda install mamba -c conda-forge
mamba install cartopy scipy -c conda-forge
mamba install geemap -c conda-forge
jupyter notebook

In [ ]:

# !pip install cartopy scipy
# !pip install geemap

# !pip install cartopy scipy # !pip install geemap

In [ ]:

%pylab inline

import ee
import geemap

# import the cartoee functionality from geemap
from geemap import cartoee

%pylab inline import ee import geemap # import the cartoee functionality from geemap from geemap import cartoee

In [ ]:

geemap.ee_initialize()

geemap.ee_initialize()

Plot an RGB image¶

In [ ]:

# get a landsat image to visualize
image = ee.Image('LANDSAT/LC08/C01/T1_SR/LC08_044034_20140318')

# define the visualization parameters to view
vis = {"bands": ['B5', 'B4', 'B3'], "min": 0, "max": 5000, "gamma": 1.3}

# get a landsat image to visualize image = ee.Image('LANDSAT/LC08/C01/T1_SR/LC08_044034_20140318') # define the visualization parameters to view vis = {"bands": ['B5', 'B4', 'B3'], "min": 0, "max": 5000, "gamma": 1.3}

In [ ]:

fig = plt.figure(figsize=(15, 10))

# use cartoee to get a map
ax = cartoee.get_map(image, vis_params=vis)

# pad the view for some visual appeal
cartoee.pad_view(ax)

# add the gridlines and specify that the xtick labels be rotated 45 degrees
cartoee.add_gridlines(ax, interval=0.5, xtick_rotation=0, linestyle=":")

# add the coastline
ax.coastlines(color="cyan")

show()

fig = plt.figure(figsize=(15, 10)) # use cartoee to get a map ax = cartoee.get_map(image, vis_params=vis) # pad the view for some visual appeal cartoee.pad_view(ax) # add the gridlines and specify that the xtick labels be rotated 45 degrees cartoee.add_gridlines(ax, interval=0.5, xtick_rotation=0, linestyle=":") # add the coastline ax.coastlines(color="cyan") show()

By default, if a region is not provided via the region keyword the whole extent of the image will be plotted as seen in the previous Landsat example. We can also zoom to a specific region of an image by defining the region to plot.

In [ ]:

fig = plt.figure(figsize=(15, 10))

# here is the bounding box of the map extent we want to use
# formatted a [E,S,W,N]
zoom_region = [-121.8025, 37.3458, -122.6265, 37.9178]

# plot the map over the region of interest
ax = cartoee.get_map(image, vis_params=vis, region=zoom_region)

# add the gridlines and specify that the xtick labels be rotated 45 degrees
cartoee.add_gridlines(ax, interval=0.15, xtick_rotation=0, linestyle=":")

# add coastline
ax.coastlines(color="cyan")

show()

fig = plt.figure(figsize=(15, 10)) # here is the bounding box of the map extent we want to use # formatted a [E,S,W,N] zoom_region = [-121.8025, 37.3458, -122.6265, 37.9178] # plot the map over the region of interest ax = cartoee.get_map(image, vis_params=vis, region=zoom_region) # add the gridlines and specify that the xtick labels be rotated 45 degrees cartoee.add_gridlines(ax, interval=0.15, xtick_rotation=0, linestyle=":") # add coastline ax.coastlines(color="cyan") show()

Adding north arrow, scale bar, and legend¶

In [ ]:

fig = plt.figure(figsize=(15, 10))

# here is the bounding box of the map extent we want to use
# formatted a [E,S,W,N]
zoom_region = [-121.8025, 37.3458, -122.6265, 37.9178]

# plot the map over the region of interest
ax = cartoee.get_map(image, vis_params=vis, region=zoom_region)

# add the gridlines and specify that the xtick labels be rotated 45 degrees
cartoee.add_gridlines(ax, interval=0.15, xtick_rotation=0, linestyle=":")

# add coastline
ax.coastlines(color="cyan")

# add north arrow
cartoee.add_north_arrow(
    ax, text="N", xy=(0.05, 0.25), text_color="white", arrow_color="white", fontsize=20
)

# add scale bar
cartoee.add_scale_bar_lite(
    ax, length=10, xy=(0.1, 0.05), fontsize=20, color="white", unit="km"
)

ax.set_title(label='Landsat False Color Composite (Band 5/4/3)', fontsize=15)

# add legend
legend_elements = [
    Line2D([], [], color='#00ffff', lw=2, label='Coastline'),
    Line2D(
        [],
        [],
        marker='o',
        color='#A8321D',
        label='City',
        markerfacecolor='#A8321D',
        markersize=10,
        ls='',
    ),
]

cartoee.add_legend(ax, legend_elements, loc='lower right')

show()

fig = plt.figure(figsize=(15, 10)) # here is the bounding box of the map extent we want to use # formatted a [E,S,W,N] zoom_region = [-121.8025, 37.3458, -122.6265, 37.9178] # plot the map over the region of interest ax = cartoee.get_map(image, vis_params=vis, region=zoom_region) # add the gridlines and specify that the xtick labels be rotated 45 degrees cartoee.add_gridlines(ax, interval=0.15, xtick_rotation=0, linestyle=":") # add coastline ax.coastlines(color="cyan") # add north arrow cartoee.add_north_arrow( ax, text="N", xy=(0.05, 0.25), text_color="white", arrow_color="white", fontsize=20 ) # add scale bar cartoee.add_scale_bar_lite( ax, length=10, xy=(0.1, 0.05), fontsize=20, color="white", unit="km" ) ax.set_title(label='Landsat False Color Composite (Band 5/4/3)', fontsize=15) # add legend legend_elements = [ Line2D([], [], color='#00ffff', lw=2, label='Coastline'), Line2D( [], [], marker='o', color='#A8321D', label='City', markerfacecolor='#A8321D', markersize=10, ls='', ), ] cartoee.add_legend(ax, legend_elements, loc='lower right') show()

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Last update: 2023-03-19
Created: 2020-10-23