In Geographic Information Systems (GIS), there are two primary types of spatial data: Raster and Vector. Each type represents geographic features and spatial information in a different way.

Raster Data

• Definition: Raster data is a grid of cells (pixels), each with a value representing information, such as temperature, elevation, or land cover.
• Structure: Made up of rows and columns forming a matrix; each cell has a geographic location and a value.
• Best Used For:
  • Continuous data (e.g., satellite imagery, aerial photos, elevation models)
  • Surface analysis (e.g., slope, aspect)
• Examples:
  • Digital Elevation Models (DEMs)
  • Satellite images (e.g., Landsat)
  • Land use/land cover maps
• File Formats: .tif, .img, .jpg, .png, .grd

Vector Data

• Definition: Vector data uses geometric shapes (points, lines, polygons) to represent discrete features.
• Structure:
  • Points: Single x,y coordinates (e.g., trees, wells)
  • Lines: Series of points forming paths (e.g., roads, rivers)
  • Polygons: Closed loops defining areas (e.g., lakes, land parcels)
• Best Used For:
  • Discrete features
  • Network analysis
  • Precise boundaries
• Examples:
  • Administrative boundaries
  • Transportation networks
  • Property parcels
• File Formats: .shp, .geojson, .kml, .gdb

Summary Table

Feature	Raster	Vector
Data Type	Pixel/grid-based	Coordinate-based
Best For	Continuous data	Discrete data
Storage	Large files for high resolution	More compact for discrete features
Examples	Elevation, satellite imagery	Roads, boundaries, cities
Geometry Types	None (just grid cells)	Points, lines, polygons

Raster vs Vector

1. Data Structure

Aspect	Raster GIS	Vector GIS
Basic Concept	Grid of cells (pixels), each cell stores a value representing information such as elevation, temperature, or land cover type.	Uses points, lines, and polygons to represent spatial features directly.
Storage Structure	Matrix (rows × columns) with equal-sized cells.	Coordinate-based geometry (x, y pairs in a defined coordinate system).
Data Type	Continuous or discrete values stored in each cell.	Discrete features with associated attribute tables.
Resolution	Defined by cell size (e.g., 30 m × 30 m). Smaller cell size = higher resolution, but larger file size.	Independent of resolution — precision depends on coordinate accuracy.

2. Representation of Space

• Raster:
  • Continuous surfaces like elevation, temperature, or rainfall.
  • Every location has a value (even “no data”).
  • Suitable for data from sensors or remote sensing.
• Vector:
  • Discrete objects like roads, boundaries, rivers.
  • Can represent precise shapes and locations without pixelation.
  • Ideal for map features that have exact shapes.

3. Data Sources

• Raster Sources:
  • Satellite imagery (Landsat, Sentinel)
  • Aerial photography
  • Digital Elevation Models (DEMs)
  • Scanned paper maps
• Vector Sources:
  • GPS survey data
  • Digitized maps
  • CAD drawings
  • Administrative boundaries databases (e.g., shapefiles)

4. Spatial Analysis

Functionality	Raster GIS	Vector GIS
Overlay Operations	Cell-by-cell mathematical operations; easy for continuous data analysis.	Overlay via topological relationships; great for discrete features.
Surface Analysis	Very efficient for slope, aspect, and viewshed calculations.	Not well-suited for continuous surface modeling.
Distance & Proximity	Euclidean or cost-distance models are straightforward.	Network distance analysis works better here (roads, utilities).
Storage & Computation	Large datasets for high resolution; processing often requires more memory.	Smaller file sizes for sparse datasets; computations depend on topology.

5. Advantages and Disadvantages

Raster Advantages:

• Simple structure for computers.
• Easy integration with remote sensing.
• Excellent for modeling continuous variables.
• Fast for certain spatial analyses.

Raster Disadvantages:

• Large file sizes for fine resolution.
• Limited precision of boundaries (stair-step effect).
• Less visually appealing for vector-like features.

Vector Advantages:

• Precise location and shape representation.
• Compact file sizes for discrete features.
• Supports complex topology (adjacency, connectivity).
• High-quality cartographic output.

Vector Disadvantages:

• Complex structures for storage and processing.
• Not well-suited for continuous surface analysis without interpolation.
• Overlay operations can be slower for large datasets.

6. Common File Formats

• Raster: GeoTIFF (.tif), IMG, NetCDF, ASCII grid
• Vector: Shapefile (.shp), GeoJSON, GPKG, KML

7. Typical Applications

Raster GIS is preferred for:

• Land cover classification
• Environmental modeling (rainfall, temperature maps)
• Remote sensing imagery analysis
• Digital elevation/slope analysis

Vector GIS is preferred for:

• Urban planning and cadastral mapping
• Road and utility network management
• Political boundaries and demographic mapping
• Navigation and routing

8. A Quick Analogy

Think of Raster as a photograph (pixel-based, great for gradients and continuous tone)
and Vector as a blueprint (precise lines, scalable without loss of quality).