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Example 1: sf objects

The following example shows how it is possible to create a nice static map with data retrieved with arcgeocoder and converting it to an sf object:

library(arcgeocoder)
library(dplyr)
library(sf) # spatial objects
library(ggplot2)
library(mapSpain) # sf objects of Spain

# McDonalds in Barcelona, Spain

mc <- arc_geo_multi("McDonalds",
  city = "Barcelona",
  region = "Catalonia", countrycode = "ES",
  category = "Food", limit = 50,
  custom_query = list(outFields = c("LongLabel", "Type,StAdd"))
)

# To sf
mc_sf <- st_as_sf(mc,
  coords = c("lon", "lat"),
  # here we have the wkid
  crs = mc$latestWkid[1]
)

bcn <- esp_get_munic(munic = "Barcelona") %>%
  st_transform(mc$latestWkid[1])

ggplot(bcn) +
  geom_sf() +
  geom_sf(data = mc_sf, color = "red")


# We can restrict the results to the bbox of BCN in the query
bbox <- st_bbox(bcn) %>% paste0(collapse = ",")
bbox
#> [1] "2.05362,41.32175,2.22717,41.46744"

mc2_sf <- arc_geo_multi("McDonalds",
  city = "Barcelona",
  region = "Catalonia", countrycode = "ES",
  category = "Food", limit = 50,
  custom_query = list(
    outFields = c("LongLabel", "Type", "StAdd"),
    searchExtent = bbox
  )
) %>%
  st_as_sf(coords = c("lon", "lat"), crs = mc$latestWkid[1])


ggplot(bcn) +
  geom_sf() +
  geom_sf(data = mc2_sf, color = "red")

Example 2: terra objects

We can add static map tiles thanks to maptiles package and tidyterra for plotting. The tiles themselves are represented here as terra objects:

library(maptiles)
library(tidyterra)

# Usually use crs 3857 for getting tiles
bcn_3857 <- st_transform(bcn, 3857)

osm_tiles <- get_tiles(bcn_3857, provider = "CartoDB.Positron", crop = TRUE)

ggplot() +
  geom_spatraster_rgb(data = osm_tiles, maxcell = Inf) +
  geom_sf(data = bcn, fill = NA, color = "black", linewidth = 1) +
  geom_sf(data = mc2_sf, color = "red") +
  coord_sf(crs = 3857) +
  labs(caption = "(c) OpenStreetMap contributors, (c) CARTO")

Session info

Details
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.4.1 (2024-06-14 ucrt)
#>  os       Windows Server 2022 x64 (build 20348)
#>  system   x86_64, mingw32
#>  ui       RTerm
#>  language en
#>  collate  English_United States.utf8
#>  ctype    English_United States.utf8
#>  tz       UTC
#>  date     2024-09-11
#>  pandoc   3.1.11 @ C:/HOSTED~1/windows/pandoc/31F387~1.11/x64/PANDOC~1.11/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package     * version date (UTC) lib source
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#>  highr         0.11    2024-05-26 [1] RSPM
#>  htmltools     0.5.8.1 2024-04-04 [1] RSPM
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#>  jquerylib     0.1.4   2021-04-26 [1] RSPM
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#>  KernSmooth    2.23-24 2024-05-17 [3] CRAN (R 4.4.1)
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#>  lifecycle     1.0.4   2023-11-07 [1] RSPM
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#> 
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#> 
#> ──────────────────────────────────────────────────────────────────────────────