Spatial Data

Spatial data is the foundation of Geographic Information Systems (GIS) and geospatial analysis. It represents real-world locations, objects, and features on the Earth's surface in a format that can be stored, analyzed, and visualized using GIS tools. There are two primary types of spatial data: vector data and raster data.

1. Vector Data

Vector data represents geographic features using points, lines, and polygons. It is ideal for storing discrete objects with well-defined boundaries.

Types of Vector Data:

1. Points – Represent a single location on a map.
   • Examples: Cities, trees, GPS locations
   • Attributes: Each point can store additional information (e.g., a city name, population)
2. Lines (Polylines) – Represent linear features connecting two or more points.
   • Examples: Roads, rivers, power lines
   • Attributes: Length, type (e.g., highway, railway)
3. Polygons – Represent enclosed areas with boundaries.
   • Examples: Countries, lakes, land parcels
   • Attributes: Area, land use type (e.g., forest, urban, agricultural)

2. Raster Data

Raster data represents the Earth's surface using a grid of cells (pixels), where each cell stores a value representing a characteristic of that location. It is ideal for storing continuous data such as elevation, temperature, and satellite imagery.

Types of Raster Data:

1. Satellite Imagery & Aerial Photos – Pixel values represent reflectance or spectral information.
   • Examples:

1. Digital Elevation Models (DEM) – Pixel values represent elevation above sea level.
   • Example:

1. Thematic Rasters – Pixel values represent categorical data such as land cover.
   • Example:

Vector Object Vs Raster Object:

2. Layers

GIS data is organized into layers, where each layer represents a specific type of spatial information.

• Example layers in a GIS map:
  • Roads (Vector - Line)
  • Buildings (Vector - Polygon)
  • Elevation (Raster - DEM)
  • Land Use (Raster - Classified image)