Spatial Generalization and Aggregation of Massive Movement Data

@article{Andrienko2011SpatialGA,
  title={Spatial Generalization and Aggregation of Massive Movement Data},
  author={Natalia V. Andrienko and Gennady L. Andrienko},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  year={2011},
  volume={17},
  pages={205-219}
}
Movement data (trajectories of moving agents) are hard to visualize: numerous intersections and overlapping between trajectories make the display heavily cluttered and illegible. It is necessary to use appropriate data abstraction methods. We suggest a method for spatial generalization and aggregation of movement data, which transforms trajectories into aggregate flows between areas. It is assumed that no predefined areas are given. We have devised a special method for partitioning the… 
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310 Citations
Highly Influential Citations
22
Background Citations
113
Methods Citations
111
Results Citations
2

310 Citations

A General Framework for Using Aggregation in Visual Exploration of Movement Data
TLDR
The goal of this research has been to systemize the possible approaches to aggregation of movement data into a framework clearly defining what kinds of exploratory tasks each approach is suitable for, and to discuss the appropriate methods of data aggregation and the visualisation techniques representing the results of aggregation.
Visual Analytics for Understanding Spatial Situations from Episodic Movement Data
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This work presents an approach utilising Visual Analytics methods to explore and understand the temporal variation of spatial situations derived from episodic movement data by means of spatio-temporal aggregation.
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A visual analytics procedure consisting of four major steps that are not limited by the size of the computer's RAM and can be applied to very large data sets, which is demonstrated by example of two real-world problems requiring analysis at different spatial scales.
Revealing Patterns and Trends of Mass Mobility Through Spatial and Temporal Abstraction of Origin-Destination Movement Data
TLDR
This work presents an approach facilitating exploration of long-term flow data by means of spatial and temporal abstraction, which allows representing spatial situations by diagram maps instead of flow maps, thus reducing the intersections and occlusions pertaining to flow maps.
Diverse Visualization Techniques and Methods of Moving-Object-Trajectory Data: A Review
TLDR
This paper summarizes the research status of trajectory data-visualization techniques in recent years and extracts common contemporary trajectoryData Visualization methods to comprehensively cognize and understand the fundamental characteristics and diverse achievements of trajectory-data visualization.
Visual Analysis of Multivariate Movement Data using Interactive Difference Views
TLDR
This work demonstrates the visual exploration of the exploration of vessel movement data from the Norwegian Coastal Administration, collected by the Automatic Ide ntification System (AIS) coastal tracking through the concept of interactive views, and proposes frequency-based visualization based on kernel density estimates (KDE).
Visualization, Selection, and Analysis of Traffic Flows
TLDR
The approach to visualize traffic flows and provide interaction tools to support their exploration is presented and validated through use cases where the temporal behavior of aircraft and vessel trajectories are explored and analyzed, e.g., landing and takeoff sequences, or the evolution of flight route density.
Directional Aggregate Visualization of Large Scale Movement Data
Widespread use of GPS terminals has made it possible to collect geospatial movement data, and visualization is an effective method to understand such data. However, for large scale movement analysis,…
An Interactive Approach for Exploration of Flows Through Direction-Based Filtering
TLDR
This paper proposes 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 based on a flow-specific interaction technique for filtering the data by direction that enables an analyst to successively identify underlying spatial arrangement patterns.
Composite Density Maps for Multivariate Trajectories
TLDR
This paper presents a flexible architecture for density maps to enable custom, versatile exploration using multiple density fields and defines six different types of blocks to create, compose, and enhance trajectories or density fields.
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