Lab 3 Tutorial | PAF 516

What You Will Build

In this lab you will integrate external point data (environmental facility locations) with your block-group-level economic hardship index. You will align coordinate reference systems, compute the distance from every block group to its nearest facility, overlay facility locations on the hardship map, and test the environmental justice hypothesis: do lower-income communities sit disproportionately close to environmental hazards? You will finish with a multi-buffer comparison that shows how the answer depends on the distance threshold you choose (the Uncertain Geographic Context Problem, UGCoP).

The tutorial walks through every step with fully working code. Knit it first to see the finished product, then go back and run chunk by chunk to understand how it works.

Learning Objectives

Load external point data and convert it to sf spatial objects with an aligned CRS
Compute distance from block group centroids to the nearest facility with st_distance()
Overlay facility locations on a hardship choropleth and map distance to nearest facility
Test the environmental justice hypothesis with a distance-decay analysis across distance bands
Assess buffer-distance sensitivity (UGCoP) by comparing 0.5-, 1-, and 2-mile buffers

Before You Begin

1 — File and Folder Setup

Create this folder structure before downloading anything. Move the downloaded .qmd into PAF516/Lab3/ before opening it in RStudio.

PAF516/
  Lab1/  Lab2/  ...
  Lab3/
    Lab3_Tutorial.qmd            ← downloaded tutorial (do not edit)
    Lab3_Tutorial.html           ← auto-generated when you knit
    Lab3_Assignment_Howell.qmd   ← your renamed assignment copy
    Lab3_Assignment_Howell.html  ← submit this to Canvas
  Lab4/  Lab5/  ...

2 — Install Packages (Run Once)

Do this before knitting

Open Lab3_Tutorial.qmd in RStudio
Click inside the packages chunk (labeled #| label: packages)
Press Cmd+Return (Mac) or Ctrl+Enter (PC) to run just that chunk
Wait — first run downloads and installs packages and may take 5–10 minutes
After it finishes, future knits will be fast — the renv block only runs once automatically

What is renv?

renv records the exact version of every package used so that code that works today still works next semester.

3 — Census API Key

The lab pulls live data from the Census Bureau. If you don't have a key yet:

Register free at api.census.gov/data/key_signup.html
Check email for your key (arrives within a few minutes)
In the RStudio console run: census_api_key("YOUR_KEY_HERE", install = TRUE)
Restart R: Session → Restart R

Running the Tutorial

Option A — Knit First (Recommended)

Click the Render button (blue arrow, top of editor) or press Cmd+Shift+K / Ctrl+Shift+K. This produces Lab3_Tutorial.html with all results — facility overlay maps, the distance-decay table and charts, and the multi-buffer comparison. Review the output to see what the completed analysis looks like.

Option B — Run Chunk by Chunk (Best for Learning)

Place your cursor inside any code chunk and press the run shortcut. Output appears inline. Fix any errors before moving on. This is how you understand what each step does.

Action	Mac	PC
Run current chunk	`Cmd+Return`	`Ctrl+Enter`
Run all chunks above	`Cmd+Option+P`	`Ctrl+Alt+P`
Knit / Render	`Cmd+Shift+K`	`Ctrl+Shift+K`

What's Inside

Step	What It Does
Step 1	Pull Maricopa County block group data from the 2015–2019 ACS
Step 2	Build the 5-variable economic hardship index with z-score standardization
Step 3	Load external point data (environmental facility locations)
Step 4	Convert point data to `sf` and align coordinate reference systems
Step 5	Compute distance from each block group centroid to the nearest facility with `st_distance()`
Step 6	Facility overlay map and distance-to-nearest-facility choropleth
Step 7	Distance-decay analysis — mean hardship and poverty by distance band (the EJ finding)
Step 8	Multi-buffer UGCoP comparison — inside vs. outside 0.5-, 1-, and 2-mile buffers

Download

Lab 3 Tutorial File

Download Lab3_Tutorial.qmd

Right-click → Save Link As. Save directly to your PAF516/Lab3/ folder. Do not open in the browser.