Reprojecting images from a Geostationary projection¶
This example demonstrates Cartopy’s ability to project images into the desired projection on-the-fly. The image itself is retrieved from a URL and is loaded directly into memory without storing it intermediately into a file. It represents pre-processed data from the Spinning Enhanced Visible and Infrared Imager onboard Meteosat Second Generation, which has been put into an image in the data’s native Geostationary coordinate system - it is then projected by cartopy into a global Miller map.
Retrieving image... Projecting and plotting image (this may take a while)...
from io import BytesIO from urllib.request import urlopen import cartopy.crs as ccrs import matplotlib.pyplot as plt def geos_image(): """ Return a specific SEVIRI image by retrieving it from a github gist URL. Returns ------- img : numpy array The pixels of the image in a numpy array. img_proj : cartopy CRS The rectangular coordinate system of the image. img_extent : tuple of floats The extent of the image ``(x0, y0, x1, y1)`` referenced in the ``img_proj`` coordinate system. origin : str The origin of the image to be passed through to matplotlib's imshow. """ url = ('https://gist.github.com/pelson/5871263/raw/' 'EIDA50_201211061300_clip2.png') img_handle = BytesIO(urlopen(url).read()) img = plt.imread(img_handle) img_proj = ccrs.Geostationary(satellite_height=35786000) img_extent = [-5500000, 5500000, -5500000, 5500000] return img, img_proj, img_extent, 'upper' def main(): fig = plt.figure() ax = fig.add_subplot(1, 1, 1, projection=ccrs.Miller()) ax.coastlines() ax.set_global() print('Retrieving image...') img, crs, extent, origin = geos_image() print('Projecting and plotting image (this may take a while)...') ax.imshow(img, transform=crs, extent=extent, origin=origin, cmap='gray') plt.show() if __name__ == '__main__': main()
Total running time of the script: ( 0 minutes 2.595 seconds)