Python matplotlib high resolution background image#

Software requirements:

  • Python 3

  • matplotlib

  • cartopy

Script high_resolution_background_image.py:

#!/usr/bin/env python
# coding: utf-8
"""
DKRZ example script: high_resolution_background_image.py

Load and draw a high resolution images from Natural Earth Data as map background.

    The capability of Cartopy to load an image as background of a map is great.
    In many cases the Earth's topography is used to be plotted as background of a
    map for land or ocean data instead of a single color.

    First, we have to look for an image which we have downloaded the image for
    August 2004 from the NASA Earth Observation download page
    https://neo.gsfc.nasa.gov/view.php?datasetId=BlueMarbleNG&date=2004-08-01
    with a high resolution of 0.1 degrees (3600x1800 pixels).

    The images have to be stored in a directory together with a JSON file named
    images.json that will be read by Cartopy's cartopy.mpl.geoaxes.GeoAxes.background_image()
    method (https://scitools.org.uk/cartopy/docs/latest/reference/generated/cartopy.mpl.geoaxes.GeoAxes.html?highlight=background_img#cartopy.mpl.geoaxes.GeoAxes.background_img).
    Cartopy finds the image if the environment variable CARTOPY_USER_BACKGROUNDS
    is set to the image directory.

    Note: The image file NE1_HR_LC_SR_W_DR.tif from the zip file
          NE1_HR_LC_SR_W_DR.zip has to be converted to PNG file format.

Example JSON file images.json:

{"__comment__": "JSON file specifying background images. env CARTOPY_USER_BACKGROUNDS, ax.background_img()",
  "BlueMarble": {
    "__comment__": "Blue Marble Next Generation, Aug 2004, 0.1 degrees",
    "__source__": "https://neo.gsfc.nasa.gov/servlet/RenderData?si=526300&cs=rgb&format=JPEG&width=3600&height=1800",
    "__projection__": "PlateCarree",
    "high": "BlueMarble_3600x1800.png"
  },

  "BlueMarbleBright": {
    "__comment__": "Blue Marble Next Generation, Aug 2004, 0.1 degrees",
    "__source__": "https://www.naturalearthdata.com/http//www.naturalearthdata.com/download/10m/raster/NE1_HR_LC_SR_W_DR.zip",
    "__projection__": "PlateCarree",
    "high": "NE1_HR_LC_SR_W_DR.png"
  },

  "NaturalEarthRelief": {
    "__comment__": "Natural Earth I with shaded Relief, water, and drainage",
    "__source__": "https://www.naturalearthdata.com/http//www.naturalearthdata.com/download/10m/raster/NE1_HR_LC_SR_W_DR.zip",
    "__projection__": "PlateCarree",
    "high": "NE1_HR_LC_SR_W_DR.png"
  },

  "GrayEarth": {
    "__comment__": "Gray Earth with shaded relief, hypsography and ocean bottom, high res",
    "__source__": "https://www.naturalearthdata.com/http//www.naturalearthdata.com/download/10m/raster/GRAY_HR_SR_OB.zip",
    "__projection__": "PlateCarree",
    "high": "GRAY_HR_SR_OB_high_res.png"
  }
}

23.05.2022 kmf, DKRZ
"""
import os
import numpy as np

import matplotlib.pyplot as plt

import cartopy.crs as ccrs
import cartopy.feature as cfeature

def main():
    #-- set environment variable CARTOPY_USER_BACKGROUNDS
    os.environ['CARTOPY_USER_BACKGROUNDS'] = '/home/itsme/Python/Backgrounds'

    #-- set projection
    projection = ccrs.PlateCarree()

    #-- create two plots next to each other
    #-- 1. on the left ax.stock_img() is used for map background
    #-- 2. on the right the high resolution image from Natural Earth Data is used

    fig = plt.figure(figsize=(12,12))
    ax1 = fig.add_subplot(1, 2, 1, projection=projection)
    ax2 = fig.add_subplot(1, 2, 2, projection=projection, sharex=ax1, sharey=ax1)
    fig.subplots_adjust(bottom=0.05, top=0.95, left=0.04, right=0.95, wspace=0.02)

    ax1.set_title('ax.stock_img()')
    ax1.set_extent([5., 20., 35.0, 60.0])
    ax1.stock_img()
    ax1.coastlines(resolution='10m')
    gl1 = ax1.gridlines(draw_labels=True)
    gl1.xlines = False
    gl1.ylines = False
    gl1.right_labels = False

    ax2.set_title('ax.background_img() - NaturalEarth')
    ax2.set_extent([5., 20., 35.0, 60.0])
    ax2.background_img(name='NaturalEarthRelief', resolution='high')
    ax2.coastlines(resolution='10m')
    gl2 = ax2.gridlines(draw_labels=True)
    gl2.xlines = False
    gl2.ylines = False
    gl2.left_labels = False

    plt.savefig('plot_high_resolution_background_image.png', bbox_inches='tight', dpi=100)


if __name__ == '__main__':
    main()

Plot result:

image0