due.Date | link |
---|---|
September 17, 2024 | Wiki on Environmental Justice |
September 17, 2024 | EJScreen Exploration |
September 19, 2024 | CalEnviroScreen Exploration |
September 19, 2024 | Bullard et al., 2014 - Check Canvas Files |
September 24, 2024 | ProPublica - Sacrifice Zones |
September 26, 2024 | Importing Data in R - RMRWR - Chapter 5.1 and 5.2 |
11 Assignments for Unit 2 - EJ
This includes the list of assignments for Unit 2 - Environmental Justice
11.1 Graded Assignment - EJ Visualization
Choose an environmental justice dataset. Three options we discuss in class are:
- CalEnviroScreen - WARNING - 20+Mb zip file
- EPA EJScreen - WARNING - 480+ Mb zip file
- CDC & ATSRD EJI tool - state level downloads - pick geoJSON format for maps!
- CEJST WARNING - 357 Mb zip file
If data downloads are not something you are comfortable with, it is perfectly ok to use the in-class SoCalEJ
dataset we have used as an example for in-class coding assignments.
The assignment is to create a new visualization or remix of a visualization using some of the data from the chosen EJ dataset. Visualization options include:
- Leaflet map(s)
- ggplot geom_sf map(s)
- ggplot figure(s) using some other geom (boxplot, point, bar, histogram)
- Some combination of 1, 2, and 3
Points will be awarded for successfully generating a unique visualization, for having made four distinct visualization choices that are different from the standard tool, and for documenting those four unique features in the accompanying email, or as commented text within the .R script
file you submit as part of the assignment. Note, the goal is to make an attractive figure, not a super ugly one. Choices that do not aid in improving the feature for the audience will not be considered on point. For example, making the font enormous or tiny is a negative feature.
In other words, the goal is to make a better visualization, not just a different visualization. When describing the four feature changes, describe in one sentence why the features improve the visualization.
Assignment is currently due October 1st, 2024 at the beginning of class (9:45 AM). Please send the .R script
and an exported visualization via email. This assignment is worth 150 points. Coding style will not be graded. Scripts will be used to reproduce the figure on my local machine - deviations between code and exported figure will likely result in deducted points.