GIS Data Types and Structures

GIS Data Types and Structures

Advantages and Disadvantages of Raster and Vector Data Models

Feature	Raster Data Model	Vector Data Model
Precision in Graphics	❌ Lower precision	✅ Higher precision
Traditional Cartography	❌ Less suited	✅ Well suited
Data Volume	❌ Larger	✅ Smaller
Topology	❌ Not inherently supported	✅ Inherently supported
Computation	✅ Faster for certain operations	❌ Slower for certain operations
Update	❌ More difficult	✅ Easier
Continuous Space	✅ Well suited	❌ Less suited
Integration	✅ Easier with remote sensing data	❌ More complex
Discontinuous	❌ Less suited	✅ Well suited

1. Vector and Feature Data

• Categorical and multivariate data types
• Contains attribute tables with additional information:
  • Area measurements
  • Length of shapes
  • Geographic information (state, country)

Vector Data Types

1. Points
   • Dimensionless
   • Represents single locations
2. Lines
   • One-dimensional
   • Contains attribute records
3. Polygons
   • Two-dimensional
   • Contains attribute records

2. Raster Data

• Used for continuous surfaces
• Similar to image-based data
• Characteristics:
  • Made up of fixed-size pixels
  • Each pixel contains area information
  • Contains various data types:
    • RGB imagery
    • Elevation data
    • Surface information
  • Attributes are per value, not per pixel

3. Spatial Data Containers

• File geodatabases
• SQLite/SpatiaLite databases
• GeoJSON
• PostGIS

Shapefiles (ESRI Format)

• Industry standard format
• Contains multiple files (up to 37)
• Uses dBase4 for data tables
• Limitations:
  • Slower processing
  • Larger size
  • Being replaced by newer formats like GeoJSON

4. Map Documents

• Workspace for viewing and analyzing data
• Characteristics:
  • Stores data representation
  • Non-destructive editing
  • Enables geoprocessing
  • References data on disk
• Uses layers that:
  • Stack and overlay
  • Similar to image editing software layers
  • Represent geographic data