| Title: | Download and Import Open Street Map Data Extracts |
|---|---|
| Description: | Match, download, convert and import Open Street Map data extracts obtained from several providers. |
| Authors: | Andrea Gilardi [aut, cre]
 , Robin Lovelace [aut]
, Barry Rowlingson
[ctb] , Salva
Fernández [rev] (Salva reviewed the package (v. 0.1) for
rOpenSci, see
<https://github.com/ropensci/software-review/issues/395>),
Nicholas Potter [rev] (Nicholas reviewed the package (v. 0.1)
for rOpenSci, see
<https://github.com/ropensci/software-review/issues/395>) |
| Maintainer: | Andrea Gilardi <[email protected]> |
| License: | GPL-3 |
| Version: | 0.5.2 |
| Built: | 2024-11-25 16:19:56 UTC |
| Source: | CRAN |
Start bicycle routing for... everywhere!
bbbike_zonesbbbike_zones
An sf object with 237 rows and
6 columns:
The, usually English, long-form name of the city.
Link to the latest .osm.pbf file for this region.
Size of the pbf file in bytes.
A unique identifier. It contains letters, numbers and potentially the characters "-" and "/".
An integer code always equal to 3 (since the bbbike data represent non-hierarchical geographical zones). This is used only for matching operations in case of spatial input. The oe_* functions will select the geographical area closest to the input place with the highest "level". See geofabrik_zones for an example of a (proper) hierarchical structure.
The sfg for that geographical region, rectangular. See
also oe_get_boundary() to extract the proper geographical boundaries.
An sf object containing the URLs, names, and file_size of the OSM extracts
stored at https://download.bbbike.org/osm/bbbike/.
https://download.bbbike.org/osm/
Other provider's-database:
geofabrik_zones,
openstreetmap_fr_zones
An sf object containing the URLs, names and file-sizes of the OSM
extracts stored at https://download.geofabrik.de/. You can read more
details about these data at the following link:
https://download.geofabrik.de/technical.html.
geofabrik_zonesgeofabrik_zones
An sf object with 476 rows and 9 columns:
A unique identifier. It contains letters, numbers and potentially the characters "-" and "/".
The, usually English, long-form name of the area.
The identifier of the next larger excerpts that contains this one, if present.
An integer code between 1 and 4. If level = 1, then the zone corresponds to one of the continents (Africa, Antarctica, Asia, Australia and Oceania, Central America, Europe, North America, and South America) or the Russian Federation. If level = 2, then the zone corresponds to the continent's subregions (i.e. the countries such as Italy, Great Britain, Spain, USA, Mexico, Belize, Morocco, Peru and so on). There are also some exceptions that correspond to the Special Sub Regions (according to the Geofabrik definition), which are: South Africa (includes Lesotho), Alps, Britain and Ireland, Germany + Austria + Switzerland, US Midwest, US Northeast, US Pacific, US South, US West, and all US states. Level = 3L corresponds to the subregions of each state (or each level 2 zone). For example, the West Yorkshire, which is a subregion of England, is a level 3 zone. Finally, level = 4 correspond to the subregions of the third level and it is mainly related to some small areas in Germany. This field is used only for matching operations in case of spatial input.
A character vector of two-letter ISO3166-1 codes. This will be set on the smallest extract that still fully (or mostly) contains the entity with that code; e.g. the code "DE" will be given for the Germany extract and not for Europe even though Europe contains Germany. If an extract covers several countries and no per-country extracts are available (e.g. Israel and Palestine), then several ISO codes will be given (such as "PS IL" for "Palestine and Israel").
A character vector of usually five-character ISO3166-2 codes. The same rules as above apply. Some entities have both an iso3166-1 and iso3166-2 code. For example, the iso3166_2 code of each US State is "US - " plus the code of the state.
Link to the latest .osm.pbf file for this region.
Size of the .pbf file in bytes.
