Geospatial Analysis with R

Fall 2025

Updated on: 2025-09-10

Instructor	Lyndon Estes
Teaching assistant	Elisabeth Tappert

Resources

• Syllabus
• Assessment Criteria
• Software installation
• Git/GitHub
• Known bugs and fixes

Links

• Helpful functions
• Cheatsheets

Course materials

The class materials were designed by Lyndon Estes and Lei Song.

• Unit 1 - Overview
  • Module 1 - Reproducibility and related R skills
  • Module 2 - R and R fundamentals
  • Module 3 - Data preparation and operation
  • Module 4 - Data manipulation and visualization
• Unit 2 - Overview
  • Module 1 - Vector data
  • Module 2a - Raster data, part 1
  • Module 2b - Raster data, part 2
• Potential Projects

Course content

Week 1 (Aug 25)

• Setup
• Class 1 slides
• Class 2 slides

Week 2 (Sept 3)

• Using git and Github; R packages;
• Class 3 slides

Week 3 (Sept 8)

• Continued setup work, RMarkdown, R ecosystem
• Assignment 1 due (Unit 1 Module 1)
• Class 4 slides
• Class 5 slides

Week 4 (Sept 15)

• R data structures, OOP, Environments, Control flow

Week 5 (Sept 22)

• R data structures, OOP, Environments, Control flow
• Assignment 2 due (Unit 1 Modules 2-3)

Week 6 (Sept 29)

• tidyverse, working with data
• regression, plotting

Week 7 (Oct 6)

• tidyverse, data manipulation
• Assignment 3 due (Unit 1 Module 4)

Week 9 (Oct 15)

• Working with vectors

Week 10 (Oct 20)

• More on vectors
• Assignment 4 due (Unit 2 Module 1)

Week 11 (Oct 27)

• Raster algebra, terrain, modeling

Week 12 (Nov 3)

• Assignment 5 (Unit 2 Module 2)
• Exam

Week 13-15 (Nov 10 onwards)

• Project Overview due (end week 13)
• Final Projects due Dec 15