Thematic Geo-Density Heatmapping for Walking Tourism Analytics using Semi-Ready GPS Trajectories

With the aim to generate beneficial reports to improve the content of walking tourism, this paper discusses methods to visualize tourist interest in geographic features in a city by automatically collecting their feedback through mobile applications. Geo-density maps that use raw trajectories generally have difficulty in determining whether the dense areas presented on them are more appealing than the other areas in a city, since environmental, user-behavioral, and technical factors present various degrees of density regardless of tourist activity. Additionally, the complicated point patterns in a trajectory underestimate polyline-shaped features, such as footpaths and streets, which are some of the most important components of walking tourism, and their density maps prevent the inference of hot streets. The proposed framework monitors user behavior, e.g., entering/leaving indoor spaces and walking/stopping, using various mobile sensors to generate semi-ready trajectory data for thematic heatmaps of city-scale tourist analysis by (1) equalizing the inherent density bias in a trajectory, (2) mitigating the errors of GPS recording, (3) adding attributes that describe concrete user events during tourism. Furthermore, our client system demonstrates hot street heatmaps, user-generated content (UGC)-oriented hot spot heatmaps, and indoor-oriented hot spot heatmaps drawn from semi-ready data. The evaluation experiment conducted in this paper illustrates that the proposed data were able to represent the actual walking trajectory more accurately than the raw GPS trajectory and existing line simplification approaches.