Modeling Checkpoint-Based Movement with the Earth Mover's Distance

Movement data comes in various forms, including trajectory data and checkpoint data. While trajectories give detailed information about the movement of individual entities, checkpoint data in its simplest form does not give identities, just counts at checkpoints. However, checkpoint data is of increasing interest since it is readily available due to privacy reasons and as a by-product of other data collection. In this paper we propose to use the Earth Mover’s Distance as a versatile tool to reconstruct individual movements or flow based on checkpoint counts at different times. We analyze the modeling possibilities and provide experiments that validate model predictions, based on coarse-grained aggregations of data about actual movements of couriers in London, UK. While we cannot expect to reconstruct precise individual movements from highly granular checkpoint data, the evaluation does show that the approach can generate meaningful estimates of object movements. B. Speckmann and K. Verbeek are supported by the Netherlands Organisation for Scientific Research (NWO) under project nos. 639.023.208 and 639.021.541, respectively. This paper arose from work initiated at Dagstuhl seminar 12512 “Representation, analysis and visualization of moving objects”, December 2012. The authors gratefully acknowledge Schloss Dagstuhl for their support

Modeling Checkpoint-Based Movement with the Earth Mover's Distance

Movement data comes in various forms, including trajectory data and checkpoint data. While trajectories give detailed information about the movement of individual entities, checkpoint data in its simplest form does not give identities, just counts at checkpoints. However, checkpoint data is of increasing interest since it is readily available due to privacy reasons and as a by-product of other data collection. In this paper we propose to use the Earth Mover’s Distance as a versatile tool to reconstruct individual movements or flow based on checkpoint counts at different times. We analyze the modeling possibilities and provide experiments that validate model predictions, based on coarse-grained aggregations of data about actual movements of couriers in London, UK. While we cannot expect to reconstruct precise individual movements from highly granular checkpoint data, the evaluation does show that the approach can generate meaningful estimates of object movements. B. Speckmann and K. Verbeek are supported by the Netherlands Organisation for Scientific Research (NWO) under project nos. 639.023.208 and 639.021.541, respectively. This paper arose from work initiated at Dagstuhl seminar 12512 “Representation, analysis and visualization of moving objects”, December 2012. The authors gratefully acknowledge Schloss Dagstuhl for their support

Representation, Analysis and Visualization of Moving Objects (Dagstuhl Seminar 12512)

From December 16 to December 21, 2012, the Dagstuhl Seminar 12512 "Representation, Analysis and Visualization of Moving Objects" was held in Schloss Dagstuhl -- Leibniz Center for Informatics. The major goal of this seminar was to bring together the diverse and fast growing, research community that is involved in developing better computational techniques for spatio-temporal object representation, data mining, and visualization of moving object data. The participants included experts from fields such as computational geometry, data mining, visual analytics, GIS science, urban planning and movement ecology. Most of the participants came from academic institutions but some also from government agencies and industry. The seminar has led to a fruitful exchange of ideas between different disciplines, to the creation of new interdisciplinary collaborations and to recommendations for future research directions. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper

Modeling Checkpoint-Based Movement with the Earth Mover’s Distance

Movement data comes in various forms, including trajectory data and checkpoint data. While trajectories give detailed information about the movement of individual entities, checkpoint data in its simplest form does not give identities, just counts at checkpoints. However, checkpoint data is of increasing interest since it is readily available due to privacy reasons and as a by-product of other data collection. In this paper we propose to use the Earth Mover’s Distance as a versatile tool to reconstruct individual movements or flow based on checkpoint counts at different times. We analyze the modeling possibilities and provide experiments that validate model predictions, based on coarse-grained aggregations of data about actual movements of couriers in London, UK. While we cannot expect to reconstruct precise individual movements from highly granular checkpoint data, the evaluation does show that the approach can generate meaningful estimates of object movements. B. Speckmann and K. Verbeek are supported by the Netherlands Organisation for Scientific Research (NWO) under project nos. 639.023.208 and 639.021.541, respectively. This paper arose from work initiated at Dagstuhl seminar 12512 “Representation, analysis and visualization of moving objects”, December 2012. The authors gratefully acknowledge Schloss Dagstuhl for their support