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The goal of nominatimlite is to provide a lightweight interface for geocoding addresses with the Nominatim API. It also allows you to return results as sf objects using the sf package.

The full site with examples and vignettes is available at https://dieghernan.github.io/nominatimlite/

What is Nominatim?

Nominatim is a tool for searching OpenStreetMap data by name and address (geocoding) and generating synthetic addresses for OSM points (reverse geocoding).

Why nominatimlite?

nominatimlite accesses the Nominatim API without depending on curl. In some situations, curl may not be available or accessible, so nominatimlite uses base R functions instead.

Other packages are more complete and mature than nominatimlite and provide similar features:

Installation

Install nominatimlite from CRAN:

install.packages("nominatimlite")

See the documentation for the development version at https://dieghernan.github.io/nominatimlite/dev/.

You can install the development version of nominatimlite with:

pak::pak("dieghernan/nominatimlite")

Alternatively, you can install nominatimlite using the r-universe:

# Install nominatimlite in R:
install.packages(
  "nominatimlite",
  repos = c(
    "https://dieghernan.r-universe.dev",
    "https://cloud.r-project.org"
  )
)

Usage

sf objects

With nominatimlite you can return sf objects:

library(nominatimlite)

# Search for Pizza Hut locations in California.

CA <- geo_lite_sf("California", points_only = FALSE)

pizzahut <- geo_lite_sf(
  "Pizza Hut, California",
  limit = 50,
  custom_query = list(countrycodes = "us")
)

library(ggplot2)

ggplot(CA) +
  geom_sf() +
  geom_sf(data = pizzahut, col = "red")

Pizza Hut restaurant locations in California extracted with nominatimlite.

You can also return polygon and line objects when the Nominatim API provides them, using the option points_only = FALSE:

# A building, returned as a polygon.
sol_poly <- geo_lite_sf("Statue of Liberty, NY, USA", points_only = FALSE)

ggplot(sol_poly) +
  geom_sf()

Location of the Statue of Liberty extracted with nominatimlite.

# Default, returned as a point.
dayton <- geo_lite_sf("Dayton, OH")
# A US state, returned as a polygon.
ohio_state <- geo_lite_sf("Ohio, USA", points_only = FALSE)
# A river, returned as a line.
ohio_river <- geo_lite_sf("Ohio river", points_only = FALSE)

ggplot() +
  geom_sf(data = ohio_state) +
  geom_sf(data = dayton, color = "red", pch = 4) +
  geom_sf(data = ohio_river, color = "blue")

Different features named Ohio extracted with nominatimlite.

Geocoding and reverse geocoding

Note: examples are adapted from the tidygeocoder package.

In this first example, we geocode a few addresses with geo_lite():

library(tibble)

# 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 <- geo_lite(
  some_addresses$addr,
  lat = "latitude",
  long = "longitude",
  progressbar = FALSE
)

This example returns only latitude, longitude and address columns from the Nominatim API. Use full_results = TRUE to return all available data from the Nominatim API.

query latitude longitude address
1600 Pennsylvania Ave NW, Washington, DC 38.89764 -77.03655 White House, 1600, Pennsylvania Avenue Northwest, Ward 2, Washington, District of Columbia, 20500, United States
600 Montgomery St, San Francisco, CA 94111 37.79519 -122.40279 Transamerica Pyramid, 600, Montgomery Street, Financial District, South of Market, San Francisco, California, 94111, United States
233 S Wacker Dr, Chicago, IL 60606 41.87874 -87.63596 Willis Tower, 233, South Wacker Drive, Financial District, Loop, Chicago, South Chicago Township, Cook County, Illinois, 60606, United States

Table 1: Example: geocoding addresses.

To perform reverse geocoding, use reverse_geo_lite() to obtain addresses from geographic coordinates. The arguments are similar to geo_lite(), but now we provide coordinate values with the lat and long arguments. The dataset used here is from the geocoding query above. The single-line address is returned in a column named with the address argument.

reverse <- reverse_geo_lite(
  lat = lat_longs$latitude,
  long = lat_longs$longitude,
  address = "address_found",
  progressbar = FALSE
)
address_found lat lon
White House, 1600, Pennsylvania Avenue Northwest, Downtown, Ward 2, Washington, District of Columbia, 20500, United States 38.89764 -77.03655
Sky Bar, Mark Twain Place, Financial District, South of Market, San Francisco, California, 94111, United States 37.79519 -122.40254
West Adams Street, Financial District, Loop, Chicago, South Chicago Township, Cook County, Illinois, 60675, United States 41.87874 -87.63589

Table 2: Example: reverse geocoding addresses.

For more advanced users, see the Nominatim documentation for the available parameters.

Citation

Hernangómez D (2026). nominatimlite: Interface to the Nominatim API. doi:10.32614/CRAN.package.nominatimlite. https://dieghernan.github.io/nominatimlite/.

A BibTeX entry for LaTeX users is

@Manual{R-nominatimlite,
  title = {{nominatimlite}: Interface to the {Nominatim} {API}},
  doi = {10.32614/CRAN.package.nominatimlite},
  author = {Diego Hernangómez},
  year = {2026},
  version = {0.6.0},
  url = {https://dieghernan.github.io/nominatimlite/},
  abstract = {Lightweight interface to the OpenStreetMap Nominatim API <https://nominatim.org/release-docs/latest/>. Extract coordinates from addresses, retrieve addresses from coordinates, look up amenities and addresses, and return results as tibble or sf objects.},
}

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. arcgeocoder: Geocoding with the ArcGIS REST API Service. Version 0.1.0. https://doi.org/10.5281/zenodo.10495365.
Padgham, Mark, Robin Lovelace, Maëlle Salmon, and Bob Rudis. 2017. “osmdata.” Journal of Open Source Software 2 (14): 305. https://doi.org/10.21105/joss.00305.