The sfg for that geographical region. These are not the
country boundaries, but a buffer around countries. Check
oe_get_boundary() to extract the geographical boundaries.
https://download.geofabrik.de/
Other provider's-database:
bbbike_zones,
openstreetmap_fr_zones
This functions is a wrapper around unlink() that can be used to delete all
.osm.pbf and .gpkg files in a given directory.
oe_clean(download_directory = oe_download_directory(), force = FALSE)oe_clean(download_directory = oe_download_directory(), force = FALSE)
download_directory |
The directory where the |
force |
Internal option. It can be used to skip the checks run at the
beginning of the function and force the removal of all |
The same as unlink().
# Warning: the following removes all files in oe_download_directory() ## Not run: oe_clean() ## End(Not run)# Warning: the following removes all files in oe_download_directory() ## Not run: oe_clean() ## End(Not run)
This function is used to download a file given a URL. It focuses on OSM
extracts with .osm.pbf format stored by one of the providers implemented in
the package. The URL is specified through the parameter file_url.
oe_download( file_url, provider = NULL, file_basename = basename(file_url), download_directory = oe_download_directory(), file_size = NA, force_download = FALSE, max_file_size = 5e+08, quiet = FALSE )oe_download( file_url, provider = NULL, file_basename = basename(file_url), download_directory = oe_download_directory(), file_size = NA, force_download = FALSE, max_file_size = 5e+08, quiet = FALSE )
file_url |
A URL pointing to a |
provider |
Which provider stores the file? If |
file_basename |
The basename of the file. The default behaviour is to
auto-generate it from the URL using |
download_directory |
Directory to store the file containing OSM data?. |
file_size |
How big is the file? Optional. |
force_download |
Should the |
max_file_size |
The maximum file size to download without asking in
interactive mode. Default: |
quiet |
Boolean. If |
This function runs several checks before actually downloading a new
file to avoid overloading the OSM providers. The first step is the
definition of the file's path associated to the input file_url. The path
is created by pasting together the download_directory, the name of chosen
provider (which may be inferred from the URL) and the basename() of the
URL. For example, if file_url is equal to
"https://download.geofabrik.de/europe/italy-latest.osm.pbf", and
download_directory = "/tmp", then the path is built as
"/tmp/geofabrik_italy-latest.osm.pbf". Thereafter, the function checks
the existence of that file and, if it founds it, then it returns the path.
The parameter force_download is used to modify this behaviour. If there
is no file associated with the new path, then the function downloads a new
file using download.file() with mode = "wb", and, again, it returns the
path.
A character string representing the file's path.
(its_match = oe_match("ITS Leeds", quiet = TRUE)) ## Not run: oe_download( file_url = its_match$url, file_size = its_match$file_size, provider = "test", download_directory = tempdir() ) iow_url = oe_match("Isle of Wight") oe_download( file_url = iow_url$url, file_size = iow_url$file_size, download_directory = tempdir() ) Sucre_url = oe_match("Sucre", provider = "bbbike") oe_download( file_url = Sucre_url$url, file_size = Sucre_url$file_size, download_directory = tempdir() ) ## End(Not run)(its_match = oe_match("ITS Leeds", quiet = TRUE)) ## Not run: oe_download( file_url = its_match$url, file_size = its_match$file_size, provider = "test", download_directory = tempdir() ) iow_url = oe_match("Isle of Wight") oe_download( file_url = iow_url$url, file_size = iow_url$file_size, download_directory = tempdir() ) Sucre_url = oe_match("Sucre", provider = "bbbike") oe_download( file_url = Sucre_url$url, file_size = Sucre_url$file_size, download_directory = tempdir() ) ## End(Not run)
By default, the download directory is equal to tempdir(). You can set a
persistent download directory by adding the following command to your
.Renviron file (e.g. with edit_r_environ function in usethis package):
OSMEXT_DOWNLOAD_DIRECTORY=/path/to/osm/data.
oe_download_directory()oe_download_directory()
A character vector representing the path for the download directory used by the package.
oe_download_directory()oe_download_directory()
This function takes a place name and returns the path of .pbf/.gpkg
files associated with it.
