Well, the method confines the random variables to a circle when you want a square [Edit: The square would not work either as it has the wrong marginals, too. One needs the full “other dimension” for each coordinate]. It probably works just fine for the initialisation heuristic, but it is far from general purpose.
(Interestingly, a similar transformation to polar coordinates is the easiest way I know to compute the normalisation constant in the normal transform. If you could apply it to squares you would get a closed form for the normal CDF.)
Best regards
Thomas