Geography 176A

library(tidyverse)
library(sf)
library(units)

library(USAboundaries)
library(rnaturalearth)

library(gghighlight)
library(ggrepel)
library(knitr)

Quesiton 1:

1.1 Define a Projection

For this lab we used the North American Equidistant Conic projection. This projection doesn’t have an EPSG code, so it’s written as follows:

eqdc = '+proj=eqdc +lat_0=40 +lon_0=-96 +lat_1=20 +lat_2=60 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs'

1.2 Get USA State Boundaries

US state boundaries were accessed with the following, as well as filtering so only the continental US is shown, and finally transformed the data to be suitable for distance measurements at the national scale.

conus = USAboundaries::us_states(resolution = "low") %>% 
  filter(!name %in% c("Alaska", "Hawaii", "District of Columbia", "Puerto Rico"))

conus <- st_transform(conus, eqdc)

1.3 Get Country Boundaries for Mexico, the United States of America, and Canada

World boundaries were accessed similarly to US boundaries and converted to simple feature format, then filtered to only show the three countries wanted and transformed to be suitable for distance measurements at the national scale.

world <- rnaturalearth::countries110 %>% 
  st_as_sf() %>% 
  filter(admin %in% c("United States of America", "Mexico", "Canada")) %>% 
  st_transform(eqdc)

1.4 Get City Locations From the CSV File

US city data was downloaded and read into the R script, then joined with CONUS data to remove cities from states outside the continental US, and finally transformed to be suitable for distance measurements at the national scale.

library(readr)
cities <- read_csv("../data/uscities.csv") %>% 
  right_join(conus, by = "state_name") %>% 
  st_as_sf(coords = c("lng", "lat"), crs = 4326) %>% 
  st_transform(eqdc)

Question 2:

2.1 Distance to USA Border (Coastline or national)(km)

US state boundaries were resolved to calculate the five cities with the greatest distance to the US border.

conus_b = st_union(conus) %>%
  st_cast("MULTILINESTRING")

cities = cities %>%
  mutate(dist_to_border = st_distance(cities, conus_b),
         dist_to_border = units::set_units(dist_to_border,"km"),
         dist_to_border = units::drop_units(dist_to_border))

cities5 = cities %>% 
  slice_max(dist_to_border, n=5) %>% 
  as_tibble() %>% 
  select(city, state_name, dist_to_border)

knitr::kable(cities5, 
             caption = "Top 5 Greatest Distance to Border",
             col.names = c("City", "State", "Greatest Distance to Border"))

Top 5 Greatest Distance to Border
City	State	Greatest Distance to Border
Dresden	Kansas	1012.317
Herndon	Kansas	1007.750
Hill City	Kansas	1005.147
Atwood	Kansas	1004.734
Jennings	Kansas	1003.646

2.2 Distance to States (km)

Here, US state boundaries are preserved in order to calculate the five cities with the greatest distance to a state border.

conus_s = st_combine(conus) %>%
  st_cast("MULTILINESTRING")

cities = cities %>%
  mutate(dist_to_stborder = st_distance(cities, conus_s),
         dist_to_stborder = units::set_units(dist_to_stborder,"km"),
         dist_to_stborder = units::drop_units(dist_to_stborder))

cities_st5 = cities %>% 
  slice_max(dist_to_stborder, n=5) %>% 
  as_tibble() %>% 
  select(city, state_name, dist_to_stborder)

knitr::kable(cities_st5, 
             caption = "Top 5 Greatest Distance to State Border",
             col.names = c("City", "State", "Greatest Distance to Border"))

Top 5 Greatest Distance to State Border
City	State	Greatest Distance to Border
Lampasas	Texas	308.9216
Bertram	Texas	302.8190
Kempner	Texas	302.5912
Harker Heights	Texas	298.8125
Florence	Texas	298.6804