oe_find( place, provider = "geofabrik", download_directory = oe_download_directory(), download_if_missing = FALSE, return_pbf = TRUE, return_gpkg = TRUE, quiet = FALSE, ... )oe_find( place, provider = "geofabrik", download_directory = oe_download_directory(), download_if_missing = FALSE, return_pbf = TRUE, return_gpkg = TRUE, quiet = FALSE, ... )
place |
Description of the geographical area that should be matched with
a |
provider |
Which provider should be used to download the data? Available
providers can be browsed with |
download_directory |
Directory where the files downloaded by osmextract
are stored. By default it is equal to |
download_if_missing |
Attempt to download the file if it cannot be
found? |
return_pbf |
Logical of length 1. If |
return_gpkg |
Logical of length 1. If |
quiet |
Boolean. If |
... |
Extra arguments that are passed to |
The matching between the existing files (saved in the directory
specified by download_directory parameter) and the input place is
performed using list.files(), setting the pattern argument equal to the
basename of the URL associated to the input place. For example, if you
specify place = "Isle of Wight", then the input is matched (via
oe_match()) with the URL of Isle of Wight's .osm.pbf file, and the
files are selected using a pattern equal to the basename of that URL.
If there is no file in the download_directory that can be matched with the
basename of the URL and download_if_missing parameter is equal to TRUE, then the
function tries to download and read a new file from the chosen
provider (geofabrik is the default provider). If download_if_missing
parameter is equal to FALSE (default value), then the function stops with
an error.
By default, this function returns the path of .pbf and .gpkg files
associated with the input place (if any). You can exclude one of the two
formats setting the arguments return_pbf or return_gpkg to FALSE.
A character vector of length one (or two) representing the path(s) of
the .pbf/.gpkg files associated with the input place. The files are
sorted in alphabetical order which implies that if both formats are present
in the download_directory, then the .gpkg file is returned first.
# Copy the ITS file to tempdir() to make sure that the examples do not # require internet connection. You can skip the next 4 lines (and start # directly with oe_get_keys) when running the examples locally. res = file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = file.path(tempdir(), "test_its-example.osm.pbf"), overwrite = TRUE ) res = oe_get("ITS Leeds", quiet = TRUE, download_directory = tempdir()) oe_find("ITS Leeds", provider = "test", download_directory = tempdir()) oe_find( "ITS Leeds", provider = "test", download_directory = tempdir(), return_gpkg = FALSE ) ## Not run: oe_find("Isle of Wight", download_directory = tempdir()) oe_find("Malta", download_if_missing = TRUE, download_directory = tempdir()) oe_find( "Leeds", provider = "bbbike", download_if_missing = TRUE, download_directory = tempdir(), return_pbf = FALSE ) ## End(Not run) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())# Copy the ITS file to tempdir() to make sure that the examples do not # require internet connection. You can skip the next 4 lines (and start # directly with oe_get_keys) when running the examples locally. res = file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = file.path(tempdir(), "test_its-example.osm.pbf"), overwrite = TRUE ) res = oe_get("ITS Leeds", quiet = TRUE, download_directory = tempdir()) oe_find("ITS Leeds", provider = "test", download_directory = tempdir()) oe_find( "ITS Leeds", provider = "test", download_directory = tempdir(), return_gpkg = FALSE ) ## Not run: oe_find("Isle of Wight", download_directory = tempdir()) oe_find("Malta", download_if_missing = TRUE, download_directory = tempdir()) oe_find( "Leeds", provider = "bbbike", download_if_missing = TRUE, download_directory = tempdir(), return_pbf = FALSE ) ## End(Not run) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())
This function is used to find, download, translate, and read OSM extracts
obtained from several providers. It is a wrapper around oe_match() and
oe_read(). Check the introductory vignette, the examples, and the help
pages of the wrapped functions to understand the details behind all
parameters.
