Kalman Filter Sensor Processing
As with any question like this, the answer is: It depends.

What does it depend on? Your signal model.

If your signal model generates $X$ and $Y$ axis velocities independently from each other so that there is no transfer function between the two channels, then two 1D Kalman filters will work the same as one 2D Kalman filter.

If your signal model allows interaction between $X$ and $Y$ axis values, then you lose that captured interaction between the axes, which can degrade the performance of the two 1D Kalman filters over a single more accurate 2D Kalman filter.

To give any more detailed answer will require you to state your signal model.



The edit really doesn't give me enough information, but let me try to update my answer.

I'm assuming, from what you say, that the latitude and longitude are estimated from a nadir image.  If that's true, then unless the image pixels are precisely aligned with the lines of latitude and longitude, you will get cross-coupling between your latitude and longitude estimates.

That cross-coupling means you'll be better off using a 2D Kalman filter.