Spatial Data Types

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What is Spatial Data?

Spatial data describes the absolute or relative location of geographic features. Simply put, it answers the question: “Where is it?”

Types of Spatial Data

1. Vector Data

   • Built from coordinates (x, y).

   • Features can be represented as:

     • Points – e.g., schools, trees.

     • Lines – e.g., rivers, roads.

     • Polygons – e.g., country boundaries, lakes.

   • Best for discrete features with clear boundaries.

2. Raster Data

   • Made up of pixels (grid cells), each with a value.

   • Ideal for continuous data such as elevation, temperature, or satellite imagery.

3. TIN (Triangulated Irregular Network)

   • Uses triangles to model continuous surfaces.

   • Especially useful for representing terrain and slope.

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What is Attribute Data?

While spatial data tells us where things are, attribute data tells us what they are, how much, and when. This is the descriptive side of GIS.

Categories of Attribute Data

1. Nominal – Names or labels (e.g., soil type, land use class).

2. Ordinal – Ordered categories (e.g., low, medium, high risk).

3. Interval – Numeric values with equal spacing but no true zero (e.g., temperature in °C).

4. Ratio – Numeric values with a true zero (e.g., population, distance).

5. Cyclic – Data that repeats in cycles (e.g., time of day, wind direction).

6. Counts and Amounts – Totals and quantities (e.g., number of hospitals, rainfall amount).

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Geometry Types in Vector Data

Vector data is further organized into geometry types:

• Point – Single location (a well).

• MultiPoint – Multiple point locations.

• LineString – Connected points forming a line (a road).

• MultiLineString – Multiple lines.

• Polygon – An enclosed shape (a lake, a district).

• MultiPolygon – Multiple polygons (country boundaries with islands).

• Geometry Collection – A mix of geometry types.