Geospatial data is data with geographic location associated with it, i.e. map data. There are two kinds of spatial data, raster data and vector data. Each has properties that make it better for representing different information.

Raster Data

Geospatial data best represented in raster format generally has one value at every point. The area to be represented is split up into a grid, with each grid cell containing a value. Elevation, temperature, precipitation are examples of data generally represented as raster.

Vector Data

Geospatial data best represented in vector format can be represented as points, lines, or polygons.

Point: Points represent a single location on a 2 dimensional surface.
Depending on the scale, different types of data are appropriate to be represented as points. At a very small scale (think of from a very great distance), a city might be represented as a single point. Species occurrences are usually represented as points.

Line: Lines are made up of multiple points, joined. Roads and rivers are usually represented as rivers.

Polygon: Polygons are made up of multiple points or lines, joined to define a discrete area. At a larger scale (zoomed in), a city, river, or street might be represented as a polygon. Administrative boundaries, like country, state, or other geo-political units are examples of polygon data.


Large scale maps refer to maps of a small area with a large amount of detail.
The ratio between distance on the map to distance on the ground is very large.
For example a detailed map of a city might be at 1:5000, meaning that 1 unit on the map (i.e. centimeter) equals 5000 units on the ground (5000 centimeters).
A smaller scale map, for example a regional map used for land-management, might be at a scale of 1:100,000 (1 centimeter = 1 kilometer).

Small scale maps are generally used for mapping large areas. The ratio of the distance on the map to the distance on the ground is much smaller. For example, a map of the country of Indonesia might be at the ratio of 1:2,000,000.

Sample Geospatial Data resources

  • [World borders] (

  • [Global administrative boundaries]

  • [Natural earth data] (