11  Symbology

11.1 Introduction

Shapefiles (Chapter 8) are a standard format for storing geographic data.

Shapefiles generally come in three types: points ●; lines ━; and polygons ▭▯.

12 Symbology

Symbology is the idea of using shapefile attributes to encode quantitative (continuous) or qualitative (discrete; categorical) information, such as income or program participation.

Symbology
Shapefile Type Symbology
Points Size: ● ● ●
Discrete Color: ● ● ●
Continuous Color: ● ● ●
Lines Width: ━ ━ ━
Discrete Color: ━ ━ ━
Continuous Color: ━ ━ ━
Pattern: ━ ┅
Polygons Discrete Color: ■ ■ ■
Continuous Color: ■ ■ ■
Pattern: ■ ▤ ▦

Color palettes can be either qualitative (discrete; categorical) or quantitative (continuous) in nature.

Note

The code used to generate these color palettes is shown for reference, but may not be the exact code needed when these colors are used in maps.

12.0.1 Base R

Show the code 
barplot(rep(1,10), col = heat.colors(10), axes = FALSE)

Heatmap Colors

Heatmap Colors
Show the code 
barplot(rep(1,10), col = topo.colors(10), axes = FALSE)

Topographical Colors

Topographical Colors
Show the code 
barplot(rep(1,10), col = terrain.colors(10), axes = FALSE)

Terrain Colors

Terrain Colors

12.0.2 RColorBrewer

Show the code 
library(RColorBrewer) # A library for color palettes
Show the code 
display.brewer.pal(name = "Blues", n = 9)

Blues Palette

Blues Palette
Show the code 
display.brewer.pal(name = "Spectral", n = 9)

Spectral Palette

Spectral Palette
Show the code 
display.brewer.pal(name = "Set1", n = 9)

Set1 Palette

Set1 Palette

12.0.3 Viridis

More details can be found at https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html

Show the code 
library(scales)
Show the code 
show_col(viridis_pal()(9), 
         ncol = 9, # 9 columns
         labels = FALSE) # no labels

Viridis Palette

Viridis Palette

13 Demonstration Map

Show the code 
library(ggplot2) # graphing and mapping

library(sf) # simple features

city_boundary <- read_sf("./shapefiles/AA_City_Boundary/AA_City_Boundary.shp")

clients <- read_sf("./shapefiles/clients/clients.shp")

ggplot(city_boundary) +
  geom_sf(color = "darkgrey", alpha = .5) +
  geom_sf(data = clients,
          aes(color = program), # color = program
          size = 3, # size
          alpha = .75) + # transparency
  labs(title = "Ann Arbor",
       subtitle = "Locations of Simulated Clients",
       caption = "Point Color Indicates Program") +
  scale_color_viridis_d(name="Program") + # nice viridis colors
  theme_minimal() +
  theme(plot.title = element_text(size = rel(2)), 
        axis.text = element_text(size = rel(.5)),
        legend.position = "bottom")