I collected all the daily images of the satellite-based Soumi VIIRS sensor and calculated the per-pixel average over the whole year of 2018.
You can see fascinating patterns, e.g. “downstream” of islands in the ocean or following big rivers like the Amazon. Be wary though as snow and clouds look the same here.
It’s also fun to look at the maximum to see cloudless regions (this image is highly exaggerated and does not make too much sense anyways):
Many thanks to Joshua Stevens for motivation and infos on data availability! The initial idea was of course inspired by Charlie ‘vruba’ Lyod‘s Cloudless atlas works. I explored imagery on https://worldview.earthdata.nasa.gov/, grabbed Soumi VIIRS images via https://wiki.earthdata.nasa.gov/display/GIBS/GIBS+API+for+Developers and processed it in GDAL. Poke me repeatedly to blog about the process please. (2022: Or don’t, I didn’t document it back then and can’t remember the final specifics. I think I did use imagemagick’s
-evaluate-sequence median but might have done something in
vips2 instead. The 2020 approach via GDAL is much easier.)
Full resolution, georeferenced imagery as Cloud-Optimized GeoTIFF:
*I said average but of course it is the median. The average or mean does not make much sense to use nor does it look any good. ;-)