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They detect the images with clouds, then average the rest.


Ok that makes sense. I thought they were using this as a replacement for filtering out pictures with clouds.


Well, we’re actually filtering out pixels with clouds. That’s what makes it seamless. Or, really, it’s extremely seamy, but all the seams are very subtle and between individual pixels instead of larger regions.


How do you know the difference between a cloud and a snowy/white sand area of ground?


There is a lot of work done for this in the scientific community, there are many algorithms. (is http://modis-atmos.gsfc.nasa.gov/MOD06_L2/) The most basic way is to look at the reflectivity, which must be very high, and the temperature, which must be very low. In this case, however, they probably do simply throw out all the snowy/white areas.


Rate of change, probably.




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