2.3 Distance to Mexico

Mexico was filtered from the world bounaries in order to calculate the five US cities with the greatest distance to the Mexican border

mexico <- world %>% 
  filter(admin == "Mexico")

cities = cities %>%
  mutate(dist_to_mexico = st_distance(cities, mexico),
         dist_to_mexico = units::set_units(dist_to_mexico,"km"),
         dist_to_mexico = units::drop_units(dist_to_mexico))

cities_mx5 = cities %>% 
  slice_max(dist_to_mexico, n=5) %>% 
  as_tibble() %>% 
  select(city, state_name, dist_to_mexico)

knitr::kable(cities_mx5, 
             caption = "Top 5 Greatest Distance to Mexico Border",
             col.names = c("City", "State", "Greatest Distance to Border"))

Top 5 Greatest Distance to Mexico Border
City	State	Greatest Distance to Border
Caribou	Maine	3250.334
Presque Isle	Maine	3234.570
Calais	Maine	3134.348
Eastport	Maine	3125.624
Old Town	Maine	3048.366

2.4 Distance to Canada (km)

Canada is filtered from the world boundaries in order to calculate the five US cities with the greatest distance from the Canadian border.

canada <- world %>% 
  filter(admin == "Canada")

cities = cities %>%
  mutate(dist_to_canada = st_distance(cities, canada),
         dist_to_canada = units::set_units(dist_to_canada,"km"),
         dist_to_canada = units::drop_units(dist_to_canada))

cities_can5 = cities %>% 
  slice_max(dist_to_canada, n=5) %>% 
  as_tibble() %>% 
  select(city, state_name, dist_to_canada)

knitr::kable(cities_can5, 
             caption = "Top 5 Greatest Distance to Canada Border",
             col.names = c("City", "State", "Greatest Distance to Border"))

Top 5 Greatest Distance to Canada Border
City	State	Greatest Distance to Border
Guadalupe Guerra	Texas	2206.455
Sandoval	Texas	2205.641
Fronton	Texas	2204.784
Fronton Ranchettes	Texas	2202.118
Evergreen	Texas	2202.020

Question 3

3.1 Data

The 10 largest cities were pulled from the city data frame and used to create a map of the 10 largest US cities by population.

big_cities = cities %>%
  slice_max(population, n = 10)

ggplot() +
  geom_sf(data = world) +
  geom_sf(data = conus_s, linetype = "dotted") +
  geom_sf(data = conus_b, size = .75) +
  geom_sf(data = big_cities, col = "darkred", size = 1) +
  ggrepel::geom_label_repel(
    data = big_cities,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "10 Largest Cities")

3.2 City Distance From the Border

A map was created to show the distance to the US border, as well as the five cities with the greatest distance from the US border.

cities5sf = cities %>% 
  slice_max(dist_to_border, n=5)

ggplot() +
  geom_sf(data = cities, aes(color = dist_to_border)) +
  scale_color_gradient(high = "salmon", low = "skyblue3") +
  geom_sf(data = cities5sf) +
  ggrepel::geom_label_repel(
    data = cities5sf,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "City Distance From the Border")

3.3 City Distance From Nearest State

A map was created to show the distance to any state border, as well as the five cities with the greatest distance from any state border.

cities_st5sf = cities %>% 
  slice_max(dist_to_stborder, n=5)

ggplot() +
  geom_sf(data = cities, aes(color = dist_to_stborder)) +
  scale_color_gradient(high = "salmon", low = "skyblue3") +
  geom_sf(data = cities_st5sf) +
  ggrepel::geom_label_repel(
    data = cities_st5sf,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "City Distance From Nearest State")

3.4 Equidistance Boudary From Mexico and Canada

This map shows cities that are equidistant from both the Mexican and Canadian border, as well as the five cities with the greastest distance from the Mexican and Canadian border.

cities <- cities %>% 
  mutate(dist_to_mxcan = abs(dist_to_canada - dist_to_mexico))

cities_mxcan5 <- cities %>% 
  filter(dist_to_mxcan < 100) %>% 
  slice_max(population, n = 5)

ggplot() +
  geom_sf(data = cities, aes(color = dist_to_mxcan)) +
  scale_color_gradient(high = "salmon", low = "skyblue3") +
  gghighlight(dist_to_mxcan < 100) +
  geom_sf(data = cities_mxcan5) +
  ggrepel::geom_label_repel(
    data = cities_mxcan5,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "Equidistance Boudary From Mexico and Canada")

