Overlay analysis is a core technique in spatial analysis within Geographic Information Systems (GIS). It involves placing multiple spatial layers on top of one another to identify relationships between them, helping to analyze spatial patterns and draw conclusions.
Definition:
Overlay analysis combines two or more spatial datasets (e.g., maps or layers) to produce a new output that highlights spatial relationships between the input datasets.
Types of Overlay Analysis:
- Vector Overlay
- Works with vector data (points, lines, polygons).
- Common operations:
- Intersect: Returns areas where both layers overlap.
- Union: Combines all features from both layers.
- Erase (Difference): Removes areas where layers overlap.
- Identity: Keeps the input layer with the attribute information of the overlapping features.
- Raster Overlay
- Works with raster data (grids/cells).
- Involves map algebra or cell-by-cell operations.
- Common methods:
- Addition, subtraction, multiplication, etc., of raster values.
- Conditional overlays (e.g., suitability modeling).
Applications:
- Environmental planning (e.g., identifying suitable habitats or protected areas)
- Urban planning (e.g., combining zoning and infrastructure maps)
- Risk assessment (e.g., flood risk overlayed with population density)
- Site selection (e.g., finding optimal locations for businesses or facilities)
Example Use Case:
Suppose you’re planning a new hospital. You may overlay:
- Population density
- Road networks
- Proximity to existing hospitals
- Land use zones
This overlay helps identify the best location based on accessibility and need.
