Two-point Equidistant Projection and Degree-of-interest Filtering for Smooth Exploration of Geo-referenced Networks
The visualization and interactive exploration of geo-referenced networks poses challenges if the network’s nodes are not evenly distributed. Our approach proposes new ways of realizing animated transitions for exploring such networks from an ego-perspective. We aim to reduce the required screen estate while maintaining the viewers’ mental map of distances and directions. A preliminary study provides first insights of the comprehensiveness of animated geographic transitions regarding directional relationships between start and end point in different projections. Two use cases showcase how ego-perspective graph exploration can be supported using less screen space than previous approaches.
Authors
- Steffen Koch (ORCID: https://orcid.org/0000-0002-9360-799X)
- Samuel J. Beck (ORCID: https://orcid.org/0000-0002-0184-8367)
- Max Franke (ORCID: https://orcid.org/0000-0002-4244-6276)
Institutions
- University of Stuttgart (DE)
Publication Details
- Published
- 2024-10-13
- DOI
- https://doi.org/10.1109/vis55277.2024.00023
- Primary Topic
- Target Tracking and Data Fusion in Sensor Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00