Two-point Equidistant Projection and Degree-of-interest Filtering for Smooth Exploration of Geo-referenced Networks

TL;DR

This paper introduces a novel visualization method combining two-point equidistant projection and degree-of-interest filtering to enable smooth, space-efficient exploration of geo-referenced networks from an ego-perspective, maintaining spatial awareness.

Contribution

It presents a new visualization approach that improves animated geographic transitions and reduces screen space requirements for exploring unevenly distributed geo-networks.

Findings

Preliminary study shows effective preservation of directional relationships during transitions.

Use cases demonstrate reduced screen space needed for ego-perspective exploration.

Method supports smooth animated transitions in geo-referenced network visualization.

Abstract

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.