Focused on the issue that the existing algorithms are unable to accurately detect active hotspots from trajectory data, a novel Trajectory Structure-based Hotspots discovery (TS_HS) algorithm was proposed. TS_HS consisted of the following two algorithms:Candidate Hotspots Discovery (CHSD) algorithm and Hotspots Filter (HSF) algorithm. First, trajectory dense regions were detected by the grid based clustering method CHSD as candidate hotspots. Second, the active hotspots region of moving objects were filtered by using HSF algorithm according to moving feature and time-varying characteristic of trajectories. The experiments on the Geolife dataset show that TS_HS is an effective solution for multi-density active hotspot problem, compared with Global Density threshold based Hot Region discovery (GD_HR) and Spatio-temporal Hot Spot Region Discovering (SDHSRD). The simulation results show that the proposed framework can detect active hotspots effectively based on the structure feature and time-varying characteristic of trajectory.