arcgisgeocode is a high-performance R package providing comprehensive access to ArcGIS geocoding services. Built with Rust and designed for both interactive applications and enterprise workflows, it offers the complete suite of ArcGIS geocoding capabilities.
🌍 Complete Geocoding Suite:
- Address suggestion: Suggest addresses candidates with
find_address_candidates() - Reverse geocoding: Coordinates to addresses with
reverse_geocode() - Batch geocoding: Bulk processing with
geocode_addresses() - Interactive suggestions: Real-time autocomplete with
suggest_places()
Integrations:
- ArcGIS Online
- ArcGIS Enterprise
- Custom locators (e.g. StreetMap Premium) note—does not support locator files
🚀 High—Performance:
- Vectorized operations across all geocoding functions
- Rust-powered JSON processing
- Parallel HTTP requests using
httr2for concurrent geocoding operations - Configurable batching for large datasets
{arcgisgeocode} is part of the {arcgis} metapackage, which provides
the complete R-ArcGIS Bridge toolkit. For most users, installing the
metapackage is recommended:
# install from CRAN
install.packages("arcgis")You can also install {arcgislayers} individually from CRAN:
install.packages("arcgisgeocode")To install the development version:
pak::pak("r-arcgis/arcgisgeocode")By default, the ArcGIS World
Geocoder
will be used. This geocoding server provides public access to the
/findAddressCandidates,
/reverseGeocode,
and
/suggest
endpoints made available via the find_address_candidates(),
reverse_geocode(), and suggest_places() functions respectively.
The batch geocoding endpoint
/geocodeAddresses
is available via geocode_addresses(). However, this requires the use
of an authorization token and may consume credits.
Refer to the ArcGIS World Geocoder official documentation for additional information on use restrictions and licensing. For example, a valid token is required to store the results of geocoding transactions.
Reverse geocoding takes a location and finds the associated address.
Tip
A token is not required to use this function.
library(arcgisgeocode)
# Find addresses from locations
rev_res <- reverse_geocode(c(-117.172, 34.052))
# preview results
dplyr::glimpse(rev_res)
#> Rows: 1
#> Columns: 23
#> $ match_addr <chr> "600-620 Home Pl, Redlands, California, 92374"
#> $ long_label <chr> "600-620 Home Pl, Redlands, CA, 92374, USA"
#> $ short_label <chr> "600-620 Home Pl"
#> $ addr_type <chr> "StreetAddress"
#> $ type_field <chr> ""
#> $ place_name <chr> ""
#> $ add_num <chr> "604"
#> $ address <chr> "604 Home Pl"
#> $ block <chr> ""
#> $ sector <chr> ""
#> $ neighborhood <chr> "South Redlands"
#> $ district <chr> ""
#> $ city <chr> "Redlands"
#> $ metro_area <chr> ""
#> $ subregion <chr> "San Bernardino County"
#> $ region <chr> "California"
#> $ region_abbr <chr> "CA"
#> $ territory <chr> ""
#> $ postal <chr> "92374"
#> $ postal_ext <chr> ""
#> $ country_name <chr> "United States"
#> $ country_code <chr> "USA"
#> $ geometry <POINT [°]> POINT (-117.172 34.05204)The find_address_candidates() function returns geocoding candidate
results. The function is vectorized over the input and will perform
multiple requests in parallel. Each request geocodes one location at a
time.
One or more candidates are returned from the endpoint. You can limit the
number of candidates using the max_locations argument (with a maximum
of 50).
Tip
A token is not required to use this function.
# Find addresses from address search
candidates <- find_address_candidates(
address = "esri",
address2 = "380 new york street",
city = "redlands",
country_code = "usa",
max_locations = 2
)
dplyr::glimpse(candidates[, 1:10])
#> Rows: 2
#> Columns: 11
#> $ input_id <int> 1, 1
#> $ result_id <int> NA, NA
#> $ loc_name <chr> "World", "World"
#> $ status <chr> "M", "M"
#> $ score <dbl> 100.00, 98.57
#> $ match_addr <chr> "Esri", "380 New York St, Redlands, California, 92373"
#> $ long_label <chr> "Esri, 380 New York St, Redlands, CA, 92373, USA", "380 Ne…
#> $ short_label <chr> "Esri", "380 New York St"
#> $ addr_type <chr> "POI", "PointAddress"
#> $ type_field <chr> "Business Facility", NA
#> $ geometry <POINT [°]> POINT (-117.1957 34.05609), POINT (-117.1954 34.0561)Geocoding services can also provide a location suggestion based on a
search term and, optionally, a location or extent. The
suggest_places() function (/suggest endpoint) is intended to be used
as part of a client-facing application that provides autocomplete
suggestions.