Question 4

4.1 Quantifing Border Zone

According to the ACLU, almost 2 out of 3 cities are within a 100 mile zone of the US border. A table was created to show the number of cities within this zone, as well as the number of people living in a city within the zone (also shown as a perentage). This data matches the data given by the ACLU.

border_pop <- cities %>% 
  filter(dist_to_border < 160) %>% 
  as_tibble() %>% 
  summarise(count = n(), population = sum(population))

total_pop <- cities %>% 
  as_tibble() %>% 
  summarise(count = n(), population = sum(population))

percent = border_pop$population / total_pop$population * 100

knitr::kable(tibble(border_pop$population, total_pop$population, percent), 
             caption = "Percent of Population Less Than 100 Miles From Border",
             col.names = c("Border Population", "Total Population", "Percent"),
             format.args = list(big.mark = ","))

Percent of Population Less Than 100 Miles From Border
Border Population	Total Population	Percent
254,717,441	391,924,266	64.9915

4.2 Mapping Border Zone

A map was created to highlight the cities within the 100 mile zone, in addition to the cities with the greatest population in each state within the zone.

ggplot() +
  geom_sf(data = (border_pop <- cities %>% 
                    filter(dist_to_border < 160)), aes(color = dist_to_border)) +
  scale_color_gradient(high = "darkred", low = "orange") +
  gghighlight(dist_to_border < 160) +
  geom_sf(data = (border_pop <- cities %>% 
                    filter(dist_to_border < 160) %>% 
                    group_by(state_name) %>% 
                    slice_max(population, n = 1))) +
  ggrepel::geom_label_repel(
    data = (border_pop <- cities %>% 
      filter(dist_to_border < 160) %>% 
      group_by(state_name) %>% 
      slice_max(population, n = 1)),
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "100 Mile Border Zone")

Geography 176A

Lab 03: Distances and the Border Zone

Bryn McGowan

Quesiton 1:

1.1 Define a Projection

For this lab we used the North American Equidistant Conic projection. This projection doesn’t have an EPSG code, so it’s written as follows:

1.2 Get USA State Boundaries

US state boundaries were accessed with the following, as well as filtering so only the continental US is shown, and finally transformed the data to be suitable for distance measurements at the national scale.

1.3 Get Country Boundaries for Mexico, the United States of America, and Canada

World boundaries were accessed similarly to US boundaries and converted to simple feature format, then filtered to only show the three countries wanted and transformed to be suitable for distance measurements at the national scale.

1.4 Get City Locations From the CSV File

US city data was downloaded and read into the R script, then joined with CONUS data to remove cities from states outside the continental US, and finally transformed to be suitable for distance measurements at the national scale.

Question 2:

2.1 Distance to USA Border (Coastline or national)(km)

US state boundaries were resolved to calculate the five cities with the greatest distance to the US border.

2.2 Distance to States (km)

Here, US state boundaries are preserved in order to calculate the five cities with the greatest distance to a state border.

2.3 Distance to Mexico

Mexico was filtered from the world bounaries in order to calculate the five US cities with the greatest distance to the Mexican border

2.4 Distance to Canada (km)

Canada is filtered from the world boundaries in order to calculate the five US cities with the greatest distance from the Canadian border.

Question 3

3.1 Data

The 10 largest cities were pulled from the city data frame and used to create a map of the 10 largest US cities by population.

3.2 City Distance From the Border

A map was created to show the distance to the US border, as well as the five cities with the greatest distance from the US border.

3.3 City Distance From Nearest State

A map was created to show the distance to any state border, as well as the five cities with the greatest distance from any state border.

3.4 Equidistance Boudary From Mexico and Canada

This map shows cities that are equidistant from both the Mexican and Canadian border, as well as the five cities with the greastest distance from the Mexican and Canadian border.

Question 4

4.1 Quantifing Border Zone

According to the ACLU, almost 2 out of 3 cities are within a 100 mile zone of the US border. A table was created to show the number of cities within this zone, as well as the number of people living in a city within the zone (also shown as a perentage). This data matches the data given by the ACLU.

4.2 Mapping Border Zone

A map was created to highlight the cities within the 100 mile zone, in addition to the cities with the greatest population in each state within the zone.