With the advancement of technology, it is now easy to collect the location information of mobile users over time. Spatio-temporal data mining techniques were proposed in the literature for the extraction of patterns from spatio-temporal data. However, current techniques can only produce patterns at the finest time granularity, and therefore overlooks potential patterns available at coarser time granularities. In this work, we propose several techniques to allow mining at different time granularities. Experimental results show that the proposed techniques are indeed effective and efficient for mining periodic spatiotemporal patterns at different time granularities.