In this example we create a search extent around a single point and find
suggestions based on the search term "bellwood".
Tip
A token is not required to use this function.
# identify a search point as a simple feature column
location <- sf::st_sfc(
sf::st_point(c(-84.34, 33.74)),
crs = 4326
)
# buffer and create a bbox object to search within the extent
search_extent <- sf::st_bbox(
sf::st_buffer(location, 10)
)
# find suggestions within the bounding box
suggestions <- suggest_places(
"bellwood",
location,
search_extent = search_extent
)
suggestions
#> # A data frame: 5 × 3
#> text magic_key is_collection
#> * <chr> <chr> <lgl>
#> 1 Bellwood Coffee, 1366 Glenwood Ave SE, Atlanta, GA, 3… dHA9MCN0… FALSE
#> 2 Bellwood Homes, 736 Jefferson St NW, Atlanta, GA, 303… dHA9MCN0… FALSE
#> 3 Bellwood, Atlanta, GA, USA dHA9MCN0… FALSE
#> 4 Bellwood Coffee, 1776 Peachtree St NW, Atlanta, GA, 3… dHA9MCN0… FALSE
#> 5 Bellwood Church, Atlanta, GA, USA dHA9MCN0… FALSEThe result is intended to be provided to find_address_candidates() to
complete the geocoding process. The column text contains the address
to geocode. The column magic_key is a special identifier that makes it
much faster to fetch results. Pass this into the argument magic_key.
# get address candidate information
# using the text and the magic key
res <- find_address_candidates(
suggestions$text,
magic_key = suggestions$magic_key
)
dplyr::glimpse(res[, 1:10])
#> Rows: 5
#> Columns: 11
#> $ input_id <int> 1, 2, 3, 4, 5
#> $ result_id <int> NA, NA, NA, NA, NA
#> $ loc_name <chr> NA, NA, NA, NA, NA
#> $ status <chr> "M", "M", "M", "M", "M"
#> $ score <dbl> 100, 100, 100, 100, 100
#> $ match_addr <chr> "Bellwood Coffee", "Bellwood Homes", "Bellwood, Atlanta, G…
#> $ long_label <chr> "Bellwood Coffee, 1366 Glenwood Ave SE, Atlanta, GA, 30316…
#> $ short_label <chr> "Bellwood Coffee", "Bellwood Homes", "Bellwood", "Bellwood…
#> $ addr_type <chr> "POI", "POI", "Locality", "POI", "POI"
#> $ type_field <chr> "Snacks", "Other Shops and Service", "City", "Snacks", "Ch…
#> $ geometry <POINT [°]> POINT (-84.34272 33.74034), POINT (-84.41127 33.77591), PO…By default, the argument for_storage = FALSE meaning that the results
of the geocoding operation cannot be persisted. If you intend to persist
the results of the geocoding operation, you must set
for_storage = TRUE.
To learn more about free and paid geocoding operations refer to the storage parameter documentation.
Many addresses can be geocoded very quickly using the
geocode_addresses() function which calls the /geocodeAddresses
endpoint. Note that this function requires an authorization token.
geocode_addresses() sends the input addresses in chunks as parallel
requests.
Batch geocoding requires a signed in user. Load the
{arcgisutils} to authorize
and set your token. This example uses the Geocoding Test Dataset from
the Urban Institute.
