Peter Ranacher holds a Bachelor’s degree in Geography at Graz University, and a Master’s degree in Geospatial Technologies at NAWI Graz – an interdisciplinary research programme at Graz University and Graz University of Technology.
His fields of interests include geoscience in general, as well as moving objects, navigation and socio-economic aspects of traffic in urban landscapes in particular. In his Master thesis he designed and developed a social networking system with a geographic-coordinative background featuring a ride-sharing application that enables users to offer car rides between two locations to other members in the network. The system was awarded the first prize in the GoGeo09 contest organized by the Bavarian Information and Communication Cluster (BICC).
At the Doctoral College GIScience, at the University of Salzburg, Peter Ranacher will carry out research on moving objects and their trajectories, mostly concentrating on spatio-temporal representations, mobility data mining and movement pattern recognition. From March until June 2013 Peter joined the U-lab at the department of Urbanism at Delft University of Technology as a visiting researcher.
In addition to GIScience, Peter is currently studying the Russian language and has a strong interest in Russian culture, language and literature.
Spatialization, Media and Society
| Moving Objects | Mobility and Traffic Phenomena | Geographic Information Science | Data Mining |
"The Rhythm of the Street – Mining and Understanding Movement Patterns in Urban Traffic"
Today's presence of ubiquitous positioning devices allows for recording detailed traces of human movement in space and time. One such kind of human movement data are provided by floating cars. Floating cars are mobile units equipped with positioning devices. These devices - usually GPS receivers - record the spatio-temporal paths of the mobile units, the so-called movement trajectories. With its own movement a floating car reflects the flow of traffic in an urban road network. In this thesis, travel times and traffic flow from floating car data are analysed. Moreover, a methodology is developed to derive the energy use of a vehicle from its trajectory. The data for the study are recorded in the city of Salzburg and its hinterland over the period of approximately one year.
The thesis relates travel times, traffic flow and energy use of a vehicle to the road network and to time. Thus, it shows where and when vehicles move in a time-consuming, non uniform way and consume much energy. Moreover, the thesis shows, that in urban road network similar traffic flow and energy demand follow a regular pattern and repeat at regular time intervals. This temporal reoccurrence is one of the main prerequisites for predicting future travel times, traffic flow and energy demand in an urban context.
An Adaptive Sampling Approach for Trajectories Based on the Concept of Error Ellipses
Ranacher. P and Rousell. A., 2013: An Adaptive Sampling Approach for Trajectories Based on the Concept of Error Ellipses, In: Creating the GISociety, Proceedings of the GI_Forum 2013 conference, Salzburg, p. 169-176., 10.1553/giscience2013s169
Mining urban mobility to improve routing strategies for e-vehicle fleets
Ranacher, P., 2013: Mining urban mobility to improve routing strategies for e-vehicle fleets, In: Proceedings of the International Interdisciplinary Conference on Environmental Information and communication, Bogota