Geographic Information Systems (GIS) primarily use two categories of digital data: 1) Raster Data and 2) Vector Data.
Raster Data portrays real world data as a matrix or a grid of cells (see Figure #1). Raster data is very good at storing continuous data (for example: precipitation, temperature, and elevation). Each cell stores information numerically, usually between 0-255 and has a geographical location. A weakness of raster data is that the cells are squares and most real world information doesn’t fit into a perfect square(See Figure#2). So sometimes a map made with satellite imagery will either underestimate or overestimate a land cover type.
Vector Data portrays real world data as a point, line or polygon. Vector data is very good at storing discrete data (for example: political boundaries, rivers, lakes, land parcels, and streets). Each point, line, or polygon is called a feature and has a unique ID# (see Figure #2). Attribute information can be added to each feature in geographical space. A weakness of vector data is that it sometimes needs great amounts of processing power to run a complex analysis.
Click to view an example of vector data (point features):
Click to view an example of vector data (polygon features):
Click to view an example of vector data (Line features):