GIS Colloquium – Talks (Winter Term 2017/2018)
Mon, October 23, 2.15 pm (Venue: INF 348, Room 015)
Digital 3D city models are of crucial importance in many applications such as urban and regional planning and enable in the environmental field precise analyses and simulations of pollutant, flood, and noise propagation. Their manual reconstruction provides good results, but is usually very time-consuming and expensive. In order to overcome this issue, the development of automatic reconstruction approaches for the time-efficient and cost-effective generation of 3D building models has become of great interest in recent years. In this talk, a fully automatic building reconstruction approach will be presented which uses building points of an aerial LiDAR data set. The approach is characterized by a strong integration of building knowledge, which is automatically derived during the reconstruction through the application of a graph grammar. It utilizes half-space modeling techniques for the construction of 3D building models to ensure their topological correctness. The resulting building models feature many details and provide in addition to the geometric information also semantic information if required. Thus, they are well suited for different applications. The talk will conclude with a brief overview of related research activities of the speaker.
Travel History: Reconstructing Travelers Semantic Trajectories Based on Heterogeneous Social Footprints
Amon Veiga Santana
Mon, November 20, 2.15 pm (Venue: INF 348, Room 015)
Travel specialized services on the web have increased their sociability and usage by adopting mechanisms that facilitates content sharing in real time between users. These web applications, however, lack tools that allow travelers to share their experiences, such as places they have visited, itineraries they have performed, and other activities of a typical touristic trip. These inds of information, when available, are insufficient and incomplete. The process of generating structured and semantic rich datasets based on recommended trips, routes and destinations usually requires high effort to be generated. This task is frequently manual, cumbersome, inaccurate, time-consuming, and depends on user’s willingness to cooperate. This work proposes a solution for reconstructing travel histories using heterogeneous social sources, such as posts in social networks, GPS positioning data, location history data generated by cloud services or any digital footprint with an associated geographic position. The solution encompasses a conceptual model; a methodology to reconstruct travel histories based on heterogeneous social tracks sources; and an application to present the reconstructed travel itinerary in a graphical and interactive fashion. An experiment conducted with real travelers showed that the proposed solution is a reasonable way to reconstruct semantic-rich travel histories in an automatic fashion.