13  Assignments for Unit 2 - EJ

This includes the list of assignments for Unit 2 - Environmental Justice

Table 13.1: Assignments from Unit 2
assignment due.Date link
Wiki on Environmental Justice February 8, 2023 1
EJScreen Exploration February 10, 2023 2
CalEnviroScreen Exploration February 10, 2023 3
Bullard et al., 2013 February 15, 2023 4
ProPublica - Sacrifice Zones February 17, 2023 5
Importing Data in R - RMRWR - Chapter 5.1 and 5.2 February 22, 2023 6
Map 2 or 3 planned warehouses February 24, 2023 7

13.1 Graded Assignment - EJ Visualization

Choose an environmental justice dataset. Three options we’ve discussed in class are:

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:

  1. Leaflet map(s)
  2. ggplot geom_sf map(s)
  3. ggplot figure(s) using some other geom (boxplot, point, bar, histogram)
  4. 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 March 1st, 2023 at the beginning of class (9:45 AM). Please send the .R script and an exported visualization via email. This assignment is worth 100 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.