Time: 30 minutes
Purpose: In this lesson we will introduce some of the key concepts associated with spatial data including:
We will also define raster vs. vector data structures.
Background: Often we need to use spatial data in our analysis - that is data that correspond to some x,y (and z) location on the Earth. however, not all spatial data are created the same. understanding the basic foundations of working with spatial data will save you a lot of time when it comes to processing the data in tools like R, QGIS and python!
At the end of this 30 minute overview you will be able to:
R
packages that can be used to work with spatial data.It may be a bit of extra effort at the beginning to learn a tool like R. However, the payoff is large once you learn the basic skills to support task automation.
Specific to spatial data, R allows you to:
In this lesson we are going to learn the basics of working with spatial data in R. Some of you may think this is the boring stuff - however understanding these concepts will allow you to do just about anything that you want with spatial data in R!
Intro to vector data - EarthDataScience.org
Attributes of vector data