# Get started wit arcgeocoder

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/

## Why 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.

## Recommended packages

There are other packages much more complete and mature than `nominatimlite`, that presents similar features:

- tidygeocoder (Cambon et al. 2021). Allows to interface with ArcGIS, Nominatim (OpenStreetMaps), Google, TomTom, Mapbox, etc. for geocoding and reverse geocoding.
- nominatimlite (Hernangómez 2024). Similar to arcgeocoder but using data from OpenStreetMaps trough the Nominatim API service.

## 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")
    #>
      |
      |                                                  |   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 | 37.79517 | -122.40278 | 600 Montgomery St, San Francisco, California, 94111 | 100 | -122.40278 | 37.79517 | -122.40378 | 37.79417 | -122.40178 | 37.79617 | 4326 | 4326
233 S Wacker Dr, Chicago, IL 60606 | 41.87877 | -87.63580 | 233 S Wacker Dr, Chicago, Illinois, 60606 | 100 | -87.63580 | 41.87877 | -87.63680 | 41.87777 | -87.63480 | 41.87977 | 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
-122.40278 | 37.79517 | Transamerica Pyramid, 600 Montgomery St, San Francisco, CA, 94111, USA
-87.63580 | 41.87877 | Willis Tower, 233 S Wacker Dr, 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, 5 Avenue Anatole France, 75007, 7e Arrondissement, Paris, Île-de-France, …

    # 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"
      )

Example: Food places near the Eiffel Tower

### 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.

## References

Cambon, Jesse, Diego Hernangómez, Christopher Belanger, and Daniel Possenriede. 2021. “tidygeocoder: An R Package for Geocoding.” Journal of Open Source Software 6 (65): 3544. https://doi.org/10.21105/joss.03544.
Hernangómez, Diego. 2024. nominatimlite: Interface with Nominatim API Service (version 0.2.1). https://doi.org/10.5281/zenodo.5113195.