Development Seed has a project Urchn that was trying to do something like that: https://medium.com/devseed/make-sense-of-urban-change-fabb9ff229d7 https://mediu

Development Seed has a project Urchn that was trying to do something like that: https://medium.com/devseed/make-sense-of-urban-change-fabb9ff229d7 https://medium.com/devseed/make-sense-of-urban-change-fabb9f... The idea was to take satellite imagery of the same location from different timestamps and I believe use deep learning to determine if anything in the imagery changed. I don't think they've released any code for that project yet though. But for determining whether or not the imagery could be used in a certain region, it might make more sense to just compare the timestamps of the vector data and the imagery. For instance, if the road doesn't appear in the imagery, but the vector data timestamp is after the imagery timestamp, then keep the road. And don't add a road if it was covered by a map segment that was deleted some time between the imagery timestamp and the current time.