19  Mapping With leaflet

19.1 Call Libraries

library(leaflet) # web based maps

library(sf) # simple (spatial) features

library(readr) # import csv

library(dplyr) # data wrangling

library(here) # where am I?

library(pander) # nice tables

# setwd(here()) # set the working directory

19.2 Get Simulated Client Data

clients <- read_csv("./location-data/clients.csv")

pander(head(clients)) # top of client data

Table continues below

ID	age	gender	race_ethnicity	family_income	program
2892	23	Male	African American	42359	Program B
1971	39	Female	Asian American	66500	Program C
4728	26	Female	Asian American	52726	Program C
1020	24	Male	Latinx	52911	Program D
4429	36	Female	Asian American	50287	Program C
3136	33	Male	African American	45570	Program C

mental_health_T1	mental_health_T2	latitude	longitude
95.25	106.8	42.16	-83.6
82.64	96.3	42.29	-83.88
80.49	98.72	42.14	-83.78
93.82	91.67	42.24	-83.68
83.37	99.69	42.18	-83.64
75.28	92.9	42.21	-83.7

19.3 Only Clients In Ann Arbor Area

clients <- clients %>% 
  filter(latitude <= 42.35 &
           latitude >= 42.2 &
           longitude >= -83.8 &
           longitude <= -83.65)

19.4 Read in Shapefiles

parks <- read_sf("./shapefiles/AA_Parks/AA_Parks.shp")

university <- read_sf("./shapefiles/AA_University/AA_University.shp")

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

20 Transform CRS

“Map projections try to portray the surface of the earth or a portion of the earth on a flat piece of paper or computer screen. A coordinate reference system (CRS) then defines, with the help of coordinates, how the two-dimensional, projected map in your GIS is related to real places on the earth. The decision as to which map projection and coordinate reference system to use, depends on the regional extent of the area you want to work in, on the analysis you want to do and often on the availability of data.” From qgis.org

see https://stackoverflow.com/questions/66471147/how-to-plot-sp-object-as-sf-in-r-leaflet

university <- st_transform(university, 4326) # transform CRS

parks <- st_transform(parks, 4326) # transform CRS

city_boundary <- st_transform(city_boundary, 4326) # transform CRS

20.1 Leaflet Map

20.1.1 Color Palette

pal <- colorFactor(c("red", "blue", "orange", "green"), 
                   domain = levels(as.factor(clients$program)))

20.1.2 Map

leaflet(clients) %>%
  setView(lng = mean(clients$longitude), 
          lat = mean(clients$latitude), 
          zoom = 12) %>% 
  # addTiles() %>% # Open StreetMap
  addProviderTiles(providers$CartoDB.Positron) %>%
  addCircleMarkers(~longitude, 
             ~latitude, 
             popup = ~paste("Client ID:", as.character(ID)), 
             label = ~paste("Client ID:", as.character(ID)),
             color = ~pal(program),
             clusterOptions = markerClusterOptions()) %>%
  addLegend("bottomright", 
            pal = pal, 
            values = ~program,
            title = "Program") %>%
  # addPolygons(data = parks, color = "green") %>%
  # addPolygons(data = university, color = "blue") %>%
  addPolygons(data = city_boundary, 
              color = "red",
              fillOpacity = 0.0)