| 1. |
- von Landesberger, Tatiana, et al.
(författare)
-
MobilityGraphs : Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering
- 2016
-
Ingår i: IEEE Transactions on Visualization and Computer Graphics. - : IEEE. - 1077-2626 .- 1941-0506. ; 22:1, s. 11-20
-
Tidskriftsartikel (refereegranskat)abstract
- Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people in certain time intervals) and to gain an understanding of the spatio-temporal changes (variations of situations over time). Traditional flow visualizations usually fail due to massive clutter. Modern approaches offer limited support for investigating the complex variation of the movements over longer time periods.We propose a visual analytics methodology that solves these issues by combined spatial and temporal simplifications. We have developed a graph-based method, called MobilityGraphs, which reveals movement patterns that were occluded in flow maps. Our method enables the visual representation of the spatio-temporal variation of movements for long time series of spatial situations originally containing a large number of intersecting flows. The interactive system supports data exploration from various perspectives and at various levels of detail by interactive setting of clustering parameters. The feasibility our approach was tested on aggregated mobility data derived from a set of geolocated Twitter posts within the Greater London city area and mobile phone call data records in Abidjan, Ivory Coast. We could show that MobilityGraphs support the identification of regular daily and weekly movement patterns of resident population.
|
|
| 2. |
- Vrotsou, Katerina, 1980-, et al.
(författare)
-
An Interactive Approach for Exploration of Flows Through Direction-Based Filtering
- 2017
-
Ingår i: Journal of Geovisualization and Spatial Analysis. - : Springer. - 2509-8810 .- 2509-8829. ; 1:1-2
-
Tidskriftsartikel (refereegranskat)abstract
- This paper is concerned with the representation and exploration of flows, defined as spatial interactions between geographic locations. Flows are challenging to display in a comprehensible manner due to the nature of the data, which are characterized by many crossings and overlaps leading to clutter. A number of different strategies have been suggested for addressing this problem, which commonly involve reducing the search space, aggregating the data or simplifying the representations often at the cost of information loss or distortion of spatial context. We propose an interactive approach for exploring large and highly connected networks of flows without distorting the geographical space and without losing the context overview in the process. The approach is based on a flow-specific interaction technique for filtering the data by direction, that enables an analyst to successively identify underlying spatial arrangement patterns. We illustrate our approach through exploring flows of tourists and locals in the Greater London area.
|
|
| 3. |
- Vrotsou, Katerina, et al.
(författare)
-
SimpliFly: A Methodology for Simplification and Thematic Enhancement of Trajectories
- 2015
-
Ingår i: IEEE Transactions on Visualization and Computer Graphics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1077-2626 .- 1941-0506. ; 21:1, s. 107-121
-
Tidskriftsartikel (refereegranskat)abstract
- Movement data sets collected using todays advanced tracking devices consist of complex trajectories in terms of length, shape, and number of recorded positions. Multiple additional attributes characterizing the movement and its environment are often also included making the level of complexity even higher. Simplification of trajectories can improve the visibility of relevant information by reducing less relevant details while maintaining important movement patterns. We propose a systematic stepwise methodology for simplifying and thematically enhancing trajectories in order to support their visual analysis. The methodology is applied iteratively and is composed of: (a) a simplification step applied to reduce the morphological complexity of the trajectories, (b) a thematic enhancement step which aims at accentuating patterns of movement, and (c) the representation and interactive exploration of the results in order to make interpretations of the findings and further refinement to the simplification and enhancement process. We illustrate our methodology through an analysis example of two different types of tracks, aircraft and pedestrian movement.
|
|
