The goal of arcgeocoder is to provide a light interface for geocoding addresses and reverse geocoding location trough the ArcGIS REST API Geocoding Service.
Full site with examples and vignettes on https://dieghernan.github.io/arcgeocoder/
arcgeocoder is a package that provides a lightweight interface for geocoding and reverse geocoding with the ArcGIS REST API service. The goal of arcgeocoder is to access 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 apigeocoder is built with the aim of easing the access to
all the features provided by the API. The API endpoints used by arcgeocoder
are findAddressCandidates
and reverseGeocode
, which can be accessed without
the need for an API key.
There are other packages much more complete and mature than nominatimlite
,
that presents similar features:
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$addr, lat = "latitude", long = "longitude") #> | | | 0% | |================= | 33% | |================================= | 67% | |==================================================| 100%
Only a few fields are returned from the geocoder service in this example, but
full_results = TRUE
can be used to return all of the data from the geocoder
service.
|query | latitude| longitude|address | score| x| y| xmin| ymin| xmax| ymax| wkid| latestWkid| |:------------------------------------------|--------:|----------:|:-----------------------------------------------------------------|-----:|----------:|--------:|----------:|--------:|----------:|--------:|----:|----------:| |1600 Pennsylvania Ave NW, Washington, DC | 38.89768| -77.03655|1600 Pennsylvania Ave NW, Washington, District of Columbia, 20500 | 100| -77.03655| 38.89768| -77.03755| 38.89668| -77.03555| 38.89868| 4326| 4326| |600 Montgomery St, San Francisco, CA 94111 | 37.79519| -122.40279|600 Montgomery St, San Francisco, California, 94111 | 100| -122.40279| 37.79519| -122.40379| 37.79419| -122.40179| 37.79619| 4326| 4326| |233 S Wacker Dr, Chicago, IL 60606 | 41.87889| -87.63602|233 S Wacker Dr, Chicago, Illinois, 60606 | 100| -87.63602| 41.87889| -87.63702| 41.87789| -87.63502| 41.87989| 4326| 4326|
To perform reverse geocoding (obtaining addresses from geographic coordinates),
we can use the arc_reverse_geo()
function. The arguments are similar to the
arc_geo()
function, but now we specify the input data columns with the x
and
y
arguments. The dataset used here is from the geocoder query above. The
single line address is returned in a column named by the address
.
reverse <- arc_reverse_geo( x = lat_longs$longitude, y = lat_longs$latitude, address = "address_found" ) #> | | | 0% | |================= | 33% | |================================= | 67% | |==================================================| 100%
| x| y|address_found | |----------:|--------:|:----------------------------------------------------------------------------| | -77.03655| 38.89768|White House, 1600 Pennsylvania Ave NW, Washington, DC, 20500, USA | | -122.40279| 37.79519|Mbia Insurance Corporation, 600 Montgomery St, San Francisco, CA, 94111, USA | | -87.63602| 41.87889|Liberty Hands Cleaning, 233 S Wacker Dr, Ste 1011, Chicago, IL, 60606, USA |
It is possible also to search for specific locations within or near a reference
are or location using category
filtering.
See more information in the documentation of the data base arc_categories
.
In the following example we would look for POIs related with food (i.e. Restaurants, Coffee Shops, Bakeries) near the Eiffel Tower in France.
library(ggplot2) # For plotting # Step 1: Locate Eiffel Tower, using multifield query eiffel_tower <- arc_geo_multi( address = "Tour Eiffel", city = "Paris", countrycode = "FR", langcode = "FR", custom_query = list(outFields = "LongLabel") ) # Display results eiffel_tower %>% select(lon, lat, LongLabel) #> # A tibble: 1 × 3 #> lon lat LongLabel #> <dbl> <dbl> <chr> #> 1 2.29 48.9 Tour Eiffel, 3 Esplanade des Ouvriers de la Tour Eiffel, 75007, 7e Arrondissement, … # Use lon,lat to boots the search and using category = Food food_eiffel <- arc_geo_categories("Food", x = eiffel_tower$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" )
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.
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