IX. Spatial Data

Spatial Data

• Attributes linked with spatial positions
• Typical of Scientific Visualization, geographical visulization
• Main point: choice of express, seperate, order and align do not apply

• Geometry data
  • Associated with spatial data
    • Shape of items
    • Explicit spaticial position
    • Points, lines, curves, surfaces, areas, volumes
  • Boundary between computer graphics and visualization
• Spatial Fields
  • Points/grids/cells
  • Implicit or explicit reference to 2D/3D geometry
• Sampled data = capture continous signal at a finite set of points (measurement)

<aside> 📝

Spatial Visualization Tasks/Appications

• Image/2D raster visualization
  • Display raster data, sampled in digital grids
  • Task: Easy decoding of one or more attribute values in the grid positions
• 2D/Map/Geo Visualization
  • Geometry referenced raster and vector data, handling range mapping, overlays, contouring, glyphs
  • Task: decode, compare attributes in geographical areas, evaluate distances.
• Volume visualization
  • 3D grids, with attributes correspinding to physical measurements or numerical simulation
  • Task: Medical Analysis, analysis of natural sciences measurements, validation of hypotheses for simulation results </aside>

Raster Data Visulization

• Data
  • Spatial arrangement: 2D regular grid
  • Attribute: scalar
• Task: Quantitative data analysis, detail inspection
• Idioms:
  • Color mapping
  • Windowing/tone mapping
  • Contouring for scalar data
  • Glyphs for vector visualization

Idioms: Colormaps

• Issues
  • Resampling:
    • Data captured and pixels in the screen are not the same
    • Captured data gird rotated and scaled
  • Range mapping
    • Display cannot represent arbitrary numbers of different intensity levels
    • Human cannot distinguish arbitrary low differences in intensity
    • Not necessarily useful to map linearly source value into intensity
• Tasks
  • Medical Image Analysis
  • Contract stretching
  • HDR image rendering

Vis Idiom: Contouring