The union monetises this by selling privacy preserving aggregates (think ‘where is everyone in London right now’, or ‘where did people commute from?’), and acts on behalf of union members to stop data brokers selling their location data.
The question of who can de-identify or unmask the data is there, but I could see the capability being required for gov, military, and police, and then as a premium service to customers.
More or less my initial approach to this is you take a grid, and you show movements/density on that grid. If necessary you coarsen the grid to avoid reidentification of individuals, and ultimately to get a good picture of the population given the biased sample which is the union membership, you need a statistical model on top which also helps from a privacy perspective.
State actors demanding individual location history is definitely an issue. I have a few possible approaches in mind to defend against that.