I found this formula in an engineering textbook (image processing). It is an approximation of the Laplacian on flat space $\mathbb{R}^2$.
\begin{eqnarray*} \nabla^2 f &\approx& -20 f(\vec{x}) + 4 \big( f( \vec{x} + \epsilon \,\mathbf{i} ) + f( \vec{x} + \epsilon \,\mathbf{j} ) + f( \vec{x} - \epsilon \,\mathbf{i} ) + f( \vec{x} - \epsilon \,\mathbf{j} )\big) \\ &+& \big( f(\vec{x}+ \epsilon (\mathbf{i}+ \mathbf{j})\big) + \big( f(\vec{x}+ \epsilon (\mathbf{i}- \mathbf{j})\big) + \big( f(\vec{x}+ \epsilon (-\mathbf{i}+ \mathbf{j})\big) + \big( f(\vec{x}+ \epsilon (-\mathbf{i}- \mathbf{j})\big) \end{eqnarray*}
Sorry I have no succinct way of writing this. Typically one uses a Stencil:
$$ \frac{1}{6\epsilon^2} \left[ \begin{array}{ccc} 1 & 4 & 1 \\ 4 & -20 & 4 \\ 1 & 4 & 1 \end{array} \right] $$
I suspect this falls out of Euler MacLaurin formula. But he also estimate the error term. More precisely if you call the right hand side $L$ he says that:
$$ L = \nabla^2 + \frac{\epsilon^2}{12} \nabla^2( \nabla^2) + O(\epsilon)^4 $$
Can one formalize such an estimate using Sobolev norms?