Difference between revisions of "Cartopybackgrounds"
A.heerdegen (talk | contribs) |
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Blue Marble: | Blue Marble: | ||
| − | [[File:Bluemarble.png| | + | [[File:Bluemarble.png|800x666px|NASA Blue Marble as cartopy background]] |
City Lights: | City Lights: | ||
| − | [[File:Lights.png| | + | [[File:Lights.png|800x666px|NASA City Lights background plot with cartopy]] |
Explorer Base Map: | Explorer Base Map: | ||
| − | [[File:Explorer.png| | + | [[File:Explorer.png|800x666px|NASA Explorer Base Map as cartopy background]] |
Blue Marble as a background image with SST data in a near side cartopy projection | Blue Marble as a background image with SST data in a near side cartopy projection | ||
| − | [[File:Bluemarble with sst nearside.png| | + | [[File:Bluemarble with sst nearside.png|800x666px|Blue Marble background image with SST data plotted in near side cartopy projection]] |
Revision as of 18:40, 28 March 2021
Background images for cartopy plots
Cartopy is a python package for geospatial data processing that can be used to produce production quality maps. It is the supported package for this purpose and is part of our python conda distribution installed at NCI.
The cartopy package has replaced the now deprecated basemap. One of the useful functions provided by basemap that has no equivalent in the cartopy package is the ability to easily add a background "NASA Blue Marble" image.
We have downloaded three NASA blue marble products (bluemarble, city lights, explorer base map) and made them easily available to use as a background for a cartopy plot. The shut up and show me how is:
plt.figure(figsize=(24,12)) ax = plt.subplot(111, projection=ccrs.PlateCarree()) ax.background_img(name='bluemarble', resolution='high')
replace bluemarble with lights or explorer to access the different products. All are avaible in four different resolutions: low, medium, high and extrahigh (aliases for 1.0deg, 0.5deg, 0.25deg and 0.1deg).
Examples of each plot
Blue Marble:
City Lights:
Explorer Base Map:
Blue Marble as a background image with SST data in a near side cartopy projection
