In this lesson, you will learn to work with the following spatial data representation models:
- Feature data, which represents spatial features as points, lines and polygons and is best applied to discrete objects with defined shapes
and boundaries.
- 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.