Spatial Generalization and Aggregation of Massive Movement Data
By Natalia V. Andrienko, Gennady L. Andrienko. IEEE Transactions on Visualization and Computer Graphics, 2011
418 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Geography, Planning and Development, Signal Processing
View Paper: https://www.semanticscholar.org/paper/ded4b3097c92775ce93e328c048f0b49de814ba4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Shixia Liu
- Yingcai Wu
- Ronghua Liang
- Guodao Sun
- Gennady L. Andrienko
- Natalia V. Andrienko
- Daniel A. Keim
- Peter Bak
In Geography, Planning and Development
- Daniel A. Keim
- Gennady L. Andrienko
- Natalia V. Andrienko
- Yingcai Wu
- Shixia Liu
- Peter Bak
- Stefan Wrobel
- Ronghua Liang
In Signal Processing
- Shixia Liu
- Yingcai Wu
- Ronghua Liang
- Guodao Sun
- Daniel A. Keim
- Natalia V. Andrienko
- Gennady L. Andrienko
- Stefan Wrobel
Citations in the corpus
- Visual Analytics of Movement (2013, methodology): “Therefore, we suggest a method that divides a territory into convex polygons of approximately equal size based on the point distribution (Andrienko and Andrienko 2011).”
- A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges (2013, methodology): “Density-based methods with kernel density estimation techniques[33,35,47-48] are used for visualizing a large number of trajectories on a map.”
- Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey (2013, neutral): “Andrienko and Andrienko [105] visualize movement data by combining data aggregation with flow maps.”