Usage
Geocoding and reverse geocoding
Note: examples adapted from tidygeocoder package
In this first example we will geocode a few addresses using the
arc_geo() function. Note that arcgeocoder
works straight away, and you don’t need to provide any API key to start
geocoding!
library(arcgeocoder)
library(dplyr)
# create a dataframe with addresses
some_addresses <- tribble(
~name, ~addr,
"White House", "1600 Pennsylvania Ave NW, Washington, DC",
"Transamerica Pyramid", "600 Montgomery St, San Francisco, CA 94111",
"Willis Tower", "233 S Wacker Dr, Chicago, IL 60606"
)
# geocode the addresses
lat_longs <- arc_geo(some_addresses$addr, lat = "latitude", long = "longitude")
#>
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|==================================================| 100%Only a few fields are returned from the geocoder service in this
example, but full_results = TRUE can be used to return all
of the data from the geocoder service.
| query | latitude | longitude | address | score | x | y | xmin | ymin | xmax | ymax | wkid | latestWkid |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1600 Pennsylvania Ave NW, Washington, DC | 38.89768 | -77.03655 | 1600 Pennsylvania Ave NW, Washington, District of Columbia, 20500 | 100 | -77.03655 | 38.89768 | -77.03755 | 38.89668 | -77.03555 | 38.89868 | 4326 | 4326 |
| 600 Montgomery St, San Francisco, CA 94111 | 37.79519 | -122.40279 | 600 Montgomery St, San Francisco, California, 94111 | 100 | -122.40279 | 37.79519 | -122.40379 | 37.79419 | -122.40179 | 37.79619 | 4326 | 4326 |
| 233 S Wacker Dr, Chicago, IL 60606 | 41.87889 | -87.63602 | 233 S Wacker Dr, Chicago, Illinois, 60606 | 100 | -87.63602 | 41.87889 | -87.63702 | 41.87789 | -87.63502 | 41.87989 | 4326 | 4326 |
To perform reverse geocoding (obtaining addresses from geographic
coordinates), we can use the arc_reverse_geo() function.
The arguments are similar to the arc_geo() function, but
now we specify the input data columns with the x and
y arguments. The dataset used here is from the geocoder
query above. The single line address is returned in a column named by
the address.
reverse <- arc_reverse_geo(
x = lat_longs$longitude,
y = lat_longs$latitude,
address = "address_found"
)
#>
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|==================================================| 100%| x | y | address_found |
|---|---|---|
| -77.03655 | 38.89768 | White House, 1600 Pennsylvania Ave NW, Washington, DC, 20500, USA |
| -122.40279 | 37.79519 | Mbia Insurance Corporation, 600 Montgomery St, San Francisco, CA, 94111, USA |
| -87.63602 | 41.87889 | Liberty Hands Cleaning, 233 S Wacker Dr, Ste 1011, Chicago, IL, 60606, USA |
It is possible also to search for specific locations within or near a
reference are or location using category
filtering. See more information in the documentation of the data
base arc_categories.
In the following example we would look for POIs related with food (i.e. Restaurants, Coffee Shops, Bakeries) near the Eiffel Tower in France.
library(ggplot2) # For plotting
# Step 1: Locate Eiffel Tower, using multifield query
eiffel_tower <- arc_geo_multi(
address = "Tour Eiffel",
city = "Paris",
countrycode = "FR",
langcode = "FR",
custom_query = list(outFields = "LongLabel")
)
# Display results
eiffel_tower %>%
select(lon, lat, LongLabel)
#> # A tibble: 1 × 3
#> lon lat LongLabel
#> <dbl> <dbl> <chr>
#> 1 2.29 48.9 Tour Eiffel, 3 Esplanade des Ouvriers de la Tour Eiffel, 75007, 7e Arrondissement, …
# Use lon,lat to boots the search and using category = Food
food_eiffel <- arc_geo_categories("Food",
x = eiffel_tower$lon,
y = eiffel_tower$lat,
limit = 50, full_results = TRUE
)
# Plot by Food Type
ggplot(eiffel_tower, aes(x, y)) +
geom_point(shape = 17, color = "red", size = 4) +
geom_point(data = food_eiffel, aes(x, y, color = Type)) +
labs(
title = "Food near the Eiffel Tower",
subtitle = "Using arcgecoder",
color = "Type of place",
x = "",
y = "",
caption = "Data from ArcGIS REST API services"
)
arcgeocoder and r-spatial
See additional articles showing how arcgeocoder can be use in combination with leaflet to create dynamic maps and with sf and terra to create static maps.