Angle-restricted steiner arborescences for flow map layout
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
FluMapper: an interactive CyberGIS environment for massive location-based social media data analysis
Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery
Crowd sensing of traffic anomalies based on human mobility and social media
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Vector field k-means: clustering trajectories by fitting multiple vector fields
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
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Flow maps are thematic maps that visualize the movement of objects, such as people or goods, between geographic regions. One or more sources are connected to several targets by lines whose thickness corresponds to the amount of flow between a source and a target. Good flow maps reduce visual clutter by merging (bundling) lines smoothly and by avoiding self-intersections. Most flow maps are still drawn by hand and only few automated methods exist. Some of the known algorithms do not support edgebundling and those that do, cannot guarantee crossing-free flows. We present a new algorithmic method that uses edge-bundling and computes crossing-free flows of high visual quality. Our method is based on so-called spiral trees, a novel type of Steiner tree which uses logarithmic spirals. Spiral trees naturally induce a clustering on the targets and smoothly bundle lines. Our flows can also avoid obstacles, such as map features, region outlines, or even the targets. We demonstrate our approach with extensive experiments.