This paper is targeted at effectively discovery of moving objects' common movement patterns The algorithms proposed in this paper consider highly tempo-spatial relevance of moving objects, measure spatial and temporal density of moving objects by spatial properties like Euclidean distance and movement direction, and temporal property, discovery dynamic evolution process of moving object clusters by time-based plane sweeping method. Experimental results demonstrate our algorithms correctly discover similar segments from real satellite tracking dataset of bar-headed geese migration.