fix: static map plot using matplotlib for Image

[12rambau]

related to #303

Earthengine has been designed with a big focus on the interactive mappng of the code editor. None the less, people still need to perform presentation and report where a reproducible static image is much more meaningful than a screenshot of the Google interface. This issue is still very real even when using geemap. To simplify the interface I propose in this PR a pot() method for the Image object.

Few technical choices:

• I only support the object based implementation of matplotlib, i.e. you need to provide an ax. (can be modified in a follow-up PR)
• I only support images and not imageCollection as I want to leave the user to filter and composite from GEE side
• I only support named colormap for now (can be cahnged in a follow-up PR

demo:

Using the following code you can create a simple S2 image over vatican city:

import ee
import geetools

level0 = ee.FeatureCollection("FAO/GAUL/2015/level0")
vatican = level0.filter(ee.Filter.eq("ADM0_NAME", "Holy See"))

def mask_s2_clouds(image):
  qa = image.select('QA60')
  cloud_bit_mask, cirrus_bit_mask = 1 << 10, 1 << 11
  mask = qa.bitwiseAnd(cloud_bit_mask).eq(0).And(qa.bitwiseAnd(cirrus_bit_mask).eq(0))
  return image.updateMask(mask)

image = (
    ee.ImageCollection('COPERNICUS/S2_HARMONIZED')
    .filterDate('2022-06-01', '2022-06-30')
    .filterBounds(vatican)
    .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 20))
    .map(mask_s2_clouds)
    .geetools.spectralIndices("NDVI")
    .mosaic()
)

Now to display this image with the overlay of the vatican shape you can do:

from matplotlib import pyplot as plt

fig, ax = plt.subplots(figsize=(10,10))
image.geetools.plot(
    bands = ["NDVI"], 
    ax=ax,
    region=vatican.geometry(), 
    crs="EPSG:3857", 
    scale=10, 
    fc=vatican, 
    cmap="viridis",
    color="k"
)

# as it's a figure you can then edit the information as you see fit
ax.set_title("NDVI in Vatican City")
ax.set_xlabel("x coordinates (m)")
ax.set_ylabel("y coordinates (m)")
fig.colorbar(ax.images[0], orientation='horizontal', label="NDVI")

and get this:

works as well with RGB band combination:

from matplotlib import pyplot as plt

fig, ax = plt.subplots(figsize=(10,10))
image.geetools.plot(
    bands = ["B4", "B3", "B2"], 
    ax=ax, 
    region=vatican.geometry(), 
    fc=vatican, 
    color="k"
)

# as it's a figure you can then edit the information as you see fit
ax.set_title("Sentinel 2 composite in Vatican City")
ax.set_xlabel("longitude")
ax.set_ylabel("latitude")

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 76.52%. Comparing base (820827c) to head (be2f523).

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #311      +/-   ##
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+ Coverage   76.18%   76.52%   +0.34%     
==========================================
  Files          30       30              
  Lines        1579     1602      +23     
  Branches      193      196       +3     
==========================================
+ Hits         1203     1226      +23     
  Misses        356      356              
  Partials       20       20              

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