Amit Chourasia

1
VISUAL REPRESENTATION OF SEISMIC DATA

• Amit Chourasia
• Visualization Scientist
• Visualization Services
• San Diego Supercomputer Center
• Presented at Geoinformatics 2007, may 18th

2
Data Sources

• Observed Sensors, experiments, etc
• Simulated Weather, earthquakes, etc
• Data Attributes
• Time varying
• Multivariate
• Heterogeneous

3
Problems

• How to verify and validate ?
• How to analyze and gain scientific insight ?
• How to share information among experts and
  others?

4
Understanding Data

• Large amount of numbers dont make much sense to
  humans

• Visual information can encode large amount of
  numbers to gain insight

High
Bandwidth
Low Bandwidth
5
Quest for Visual Representation

• Desirable Attributes
• Intuitive
• Highlights feature of interest
• Color Perceptual or Rainbow style?

6
Maps

• TeraShake1.3 Spectral Acceleration at 3.0 sec

Collab SCEC
7
Self Contouring Technique

• TeraShake1.3 Spectral Acceleration at 3.0 sec

Collab SCEC
8
Topography Deformation

• TeraShake2.1 Displacement magnitude

• Puente Hills Simulation

Movie Puente Hills
Collab SCEC
9
Cross Sectional

• TeraShake2.1 Velocity Magnitude and Sliprate

Collab SCEC
10
Volumetric

• TeraShake 2.2 Velocity-X

Movie TeraShake 2.1
Collab SCEC
11
Design Evolution

• TeraShake Aggregate Data 100TB

Collab SCEC
12
Multivariate Encoding

• 1906 San Francisco Earthquake Simulation

Movie South Bound
Collab USGS
13
Multivariate Encoding

• 1906 San Francisco Earthquake Simulation

Irregular Mesh (36,000 verts, 65,000 tri)
Color Blending
Color Scheme
Collab USGS
14
Seven Story Building Shake
Movie Deformation
Collab NEES
15
Seven Story Building Shake
Original video Match Check Match
Combined
Perspective npr
Collab NEES
16
Tools - SCEC Viz portal
Collab SCEC
17
Dirty Data Issues

• Data Formats
• Data Translation
• Data transfer and replication between archival
  and active file systems
• Data larger than available memory

18
Lessons Learned (TeraShake)

• In the north-westward propagating rupture
  scenario the wave propagation is strongly guided
  toward the Los Angeles basin after leaving the
  San Andreas Fault (unexpected)
• The sediment filled basin acts as an
  amplification source for trapped waves. A Strong
  amplification is observed in the LA basin long
  after the initial rupture (unexpected)
• Contiguous basins act as energy channels,
  enhancing ground motion in parts of the San
  Gabriel and Los Angeles basins.
• Identification of regions of particularly strong
  shaking
• Validation of input rupture model and instability
  identification
• Observation of star burst patterns in the
  Spectral Amplification maps (unexpected)

19
Visualization Issues

• Domain knowledge
• Multivariate data representation design
• Temporal coherence
• Precision Loss (compression, etc)
• Interaction vs. batch visualization
• Perceptual Issues
• Personal Bias (author viewer)

20
Information is infinite

• Information overload
• Cant win
• Cant break even
• Cant get out of the game
• Can visual representation help?

Joseph Kielman Science Advisor Dept. of Homeland
Security Comments at VAST2006 Capstone
Think Petascale Data Analysis
21
Thanks for your patience? - ?Web
http//visservices.sdsc.edu/email amit
sdsc.edu