Week | Date | Topic | Slides | Exercise |
---|---|---|---|---|
1 | Fri, Aug 30 | Getting started with spatial data using sf and the tidyverse | 📖 | 📝 |
2 | Fri, Sep 6 | Visualizing spatial data with ggplot2 | 📖 | 📝 |
3 | Fri, Sep 13 | Transforming data with dplyr | 📖 | 📝 |
4 | Fri, Sep 20 | Transforming spatial data attributes | 📖 | 📝 |
5 | Fri, Sep 27 | Applying spatial transformations and geometric operations using sf | 📖 | 📝 |
6 | Fri, Oct 4 | Tidying and joining spatial data | 📖 | 📝 |
7 | Fri, Oct 11 | Building functions in R and literate programming with Quarto | 📖 | 📝 |
8 | Fri, Oct 18 | Developing an exploratory data analysis with sf and the tidyverse | 📖 | — |
9 | Fri, Oct 25 | Editing OpenStreetMap and exploring OpenStreetMap data with the osmdata package | 📖 | — |
10 | Fri, Nov 1 | Exploring American Community Survey data with the tidycensus package | — | — |
11 | Fri, Nov 8 | Reading and writing spatial data files and services | 📖 | — |
12 | Fri, Nov 15 | Creating and managing spatial metadata | 📖 | — |
13 | Fri, Nov 22 | Project check-in meetings (no class) | — | — |
14 | Fri, Nov 29 | Review and work session | — | — |
15 | Fri, Dec 6 | Final project presentations | — | — |
— | Sat, Dec 14 | Due: Final project repository | — | — |
GES 668: Building Spatial Datasets (Fall 2024)
In this course, students learn how to look critically at spatial data and use the R programming language to transform, visualize, and create spatial datasets. Working with open-source tools, reproducible methods, and real world data, students develop skills in the fundamentals of reading and wrangling spatial data with the sf and tidyverse family of R packages.