subspace clustering with density threshold

let say I apply subspace clustering with apriori rule.

so, i use 2 units to divide the space. for example, my x is from 0 to 20. so i will have 10 grids.

if 1D space (x) cellA is dense, cnt>5.

if 1D space (y) cellB is dense, cnt>5.

then I consider 2D space (x,y), cellAB, and if the cnt>5, then I found a dense cluster.

but as higher space, it is more less likely to have dense unit.

if i relax the constraint, such that in 2D space (x,y), I use 4 units to divide the space, so I have a bigger grid size, and have 5 grids only.

can i still apply apriori to find dense units in 2D space?

is that any direct explanation? or google keyword or suggested reading that I can read to understand this type of "dense" definition variance?