Comparing the supported OSM providers
Source:vignettes/providers_comparisons.Rmd
providers_comparisons.Rmd
This vignette presents a simple comparison between the OSM providers
supported by osmextract
, explaining their pros and cons. We
decided to write this vignette since, as you will see in the following
examples, even if you always start from the same pre-defined
place
, you can get significantly different OSM extracts
according to the chosen provider
. Hence, we want to help
you choose the best suitable provider for a given situation.
We assume that you are already familiar with the basic functions in
osmextract
, otherwise please check the “Get Started”
vignette for a more detailed introduction. Now, let’s start with an
example, but, first of all, we have to load the package:
library(osmextract)
#> Data (c) OpenStreetMap contributors, ODbL 1.0. https://www.openstreetmap.org/copyright.
#> Check the package website, https://docs.ropensci.org/osmextract/, for more details.
library(sf)
#> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.4.0; sf_use_s2() is TRUE
We geocode the coordinates of Lima, the Capital of Peru,
lima = tmaptools::geocode_OSM("Lima, Peru")$coords
and look for a match in the OSM extracts using
oe_match()
:
oe_match(lima, provider = "geofabrik")
#> $url
#> [1] "https://download.geofabrik.de/south-america/peru-latest.osm.pbf"
#>
#> $file_size
#> [1] 2.06e+08
oe_match(lima, provider = "bbbike")
#> $url
#> [1] "https://download.bbbike.org/osm/bbbike/Lima/Lima.osm.pbf"
#>
#> $file_size
#> [1] 17905003
oe_match(lima, provider = "openstreetmap_fr")
#> $url
#> [1] "http://download.openstreetmap.fr/extracts/south-america-latest.osm.pbf"
#>
#> $file_size
#> [1] 3889405217
We can see that:
- when we used
geofabrik
provider (which is also the default provider), then the inputplace
was matched with an OSM extract corresponding to Peru region; - when we used the
bbbike
provider, then the inputplace
was matched with an OSM extract corresponding to the city of Lima; - when we used
openstreetmap_fr
provider, then the input data was matched with an OSM extract covering the whole of South America.
The reason behind these differences is that each OSM provider divides the geographical space into different discrete chunks, and, in the following paragraphs, we will show the tessellation used by each provider.
Geofabrik
geofabrik
is a society that provides map-based services
and free downloads of OSM extracts that are updated daily. These
extracts are based on a division of the world into different regions,
covering a whole continent (plus Russian Federation):
par(mar = rep(0, 4))
plot(geofabrik_zones[geofabrik_zones$level == 1, "name"], key.pos = NULL, main = NULL)
or several countries all around the world:
plot(geofabrik_zones[geofabrik_zones$level == 2, "name"], key.pos = NULL, main = NULL)
Geofabrik also defines several special zones, such as Alps, Britain and Ireland, Germany, Austria and Switzerland, US Midwest, US Northeast, US Pacific, US South and US West. Moreover, it contains extracts relative to some administrative subregions, mainly in Europe, Russia, Canada and South America:
plot(geofabrik_zones[geofabrik_zones$level == 3, "name"], key.pos = NULL, main = NULL)
Check ?geofabrik_zones
and the provider’s webpage for more
details.
Openstreetmap.fr
openstreetmap_fr
extracts are taken from http://download.openstreetmap.fr/, a web-service that
provides OSM data updated every few minutes. The extracts are based on
several regions, such as the continents:
# Russian federation is considered as a level 1 zone
plot(openstreetmap_fr_zones[openstreetmap_fr_zones$level == 1, "name"], key.pos = NULL, main = NULL)
or some countries around the world (less than
geofabrik
):
plot(openstreetmap_fr_zones[openstreetmap_fr_zones$level == 2, "name"], key.pos = NULL, main = NULL)
It can be noticed that there are several holes (such as Peru, which
is the reason why, in the first example, Lima was matched with South
America data), implying that openstreetmap_fr
cannot always
be used for geographical matching of a place
. Nevertheless,
it provides extremely detailed extracts for some regions of the world,
like China,
plot(openstreetmap_fr_zones[openstreetmap_fr_zones$parent == "china", "name"], key.pos = NULL, main = NULL)
India,
plot(openstreetmap_fr_zones[openstreetmap_fr_zones$parent == "india", "name"], key.pos = NULL, main = NULL)
France,
ids_2 = openstreetmap_fr_zones$parent %in% "france"
ids_3 = openstreetmap_fr_zones$parent %in% openstreetmap_fr_zones$id[ids_2]
plot(openstreetmap_fr_zones[ids_2 | ids_3, "name"], key.pos = NULL, main = NULL)
and Brazil
BBBike
bbbike
provider is based on https://download.bbbike.org/osm/bbbike/. It is quite
different from any other provider supported in osmextract
since it contains OSM data for more than 200 cities worldwide.
par(mar = rep(0, 4))
plot(sf::st_geometry(spData::world))
plot(sf::st_geometry(bbbike_zones), border = "darkred", add = TRUE, lwd = 3)
bbbike
provider is the safest choice if you are looking
for OSM data relative to a particular city in the world.