Notes on Spatial Data Structures for GIS

Overview of Spatial Data and Structures

  • Spatial Data: Represents features and phenomena related to geographic locations.
  • GIS Function: Simplifies the complex real world using data models and structures.

Levels of Abstraction in GIS

  1. Real World: Physical entities and phenomena.
  2. Data Model: Simplified representation of objects from the real world.
  3. Data Structure: Implementation and organization of the data model.
  4. File Structure: How data is stored on physical media.

Spatial Data Models

  • Definition: A spatial data model is a simplified representation of spatial features on the Earth's surface.
  • Types of Models:
    • Vector Model: Includes Points, Lines, and Polygons.
    • Raster Model: Comprised of Grid cells and Pixels.
  • Attributes: Additional information associated with spatial features.

Vector Data and Topology

  • Vector Data can have: Topology (relationships between features) or No Topology.
  • Topology Definitions:
    • Connection between lines.
    • Shared boundaries between areas.
    • Inclusion of points in areas.
  • Topology Function: Validates spatial relationships of neighboring and overlapping features.

Data Models for Vector Objects

  1. Georelational Model:
    • Geometry and attributes stored separately.
    • Uses Feature Identification number to link geometry to attributes.
  2. Object-Based Data Model (OODM):
    • Geometry and attributes stored in a unified system.
    • Features are treated as objects with properties and methods.

Georelational Data Model: Shapefile

  • Shapefiles include multiple files with the same base name but different extensions (e.g., country.shp, country.shx, country.dbf).
  • Advantages of Shapefile:
    • Faster display and non-proprietary.
  • Disadvantages:
    • Shapes can overlay, duplicate boundary storage, limited error checking, and potential data quality issues.

Georelational Data Model: Coverage

  • Coverage: Contains both spatial and descriptive attribute data.
  • Introduced in the early '80s with ArcInfo, made of multiple physical files in a folder.
  • Topology: May include feature relationships.

Object-Oriented Data Model (OODM)

  • Definition: Stores geometry and attributes as objects.
  • Key Components:
    • Feature Class: Storage for spatial features with the same geometry.
    • Feature Dataset: Storage for features sharing extent and coordinate systems.
  • OODM differs from Georelational Model in that both geometry and attributes are stored within the same system, often in BLOB format.

Geodatabase in ArcGIS

  • Geodatabase: Centralized system for storing feature layers.
  • Types of Geodatabases:
    1. Personal Geodatabase: Uses Microsoft Access, 2GB limit.
    2. File Geodatabase: Stores data in multiple small files, no size limit.

Topology in Geodatabase

  • Defined as rules ensuring the integrity of spatial relationships within vector layers.
  • Examples include no overlapping boundaries for countries or no intersecting contour lines.

Raster Data Model

  • Definition: Represents continuous surface features using a grid of pixels.
  • Storage Methods:
    1. Cell by Cell Coding: Simplest method, ideal for rapidly changing surfaces.
    2. Run Length Coding: Efficient for repetitive values, stores runs of similar values.
    3. Quadtree Coding: Recursively divides raster into quadrants based on pixel similarity.

Raster Data Compression

  • Types of Compression:
    1. Lossless: Original data can be fully reconstructed.
    2. Lossy: Allows for compression but results in loss of data quality, generally used for background images.

Conversions and Integration

  • Conversion Types:
    1. Rasterization: Converts vector data to raster format.
    2. Vectorization: Converts raster data to vector format.
    3. Hybrid Models: Utilize both formats simultaneously.
  • Integration in GIS: Crucial for analysis, combining various data types.