University of Twente Student Theses

Login

The use of different visual representation in the space time cube to explore changing network datasets

Yang, Fengfan (2011) The use of different visual representation in the space time cube to explore changing network datasets.

[img] PDF
3MB
Abstract:With the increasing road network use and traffic demand, the speed of vehicles slow down, the increased vehicular queuing incurred traffic congestion. If a stream of vehicles is stopped for more time, this is leading to a traffic jam. Nowadays, transport department face great challenges to solve questions such as how to detect and manage transport congestion and accelerate the rate of transport accessibility. To answer these questions, choosing proper representation methods to represent the changing road network datasets and expose the traffic situation is essential. However, different representations may greatly influence people‘s understanding of the same traffic situation. It is therefore important to compare existing representation methods and judge which the suitable way to visualize road network datasets is. Moreover, appropriately use the characteristics of visual variables to create new representation methods for visualizing changing network datasets will help people better understand movement patterns. In this research, three representations (flow map, 3D wall map and intensity map) are designed and implemented in a Space Time Cube (STC)-the potential representation method which can express location, time and attribute information for spatio-temporal network datasets in a 3D environment. Then, the research challenge exists in how effective efficiency and satisfactory when using the chosen methods to gain insight into spatio-temporal network datasets in order to facilitate transport managers to detect the traffic situation and make decisions. Based on the user centred design guidelines, usability test is executed and evaluated. 3D wall method in the STC environment is the best solution to deal with changing network datasets in this research.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:https://purl.utwente.nl/essays/92793
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page