oe_get( place, layer = "lines", ..., provider = "geofabrik", match_by = "name", max_string_dist = 1, level = NULL, download_directory = oe_download_directory(), force_download = FALSE, max_file_size = 5e+08, vectortranslate_options = NULL, osmconf_ini = NULL, extra_tags = NULL, force_vectortranslate = FALSE, boundary = NULL, boundary_type = c("spat", "clipsrc"), download_only = FALSE, skip_vectortranslate = FALSE, never_skip_vectortranslate = FALSE, quiet = FALSE )oe_get( place, layer = "lines", ..., provider = "geofabrik", match_by = "name", max_string_dist = 1, level = NULL, download_directory = oe_download_directory(), force_download = FALSE, max_file_size = 5e+08, vectortranslate_options = NULL, osmconf_ini = NULL, extra_tags = NULL, force_vectortranslate = FALSE, boundary = NULL, boundary_type = c("spat", "clipsrc"), download_only = FALSE, skip_vectortranslate = FALSE, never_skip_vectortranslate = FALSE, quiet = FALSE )
place |
Description of the geographical area that should be matched with
a |
layer |
Which |
... |
(Named) arguments that will be passed to |
provider |
Which provider should be used to download the data? Available
providers can be browsed with |
match_by |
Which column of the provider's database should be used for
matching the input |
max_string_dist |
Numerical value greater or equal than 0. What is the
maximum distance in fuzzy matching (i.e. Approximate String Distance, see
|
level |
An integer representing the desired hierarchical level in case
of spatial matching. For the |
download_directory |
Directory to store the file containing OSM data?. |
force_download |
Should the |
max_file_size |
The maximum file size to download without asking in
interactive mode. Default: |
vectortranslate_options |
Options passed to the |
osmconf_ini |
The configuration file. See documentation at
gdal.org. Check details in the
introductory vignette and the help page of |
extra_tags |
Which additional columns, corresponding to OSM tags, should
be in the resulting dataset? |
force_vectortranslate |
Boolean. Force the original |
boundary |
An |
boundary_type |
A character vector of length 1 specifying the type of
spatial filter. The |
download_only |
Boolean. If |
skip_vectortranslate |
Boolean. If |
never_skip_vectortranslate |
Boolean. This is used in case the user
passed its own |
quiet |
Boolean. If |
The algorithm that we use for importing an OSM extract data into R
is divided into 4 steps: 1) match the input place with the url of a
.pbf file; 2) download the .pbf file; 3) convert it into .gpkg format
and 4) read-in the .gpkg file. The function oe_match() is used to
perform the first operation and the function oe_read() (which is a
wrapper around oe_download(), oe_vectortranslate() and sf::st_read())
performs the other three operations.
An sf object.
oe_match(), oe_download(), oe_vectortranslate(), and
oe_read().
# Copy ITS file to tempdir so that the examples do not require internet # connection. You can skip the next 4 lines when running the examples # locally. its_pbf = file.path(tempdir(), "test_its-example.osm.pbf") file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = its_pbf, overwrite = TRUE ) # Match, download (not really) and convert OSM extracts associated to a simple test. its = oe_get("ITS Leeds", download_directory = tempdir()) class(its) unique(sf::st_geometry_type(its)) # Get another layer from ITS Leeds extract its_points = oe_get("ITS Leeds", layer = "points", download_directory = tempdir()) unique(sf::st_geometry_type(its_points)) # Get the .osm.pbf and .gpkg files paths oe_get( "ITS Leeds", download_only = TRUE, quiet = TRUE, download_directory = tempdir() ) oe_get( "ITS Leeds", download_only = TRUE, skip_vectortranslate = TRUE, quiet = TRUE, download_directory = tempdir() ) # See also ?oe_find() # Add additional tags its_with_oneway = oe_get( "ITS Leeds", extra_tags = "oneway", download_directory = tempdir() ) names(its_with_oneway) table(its_with_oneway$oneway, useNA = "ifany") # Use the query argument to get only oneway streets: q = "SELECT * FROM 'lines' WHERE oneway == 'yes'" its_oneway = oe_get("ITS Leeds", query = q, download_directory = tempdir()) its_oneway[, c(1, 3, 9)] # Apply a spatial filter during the vectortranslate operations its_poly = sf::st_sfc( sf::st_polygon( list(rbind( c(-1.55577, 53.80850), c(-1.55787, 53.80926), c(-1.56096, 53.80891), c(-1.56096, 53.80736), c(-1.55675, 53.80658), c(-1.55495, 53.80749), c(-1.55577, 53.80850) )) ), crs = 4326 ) its_spat = oe_get("ITS Leeds", boundary = its_poly, download_directory = tempdir()) its_clipped = oe_get( "ITS Leeds", boundary = its_poly, boundary_type = "clipsrc", quiet = TRUE, download_directory = tempdir() ) plot(sf::st_geometry(its), reset = FALSE, col = "lightgrey") plot(sf::st_boundary(its_poly), col = "black", add = TRUE) plot(sf::st_boundary(sf::st_as_sfc(sf::st_bbox(its_poly))), col = "black", add = TRUE) plot(sf::st_geometry(its_spat), add = TRUE, col = "darkred") plot(sf::st_geometry(its_clipped), add = TRUE, col = "orange") # More complex examples ## Not run: west_yorkshire = oe_get("West Yorkshire") # If you run it again, the function will not download the file # or convert it again west_yorkshire = oe_get("West Yorkshire") # Match with place name oe_get("Milan") # Warning: the .pbf file is 400MB oe_get("Vatican City") # Check all providers oe_get("Zurich") # Use Nominatim API for geolocating places # Match with coordinates (any EPSG) milan_duomo = sf::st_sfc(sf::st_point(c(1514924, 5034552)), crs = 3003) oe_get(milan_duomo, quiet = FALSE) # Warning: the .pbf file is 400MB # Match with numeric coordinates (EPSG = 4326) oe_match(c(9.1916, 45.4650), quiet = FALSE) # Check also alternative providers baku = oe_get(place = "Baku") # Other examples: oe_get("RU", match_by = "iso3166_1_alpha2", quiet = FALSE) # The following example mimics read_sf oe_get("Andora", stringsAsFactors = FALSE, quiet = TRUE, as_tibble = TRUE) ## End(Not run) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())# Copy ITS file to tempdir so that the examples do not require internet # connection. You can skip the next 4 lines when running the examples # locally. its_pbf = file.path(tempdir(), "test_its-example.osm.pbf") file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = its_pbf, overwrite = TRUE ) # Match, download (not really) and convert OSM extracts associated to a simple test. its = oe_get("ITS Leeds", download_directory = tempdir()) class(its) unique(sf::st_geometry_type(its)) # Get another layer from ITS Leeds extract its_points = oe_get("ITS Leeds", layer = "points", download_directory = tempdir()) unique(sf::st_geometry_type(its_points)) # Get the .osm.pbf and .gpkg files paths oe_get( "ITS Leeds", download_only = TRUE, quiet = TRUE, download_directory = tempdir() ) oe_get( "ITS Leeds", download_only = TRUE, skip_vectortranslate = TRUE, quiet = TRUE, download_directory = tempdir() ) # See also ?oe_find() # Add additional tags its_with_oneway = oe_get( "ITS Leeds", extra_tags = "oneway", download_directory = tempdir() ) names(its_with_oneway) table(its_with_oneway$oneway, useNA = "ifany") # Use the query argument to get only oneway streets: q = "SELECT * FROM 'lines' WHERE oneway == 'yes'" its_oneway = oe_get("ITS Leeds", query = q, download_directory = tempdir()) its_oneway[, c(1, 3, 9)] # Apply a spatial filter during the vectortranslate operations its_poly = sf::st_sfc( sf::st_polygon( list(rbind( c(-1.55577, 53.80850), c(-1.55787, 53.80926), c(-1.56096, 53.80891), c(-1.56096, 53.80736), c(-1.55675, 53.80658), c(-1.55495, 53.80749), c(-1.55577, 53.80850) )) ), crs = 4326 ) its_spat = oe_get("ITS Leeds", boundary = its_poly, download_directory = tempdir()) its_clipped = oe_get( "ITS Leeds", boundary = its_poly, boundary_type = "clipsrc", quiet = TRUE, download_directory = tempdir() ) plot(sf::st_geometry(its), reset = FALSE, col = "lightgrey") plot(sf::st_boundary(its_poly), col = "black", add = TRUE) plot(sf::st_boundary(sf::st_as_sfc(sf::st_bbox(its_poly))), col = "black", add = TRUE) plot(sf::st_geometry(its_spat), add = TRUE, col = "darkred") plot(sf::st_geometry(its_clipped), add = TRUE, col = "orange") # More complex examples ## Not run: west_yorkshire = oe_get("West Yorkshire") # If you run it again, the function will not download the file # or convert it again west_yorkshire = oe_get("West Yorkshire") # Match with place name oe_get("Milan") # Warning: the .pbf file is 400MB oe_get("Vatican City") # Check all providers oe_get("Zurich") # Use Nominatim API for geolocating places # Match with coordinates (any EPSG) milan_duomo = sf::st_sfc(sf::st_point(c(1514924, 5034552)), crs = 3003) oe_get(milan_duomo, quiet = FALSE) # Warning: the .pbf file is 400MB # Match with numeric coordinates (EPSG = 4326) oe_match(c(9.1916, 45.4650), quiet = FALSE) # Check also alternative providers baku = oe_get(place = "Baku") # Other examples: oe_get("RU", match_by = "iso3166_1_alpha2", quiet = FALSE) # The following example mimics read_sf oe_get("Andora", stringsAsFactors = FALSE, quiet = TRUE, as_tibble = TRUE) ## End(Not run) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())
This function can be used to obtain polygon/multipolygon objects representing
an administrative boundary. The objects are extracted from the
multipolygons layer of a given OSM extract.
oe_get_boundary(place, name = place, exact = TRUE, ...)oe_get_boundary(place, name = place, exact = TRUE, ...)
place |
Description of the geographical area that should be matched with
a |
name |
A character vector of length 1 that describes the relevant area.
By default, this is equal to |
exact |
Boolean of length 1. If |
... |
Further arguments (e.g. |
The function may return an empty result when the corresponding GPKG file
already exists and contains partial results. In that case, you can try
running the function setting never_skip_vectortranslate = TRUE.
An sf object
## Not run: library(sf) my_cols = sf.colors(5, categorical = TRUE) gabon = oe_get_boundary("Gabon", quiet = TRUE) # country libreville = oe_get_boundary("Gabon", "Libreville", quiet = TRUE) # capital opar = par(mar = rep(0, 4)) plot(st_geometry(st_boundary(gabon)), reset = FALSE, col = "grey") plot(st_geometry(libreville), add = TRUE, col = my_cols[1]) # Exact match komo = oe_get_boundary("Gabon", "Komo", quiet = TRUE) # Pattern matching komo_pt = oe_get_boundary("Gabon", "Komo", exact = FALSE, quiet = TRUE) plot(st_geometry(komo), add = TRUE, col = my_cols[2]) plot(st_geometry(komo_pt), add = TRUE, col = my_cols[3:5]) par(opar) # Get all boundaries (oe_get_boundary("Gabon", name = "%", exact = FALSE, quiet = TRUE)[, 1:2]) # If the basic approach doesn't work, i.e. oe_get_boundary("Leeds") # try to consider larger regions, i.e. oe_get_boundary("West Yorkshire", "Leeds") ## End(Not run)## Not run: library(sf) my_cols = sf.colors(5, categorical = TRUE) gabon = oe_get_boundary("Gabon", quiet = TRUE) # country libreville = oe_get_boundary("Gabon", "Libreville", quiet = TRUE) # capital opar = par(mar = rep(0, 4)) plot(st_geometry(st_boundary(gabon)), reset = FALSE, col = "grey") plot(st_geometry(libreville), add = TRUE, col = my_cols[1]) # Exact match komo = oe_get_boundary("Gabon", "Komo", quiet = TRUE) # Pattern matching komo_pt = oe_get_boundary("Gabon", "Komo", exact = FALSE, quiet = TRUE) plot(st_geometry(komo), add = TRUE, col = my_cols[2]) plot(st_geometry(komo_pt), add = TRUE, col = my_cols[3:5]) par(opar) # Get all boundaries (oe_get_boundary("Gabon", name = "%", exact = FALSE, quiet = TRUE)[, 1:2]) # If the basic approach doesn't work, i.e. oe_get_boundary("Leeds") # try to consider larger regions, i.e. oe_get_boundary("West Yorkshire", "Leeds") ## End(Not run)
This function returns the OSM keys and (optionally) the values stored in the
other_tags field. See Details. In both cases, the keys are sorted according
to the number of occurrences, which means that the most common keys are
stored first.
