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(true newbie here,) I have a (large) geo-data set containing [lat ,lon] and I'd like to convert it all to a flat two-dimensional surface (x,y).

The result needs to preserve the great-circle distance between each two points (what I mean here is the shortest distance by airplane travel between the two points).

I'm really not clear if this is doable accurately, what is the algorithm and is there an out of the box code doing this in Python.

shayn
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  • To answer your question, yes it would be possible. You would need to determine the unit of measure (imperial/metric) and then implement the haversine formula into your code. You would probably want to use `numpy` module for it. Look at [this example](https://stackoverflow.com/questions/29545704/fast-haversine-approximation-python-pandas). – Rory Jun 08 '22 at 14:22
  • Your requirement is `map projection` process. In general, there is no map projection that meets your needs. – swatchai Jun 20 '22 at 22:51

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