The goal of arcgeocoder is to provide a lightweight interface for geocoding addresses and reverse geocoding locations through the ArcGIS REST API Geocoding Service.
The full site with examples and vignettes is available at https://dieghernan.github.io/arcgeocoder/.
Why arcgeocoder?
arcgeocoder provides a lightweight interface for geocoding and reverse geocoding with the ArcGIS REST API service. It accesses the ArcGIS REST API with fewer dependencies, such as curl. In some situations, curl may not be available or accessible, so arcgeocoder uses base functions to overcome this limitation.
The interface of arcgeocoder is designed to make the API features easier to access. The API endpoints used by arcgeocoder are findAddressCandidates and reverseGeocode, which can be accessed without an API key.
Recommended packages
Other packages are more mature and provide similar features:
- tidygeocoder (Cambon et al. 2021). Provides an interface to ArcGIS, Nominatim (OpenStreetMap), Google, TomTom, Mapbox and other services for geocoding and reverse geocoding.
- nominatimlite (Hernangómez 2024). Similar to arcgeocoder but using data from OpenStreetMap through the Nominatim API service.
Usage
Geocoding and reverse geocoding
Note: examples adapted from the tidygeocoder package.
In this first example, we geocode a few addresses using the arc_geo() function. Note that arcgeocoder works without additional setup, and you do not need to provide an API key to start geocoding.
library(arcgeocoder)
library(dplyr)
# Create a data frame 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$addr,
lat = "latitude",
long = "longitude",
progressbar = FALSE
)Only a few fields are returned from the geocoding service in this example, but full_results = TRUE can be used to return all data from the geocoder service.
| query | latitude | longitude | address | score | x | y | xmin | ymin | xmax | ymax | wkid | latestWkid |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1600 Pennsylvania Ave NW, Washington, DC | 38.89768 | -77.03655 | 1600 Pennsylvania Ave NW, Washington, District of Columbia, 20500 | 100 | -77.03655 | 38.89768 | -77.03755 | 38.89668 | -77.03555 | 38.89868 | 4326 | 4326 |
| 600 Montgomery St, San Francisco, CA 94111 | 37.79516 | -122.40273 | 600 Montgomery St, San Francisco, California, 94111 | 100 | -122.40273 | 37.79516 | -122.40373 | 37.79416 | -122.40173 | 37.79616 | 4326 | 4326 |
| 233 S Wacker Dr, Chicago, IL 60606 | 41.87867 | -87.63587 | 233 S Wacker Dr, Chicago, Illinois, 60606 | 100 | -87.63587 | 41.87867 | -87.63687 | 41.87767 | -87.63487 | 41.87967 | 4326 | 4326 |
To perform reverse geocoding (obtaining addresses from geographic coordinates), we can use the arc_reverse_geo() function. The arguments are similar to the arc_geo() function, but now we specify the input data columns with the x and y arguments. The dataset used here is from the geocoder query above. The single-line address is returned in the column named by address.
reverse <- arc_reverse_geo(
x = lat_longs$longitude,
y = lat_longs$latitude,
address = "address_found",
progressbar = FALSE
)| x | y | address_found |
|---|---|---|
| -77.03655 | 38.89768 | White House, 1600 Pennsylvania Ave NW, Washington, DC, 20500, USA |
| -122.40273 | 37.79516 | Chess Ventures, 600 Montgomery St, San Francisco, CA, 94111, USA |
| -87.63587 | 41.87867 | The Metropolitan, 233 South Wacker Drive, Chicago, IL, 60606, USA |
It is also possible to search for specific locations within or near a reference area or location using category filtering. See more information in the documentation for the arc_categories data object.
In the following example, we look for food-related points of interest (POIs), such as restaurants, coffee shops and bakeries, near the Eiffel Tower in France.
library(ggplot2) # For plotting.
# Step 1: Locate the Eiffel Tower using a multi-field query.
eiffel_tower <- arc_geo_multi(
address = "Tour Eiffel",
city = "Paris",
countrycode = "FR",
langcode = "FR",
custom_query = list(outFields = "LongLabel")
)
# Display results.
eiffel_tower |>
select(lon, lat, LongLabel)
#> # A tibble: 1 × 3
#> lon lat LongLabel
#> <dbl> <dbl> <chr>
#> 1 2.29 48.9 Tour Eiffel, 3 Rue de l'Université, 75007, 7e Arrondissement, Paris, Île-de…
# Use `lon` and `lat` to boost the search with `category = "Food"`.
food_eiffel <- arc_geo_categories(
"Food",
x = eiffel_tower$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 arcgeocoder",
color = "Type of place",
x = "",
y = "",
caption = "Data from the ArcGIS REST API service"
)