Geographic Information Systems (GIS) Summary

Geographic Information

  • GIS can refer to both Geographic Information System (a computer-based system for analysis) and Geographic Information Science (the science behind the system).
  • 'Geographic' refers to location or spatial data, while 'information' is meaningful data.

Geographic Information System (GIS) Definition

  • A computer-based system for capturing, storing, querying, analyzing, and displaying geospatial data.
  • Capturing: Turning real-world observations into geospatial data.
  • Storing: Organizing data for analysis.
  • Querying: Retrieving specific data.
  • Analyzing: Performing spatial analysis.
  • Displaying: Visualizing results.

Thinking Spatially

  • Abstraction: Simplifying complex real-world phenomena for representation in a GIS.
  • Scale: Dependent on the purpose and resources; large scale maps have high detail, while small scale maps have less detail.
  • Dimensionality:
    • Point (0D)
    • Line (1D)
    • Polygon (2D)
    • 2.5D (one Z value per XY location)
    • 3D (multiple XYZ combinations)
    • 4D (includes temporal dimension)

Spatial and Non-Spatial Components

  • Spatial Component: Location and geometry of geographic features.
  • Non-Spatial Component: Attributes or characteristics of those features.

Data Models

  • Vector: Represents discrete objects (e.g., points, lines, polygons).
  • Raster: Represents continuous phenomena (e.g., elevation, temperature) as grid cells.

Real World Objects and Phenomena

  • Objects: Discrete entities with clear boundaries (e.g., fields, houses, rivers).
  • Phenomena: Continuous data without clear boundaries (e.g., temperature, elevation).
  • Discrete Themes: Objects or phenomena with crisp boundaries.
  • Continuous Themes: Phenomena with values everywhere.

Vector vs. Raster Data Models

  • Vector: More precise for discrete themes; represented as points, lines, or polygons.
  • Raster: Grid-based model for continuous themes; each grid cell has a unique value.

Representing Geospatial Data

  • Locate objects/phenomena using coordinate systems.
  • Use projections to represent locations in 2D space.

Discrete vs. Continuous Features

  • Discrete: Clear boundaries (roads, buildings).
  • Continuous: No boundaries (temperature, elevation); must be discretized.

GIS Data Models: Vector vs. Raster

  • Vector: Points, lines, polygons.
  • Raster: Grid-based model.

Vector Data Model

  • Points: 0D, represented by coordinates (x,y)(x, y).
  • Lines: 1D, represented by a list of coordinates (at least two points).
  • Polygons: 2D, enclosed lines represented by a list of coordinates with the same start and end nodes.

Raster Data Model

  • Grid-based model.
  • Basic unit is the cell.
  • Arranged in rows and columns.
  • Resolution determined by grid cell size.
  • Satellite Imagery: Uses pixels instead of grids; resolution is pixel size.

Raster vs. Vector Comparison

  • Raster: Faster processing.
  • Vector: More precise, complex data structures.

Georeferencing

  • Identifying the location of data in the real world.
  • Reference Surfaces: Sphere and ellipsoid.
  • Projections: Cylindrical, conical, planar.

Reference Surfaces

  • Geoid: Equipotential surface at mean sea level for measuring heights.
  • Ellipsoid: Mathematical figure of the earth for measuring coordinates (latitude/longitude).

Map Projections

  • Projecting coordinates from the ellipsoid onto a map plane (Cartesian coordinates).
  • Types: Planar, conical, cylindrical.