Spatial Data Integration & Environmental Justice

After knitting, review the Step 7–8 charts and answer the following two parts:

• Distance-decay: Describe the pattern in Step 7. Does mean hardship decrease as distance from facilities increases? Is the pattern strong or weak? Are there any unexpected reversals?
• EJ interpretation: Do the maps and distance-decay chart support the environmental justice hypothesis — that lower-income communities bear disproportionate proximity to environmental hazards? Cite specific numbers from the decay table in your answer.

Replace the placeholder text in the Q1 section. A few sentences per bullet is sufficient.

Re-run the Step 7 distance-decay analysis with finer distance bands: < 0.25 mi, 0.25–0.5 mi, 0.5–1 mi, 1–2 mi, > 2 mi.

• Two scaffold chunks are provided at the end of the file: q2-fine-bands and q2-decay-plot
• Copy the cbg_decay and decay_summary code from Step 7, then change the breaks in cut() to c(0, 0.25, 0.5, 1.0, 2.0, Inf) and update the labels
• Regenerate the hardship and poverty decay bar charts using the new summary

Answer the following three parts:

• Decay comparison: How does the finer-band pattern (Q2) compare to the original 5-band version (Step 7)? Did breaking < 0.5 mi into two sub-bands reveal anything new about the very nearest block groups?
• UGCoP: Look at the multi-buffer comparison table from Step 8. Is the gap between inside and outside buffer consistent across the three distances (0.5, 1.0, 2.0 miles), or does it shrink or change at one threshold? What does this tell you about the Uncertain Geographic Context Problem?
• Policy recommendation: If you were advising a city agency on which block groups to prioritize for environmental remediation funding, what buffer distance would you recommend — and why? Drawing on Kwan (2012) and Maantay (2002), how would you defend that choice?