What are the significant applications of minimum spanning trees?After doing some research online and in several textbooks, I have found three real-world applications:Building a connected network.  There are scenarios where we have a limited set of possible routes, and we want to select a subset that will make our network (e.g., electrical grid, computer network) fully connected at the lowest cost.Clustering.  If you want to cluster a bunch of points into $k$ clusters, then one approach is to compute a minimum spanning tree and then drop the $k-1$ most expensive edges of the MST.  This separates the MST into a forest with $k$ connected components; each component is a cluster.  (I confess I'm not very clear on whether anyone uses this clustering method in practice, and if so, what domains it is useful in.)Traveling salesman problem.  There's a straightforward way to use the MST to get a $2$-approximation to the optimal solution to the traveling salesman problem, and the Christofides' heuristic uses MSTs to get a $1.5$-approximation.  (One could reasonably question how real-world this is, though, as there are other approximation algorithms for the traveling salesman problem that will typically do even better in practice.)I have found vague references to other applications, but I have not found details.  Are there other significant real-world applications of minimum spanning trees, and if so, how do they work?
Applications of min spanning trees
graphs;spanning trees;weighted graphs;applied theory