oe_get_keys( zone, layer = "lines", values = FALSE, which_keys = NULL, download_directory = oe_download_directory() ) ## Default S3 method: oe_get_keys( zone, layer = "lines", values = FALSE, which_keys = NULL, download_directory = oe_download_directory() ) ## S3 method for class 'character' oe_get_keys( zone, layer = "lines", values = FALSE, which_keys = NULL, download_directory = oe_download_directory() ) ## S3 method for class 'sf' oe_get_keys( zone, layer = "lines", values = FALSE, which_keys = NULL, download_directory = oe_download_directory() ) ## S3 method for class 'oe_key_values_list' print(x, n = getOption("oe_max_print_keys", 10L), ...)oe_get_keys( zone, layer = "lines", values = FALSE, which_keys = NULL, download_directory = oe_download_directory() ) ## Default S3 method: oe_get_keys( zone, layer = "lines", values = FALSE, which_keys = NULL, download_directory = oe_download_directory() ) ## S3 method for class 'character' oe_get_keys( zone, layer = "lines", values = FALSE, which_keys = NULL, download_directory = oe_download_directory() ) ## S3 method for class 'sf' oe_get_keys( zone, layer = "lines", values = FALSE, which_keys = NULL, download_directory = oe_download_directory() ) ## S3 method for class 'oe_key_values_list' print(x, n = getOption("oe_max_print_keys", 10L), ...)
zone |
An |
layer |
Which |
values |
Logical. If |
which_keys |
Character vector used to subset only some keys and
corresponding values. Ignored if |
download_directory |
Path of the directory that stores the |
x |
object of class |
n |
Maximum number of keys (and corresponding values) to print; can be
set globally by |
... |
Ignored. |
OSM data are typically documented using several
tags, i.e. pairs of two
items, namely a key and a value. The conversion between .osm.pbf and
.gpkg formats is governed by a CONFIG file that lists which tags must
be explicitly added to the .gpkg file. All the other keys are
automatically stored using an other_tags field with a syntax compatible
with the PostgreSQL HSTORE type. See
here for
more details.
When the argument values is TRUE, then the function returns a named
list of class oe_key_values_list that, for each key, summarises the
corresponding values. The key-value pairs are stored using the following
format: list(key1 = c("value1", "value1", "value2", ...), key2 = c("value1", ...) ...). We decided to implement an ad-hoc method for
printing objects of class oe_key_values_list using the following
structure:
key1 = {#value1 = n1; #value2 = n2; #value3 = n3,
...} key2 = {#value1 = n1; #value2 = n2; ...} key3 = {#value1 = n1} ...
where n1 denotes the number of times that value1 is repeated, n2
denotes the number of times that value2 is repeated and so on. Also the
values are listed according to the number of occurrences in decreasing
order. By default, the function prints only the ten most common keys, but
the number can be adjusted using the option oe_max_print_keys.
Finally, the hstore_get_value() function can be used inside the query
argument in oe_get() to extract one particular tag from an existing file.
Check the introductory vignette and see examples.
If the argument values is FALSE (the default), then the function
returns a character vector with the names of all keys stored in the
other_tags field. If values is TRUE, then the function returns named
list which stores all keys and the corresponding values. In the latter
case, the returned object has class oe_key_values_list and we defined an
ad-hoc printing method. See Details.
