Human mobility is known to be distributed across several orders of magnitude of physical distances, which makes it difficult to find or define typical and meaningful scales. Relying on geotagged data collected from photo-sharing social media, we apply community detection to movement networks constrained by increasing percentiles of the distance distribution. We discover clear phase transitions in the community partition space. This is the first known method of identifying natural scales of human movement. The partitions of the natural scales allow us to draw discrete multi-scale geographical boundaries, potentially capable of providing key insights in fields such as epidemiology or cultural contagion.