How to smoothen a surface?

I have a x-y-z dataset of points that represent the surface of a property (z represents the elevation). There is no x-y "grid" as the point were "randomly" chosen by the surveyor (for clarification I attached an excerpt of the data file: x-y are in UTM, z elevation in meter).

As the elevation values seem pretty noisy I would like to use matlab to smoothen the surface, meaning that the x-y values stay the same and the z-values will be smoothend.

Could someone kindly point me in the right direction how to archive this?

[KSSV]

https://in.mathworks.com/help/curvefit/smoothing-data.html

There are variety of other ways.... averaging, nearest neighbor avarage, filters, etc.

[Matt Kohl]

Thanks for the link but I could not solve my problem with it, maybe you could give me some more detailed information?

I do understand the concept of algorithms like moving average to smoothen a function f(x). And I can see that a similar concept could be applied if I had a function f(x,y) if x and y follow a grid, like f(0,0), f(0,1), f (0,2),.., f(1,0), f(1,1,),..., f(2,0), f(2,1)...

But how do solve my problem when I have "randomly" distributed x-y points each with an assigned z value (the elevation)?

I just don't understand how to enter the data and tell Matlab what to do in this case.

Any further pointers? Thank you very much.