Session_9_Lab_3_IT

Introduction

In this lab I explored the spatial data assembled in Labs 1 and 2.
For Lab 1, I produced a final dataset of NYC ZIP code areas with COVID‑19 data (see RPubs 1284677) and for Lab 2, I aggregated additional demographic data from ACS (see RPubs 1287481).

In this assignment, I used the final aggregated dataset (nyc_zip_final) to:

1. Create two high-quality static maps:
   • A choropleth map of COVID‑19 positive cases.
   • A choropleth map of elderly population (65+).
2. Create a multi-map figure, arranged side by side, to explore the potential relationship between COVID‑19 cases and elderly population (with graticules and labels).
3. Build an interactive web map using leaflet for the COVID-19 data.

---

Setup

load("D:/Session_7/R-Spatial_I_Lab/nyc_zip_final.RData")

p_covid <- ggplot(nyc_zip_final) +
  geom_sf(aes(fill = Positive)) +
  scale_fill_viridis_c(option = "plasma", direction = -1) +
  labs(
    title = "NYC COVID-19 Positive Cases by ZIP Code",
    fill = "Positive Cases"
  ) +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5)) +
  coord_sf(clip = "off") +
  ggspatial::annotation_north_arrow(
    location = "tr",
    which_north = "true",
    style = ggspatial::north_arrow_fancy_orienteering
  )

p_elderly <- ggplot(nyc_zip_final) +
  geom_sf(aes(fill = elderly_population)) +
  scale_fill_viridis_c(option = "viridis", direction = -1) +
  labs(
    title = "NYC Elderly Population (65+)",
    fill = "Elderly Population"
  ) +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5)) +
  coord_sf(clip = "off") +
  ggspatial::annotation_north_arrow(
    location = "tr",
    which_north = "true",
    style = ggspatial::north_arrow_fancy_orienteering
  )

print(p_covid)

print(p_elderly)

p1 <- ggplot(nyc_zip_final) +
  geom_sf(aes(fill = Positive)) +
  scale_fill_viridis_c(option = "plasma", direction = -1) +
  labs(title = "COVID-19 Positive Cases", fill = "Positive") +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5),
        axis.text.x = element_text(angle = 45, hjust = 1)) +
  coord_sf(clip = "off") +
  ggspatial::annotation_north_arrow(location = "tr", which_north = "true",
                                    style = ggspatial::north_arrow_fancy_orienteering)

p2 <- ggplot(nyc_zip_final) +
  geom_sf(aes(fill = elderly_population)) +
  scale_fill_viridis_c(option = "viridis", direction = -1) +
  labs(title = "Elderly Population (65+)", fill = "Elderly") +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5),
        axis.text.x = element_text(angle = 45, hjust = 1)) +
  coord_sf(clip = "off") +
  ggspatial::annotation_north_arrow(location = "tr", which_north = "true",
                                    style = ggspatial::north_arrow_fancy_orienteering)

combined <- ggarrange(p1, p2, ncol = 2, nrow = 1)

ggsave("D:/Spring2025Hunter/Session_8/combined_map.png", plot = combined, width = 12, height = 8, dpi = 300)

Combined Map

nyc_zip_final_no_na <- nyc_zip_final[!is.na(nyc_zip_final$Positive), ]
nyc_zip_final_no_na$Positive <- as.numeric(nyc_zip_final_no_na$Positive)

pal <- colorNumeric(
  palette = viridisLite::plasma(256, direction = -1),
  domain  = nyc_zip_final_no_na$Positive
)

leaflet(nyc_zip_final_no_na %>% st_transform(4326)) %>%
  addProviderTiles("CartoDB.Voyager") %>%
  addPolygons(
    fillColor   = ~pal(Positive),
    fillOpacity = 0.7,
    color       = "grey",
    weight      = 1,
    popup       = ~paste("<strong>ZIP Code:</strong>", ZIPCODE, "<br>",
                         "<strong>Positive Cases:</strong>", Positive)
  ) %>%
  addLegend(
    pal      = pal,
    values   = nyc_zip_final_no_na$Positive,
    title    = "Positive COVID-19 Cases",
    position = "bottomright"
  ) %>%
  addScaleBar(
    position = "bottomleft",
    options  = scaleBarOptions(imperial = FALSE)
  )