Introduction to Spatial Data in R

Course Objectives

By the end of this course, you should be able to:

• Develop reproducible workflows for manipulating, visualizing, and analyzing spatial data.
• Understand the unique components of spatial data and how those components fit in R’s data structures.
• Articulate the different formats of spatial data and identify which R packages are suited to each type.
• Describe why space matters for many social and ecological questions
• Implement a variety of descriptive and statistical spatial analyses.
• Leverage functional programming to automate and expedite spatial data operations.

Code of Conduct

We are dedicated to providing a welcoming and supportive environment for all people, regardless of background or identity. However, we recognise that some groups in our community are subject to historical and ongoing discrimination, and may be vulnerable or disadvantaged. Membership in such a specific group can be on the basis of characteristics such as gender, sexual orientation, disability, physical appearance, body size, race, nationality, sex, colour, ethnic or social origin, pregnancy, citizenship, familial status, veteran status, genetic information, religion or belief, political or any other opinion, membership of a national minority, property, birth, age, or choice of text editor. We do not tolerate harassment of participants on the basis of these categories, or for any other reason.

If you are being harassed, notice that someone else is being harassed, or have any other concerns, please contact the Boise State Dean of Students office.

Thank you for helping make this a welcoming, friendly community for all.