My googling shows 148.94 trillion square meters, with 18.6 trillion
We'll being generous to say "good enough to spot a car" is 2 pixels with 1 meter pixel size.
To be moderately confident it's a car, I'd guesstimate we'd need quite a bit higher resolution.
With no compression and RGB 24 bit encoding, that's 3 bytes/pixel, or 446 TB of data per "frame" of our realtime recording. Of course that could be compressed down a TON, but regardless it's a staggeringly large quantity of data to work with.
> some machine learning it should be possible to skip most of oceans forests and deserts (unless some unusual object appears in that area).
As far as I can think through, you'd need to process the data in the oceans, forests, and deserts if you want to find unusual objects. We can't do a shortcut and say only 1/8 of the world is inhabited/developed in some way and that's all we're going to monitor. Perhaps you take 1/4 or 1/8 of the data from the vast amounts of uninteresting data and look for larger anomalies.
No matter how you look at it, there'd be a ridiculous amount of data and processing required to do object detection on that scale.