Geocoding is the process of retrieving geographic coordinates based on text, such as an address or the name of a place (Wikipedia page). On the other hand, reverse geocoding is the process of retrieving the name and address from geographic coordinates (Wikipedia page).
geocode(
place,
as_coordinates = FALSE,
only_netherlands = TRUE,
api_key = read_secret("gis.api_key"),
api_requests_per_second = 1
)
reverse_geocode(
sf_data,
api_key = read_secret("gis.api_key"),
api_requests_per_second = 1
)
Data © OpenStreetMap contributors, ODbL 1.0. https://osm.org/copyright
a (vector of) names or addresses of places
a logical to indicate whether the result should be returned as coordinates (i.e., class sfc_POINT
)
a logical to indicate whether only Dutch places should be searched
free API key created at https://geocode.maps.co
number of requests per second
an 'sf' object or an 'sfc' object (i.e., a vector with geometric sfc_POINT
s). Can also be a character vector, in which case geocode()
will be called first.
These functions use OpenStreetMap (OSM), by using the API of https://geocode.maps.co.
geocode()
provides geocoding and returns an 'sf' data.frame at default. In case of multiple results, the distance from the main Certe building in Groningen is leading.
reverse_geocode()
provides reversed geocoding and returns a data.frame with the columns "name", "address", "zipcode" and "city".
For both functions, the https://geocode.maps.co API will only be called on unique input values, to increase speed.
if (FALSE) { # \dontrun{
# geocoding: retrieve 'sf' data.frame based on place names
coord <- geocode("Van Swietenlaan 2, Groningen")
coord
# reverse geocoding: get the name and address
reverse_geocode(coord)
# places can be any text, and the results are prioritised based on
# the distance from the main Certe building, so:
reverse_geocode(c("Certe", "IKEA"))
hospitals <- geocode(c("Martini ziekenhuis",
"Medisch Centrum Leeuwarden",
"Tjongerschans Heerenveen",
"Scheper Emmen"))
hospitals
if (require("certeplot2")) {
geo_gemeenten |>
crop_certe() |>
plot2(datalabels = FALSE) |>
add_sf(hospitals, colour = "certeroze", datalabels = place)
}
} # }