I should think after defining a uniform distribution of points, you could cluster them as needed to form larger lower-resolution chunks according to population size. Binning everyone in that region to say the central most point. Which could then be adaptive as the populations change.
This is the correct answer. You need an aggregation threshold that restricts precision when population count is too low. In this case, the cell size needs to increase until there are at least N users.