Tip
A token is required to use this function with the World Geocoding Service. It may not be necessary if you are using a private ArcGIS Enterprise service.
set_arc_token(auth_user())
# Example dataset from the Urban Institute
fp <- "https://urban-data-catalog.s3.amazonaws.com/drupal-root-live/2020/02/25/geocoding_test_data.csv"
to_geocode <- readr::read_csv(fp, show_col_types = FALSE)
geocoded <- to_geocode |>
dplyr::reframe(
geocode_addresses(
address = address,
city = city,
region = state,
postal = zip
)
)
dplyr::glimpse(res[, 1:10])
#> Rows: 5
#> Columns: 11
#> $ input_id <int> 1, 2, 3, 4, 5
#> $ result_id <int> NA, NA, NA, NA, NA
#> $ loc_name <chr> NA, NA, NA, NA, NA
#> $ status <chr> "M", "M", "M", "M", "M"
#> $ score <dbl> 100, 100, 100, 100, 100
#> $ match_addr <chr> "Bellwood Coffee", "Bellwood Homes", "Bellwood, Atlanta, G…
#> $ long_label <chr> "Bellwood Coffee, 1366 Glenwood Ave SE, Atlanta, GA, 30316…
#> $ short_label <chr> "Bellwood Coffee", "Bellwood Homes", "Bellwood", "Bellwood…
#> $ addr_type <chr> "POI", "POI", "Locality", "POI", "POI"
#> $ type_field <chr> "Snacks", "Other Shops and Service", "City", "Snacks", "Ch…
#> $ geometry <POINT [°]> POINT (-84.34272 33.74034), POINT (-84.41127 33.77591), PO…You can use list_geocoders() to find all of the geocoders available to
you by your organization.
list_geocoders()
#> # A data frame: 1 × 10
#> url northLat southLat eastLon westLon name suggest zoomScale placefinding
#> * <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <int> <lgl>
#> 1 https:… Ymax Ymin Xmax Xmin ArcG… TRUE 10000 TRUE
#> # ℹ 1 more variable: batch <lgl>{arcgisgeocode} can be used with other geocoding services, including
custom locators hosted on ArcGIS Online or Enterprise. You can search
for geocoding services that may be useful for you with
arcgisutils::search_items().
search_items(item_type = "Geocoding Service", max_pages = 1)
#> # A data frame: 50 × 45
#> id owner created modified guid name title type
#> * <chr> <chr> <dttm> <dttm> <lgl> <chr> <chr> <chr>
#> 1 62e6d8… jstr… 2017-09-21 20:46:45 2017-09-21 20:54:15 NA <NA> Brev… Geoc…
#> 2 495c4d… AdmB… 2020-01-13 08:21:34 2020-07-01 07:07:25 NA <NA> Sted… Geoc…
#> 3 b3f732… Clar… 2019-10-24 21:01:47 2019-10-24 21:02:35 NA <NA> Clar… Geoc…
#> 4 11f1b5… Erik… 2015-10-20 17:36:20 2017-11-28 17:24:30 NA <NA> COMP… Geoc…
#> 5 e2e52a… mari… 2017-02-09 12:20:33 2017-02-09 12:20:38 NA <NA> Topo… Geoc…
#> 6 c10754… balt… 2019-12-06 15:47:03 2019-12-06 15:47:06 NA <NA> EGIS… Geoc…
#> 7 2fde30… cbat… 2015-10-29 17:49:15 2015-10-29 17:49:15 NA <NA> Addr… Geoc…
#> 8 0983b4… dili… 2016-05-04 15:59:35 2016-05-04 15:59:35 NA <NA> what… Geoc…
#> 9 893e0b… gis_… 2017-11-15 09:19:05 2017-11-15 11:44:58 NA <NA> PKC Geoc…
#> 10 b8bcbe… 3918 2014-03-21 13:00:08 2014-03-21 13:00:08 NA <NA> Indy… Geoc…
#> # ℹ 40 more rows
#> # ℹ 37 more variables: typeKeywords <list>, description <chr>, tags <list>,
#> # snippet <chr>, thumbnail <chr>, documentation <lgl>, extent <list>,
#> # categories <list>, spatialReference <chr>, accessInformation <chr>,
#> # classification <lgl>, licenseInfo <chr>, culture <chr>, properties <list>,
#> # advancedSettings <lgl>, url <chr>, sourceUrl <chr>, proxyFilter <lgl>,
#> # access <chr>, size <int>, subInfo <int>, appCategories <list>, …To learn more about geocoding with the R-ArcGIS Bridge visit the developers site.