Scalable multi-variate analytics of seismic and satellite-based observational data

Area of Science:

• Geophysics
• Data Science
• Geographical Information Systems (GIS)

Background:

• Increasing seismic activities worldwide necessitate better tools for analysis.
• Understanding seismic and geographical data is crucial for research and policy-making.

Purpose of the Study:

• To present a visual analytics system for exploring integrated seismic and satellite data.
• To introduce tools for intuitive comprehension of multi-modal scientific observations.

Main Methods:

• Integration of seismic and satellite data temporally and spatially.
• Development of tools for designing high-dimensional transfer functions.
• Implementation of spreadsheet-style comparisons for data drill-down and event comparison.

Main Results:

• A scalable visual analytics system enabling explorative visualization of seismic and satellite data.
• Tools for intuitive comprehension and comparison of multi-modal data related to seismic events.
• Facilitation of detailed inspection of changes during and after seismic events.

Conclusions:

• The developed system enhances the exploration and understanding of seismic and geographical information.
• The system supports both scientific research and governmental policy-making related to seismic activities.
• The system is designed for scalability across data size, complexity, and display environments.