Discrete Spatial variables

In this lesson, you will learn to work with the following spatial data representation models:

  1. Feature data, which represents spatial features as points, lines and polygons and is best applied to discrete objects with defined shapes and boundaries.
  2. Raster data represents imaged or continuous data. Each grid cell in a raster is a measured quantity. The most common source for raster dataset is a remote sensing image or aerial photograph. A discrete object can be stored in a raster dataset by assigning the identifier value to the grid cell.

Raster datasets excels in storing and working with continuous data, such as elevation data, pollution concentration and temperature.

Learning Objectives