oe_vectortranslate()
# Copy the ITS file to tempdir() to make sure that the examples do not # require internet connection. You can skip the next 4 lines (and start # directly with oe_get_keys) when running the examples locally. its_pbf = file.path(tempdir(), "test_its-example.osm.pbf") file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = its_pbf, overwrite = TRUE ) # Get keys oe_get_keys("ITS Leeds", download_directory = tempdir()) # Get keys and values oe_get_keys("ITS Leeds", values = TRUE, download_directory = tempdir()) # Subset some keys oe_get_keys( "ITS Leeds", values = TRUE, which_keys = c("surface", "lanes"), download_directory = tempdir() ) # Print all (non-NA) values for a given set of keys res = oe_get_keys("ITS Leeds", values = TRUE, download_directory = tempdir()) res["surface"] # Get keys from an existing sf object its = oe_get("ITS Leeds", download_directory = tempdir()) oe_get_keys(its, values = TRUE) # Get keys from a character vector pointing to a file (might be faster than # reading the complete file and then filter it) its_path = oe_get( "ITS Leeds", download_only = TRUE, download_directory = tempdir(), quiet = TRUE ) oe_get_keys(its_path, values = TRUE) # Add a key to an existing .gpkg file without repeating the # vectortranslate operations its = oe_get("ITS Leeds", download_directory = tempdir()) colnames(its) its_extra = oe_read( its_path, query = "SELECT *, hstore_get_value(other_tags, 'oneway') AS oneway FROM lines", quiet = TRUE ) colnames(its_extra) # The following fails since there is no points layer in the .gpkg file ## Not run: oe_get_keys(its_path, layer = "points") ## End(Not run) # Add layer and read keys its_path = oe_get( "ITS Leeds", layer = "points", download_only = TRUE, download_directory = tempdir(), quiet = TRUE ) oe_get_keys(its_path, layer = "points") # Remove .pbf and .gpkg files in tempdir rm(its_pbf, res, its_path, its, its_extra) oe_clean(tempdir())# Copy the ITS file to tempdir() to make sure that the examples do not # require internet connection. You can skip the next 4 lines (and start # directly with oe_get_keys) when running the examples locally. its_pbf = file.path(tempdir(), "test_its-example.osm.pbf") file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = its_pbf, overwrite = TRUE ) # Get keys oe_get_keys("ITS Leeds", download_directory = tempdir()) # Get keys and values oe_get_keys("ITS Leeds", values = TRUE, download_directory = tempdir()) # Subset some keys oe_get_keys( "ITS Leeds", values = TRUE, which_keys = c("surface", "lanes"), download_directory = tempdir() ) # Print all (non-NA) values for a given set of keys res = oe_get_keys("ITS Leeds", values = TRUE, download_directory = tempdir()) res["surface"] # Get keys from an existing sf object its = oe_get("ITS Leeds", download_directory = tempdir()) oe_get_keys(its, values = TRUE) # Get keys from a character vector pointing to a file (might be faster than # reading the complete file and then filter it) its_path = oe_get( "ITS Leeds", download_only = TRUE, download_directory = tempdir(), quiet = TRUE ) oe_get_keys(its_path, values = TRUE) # Add a key to an existing .gpkg file without repeating the # vectortranslate operations its = oe_get("ITS Leeds", download_directory = tempdir()) colnames(its) its_extra = oe_read( its_path, query = "SELECT *, hstore_get_value(other_tags, 'oneway') AS oneway FROM lines", quiet = TRUE ) colnames(its_extra) # The following fails since there is no points layer in the .gpkg file ## Not run: oe_get_keys(its_path, layer = "points") ## End(Not run) # Add layer and read keys its_path = oe_get( "ITS Leeds", layer = "points", download_only = TRUE, download_directory = tempdir(), quiet = TRUE ) oe_get_keys(its_path, layer = "points") # Remove .pbf and .gpkg files in tempdir rm(its_pbf, res, its_path, its, its_extra) oe_clean(tempdir())
This function is a wrapper around oe_get() and can be used to import a road
network given a place and a mode of transport. Check the Details for a
precise description of the procedures used to filter the OSM ways according
to each each mode of transport.
oe_get_network(place, mode = c("cycling", "driving", "walking"), ...)oe_get_network(place, mode = c("cycling", "driving", "walking"), ...)
place |
Description of the geographical area that should be matched with
a |
mode |
A character string of length one denoting the desired mode of
transport. Can be abbreviated. Currently |
... |
Additional arguments passed to |
The definition of usable transport network was taken from the Python packages osmnx and pyrosm and several other documents found online, i.e. https://wiki.openstreetmap.org/wiki/OSM_tags_for_routing/Access_restrictions, https://wiki.openstreetmap.org/wiki/Key:access. See also the discussion in https://github.com/ropensci/osmextract/issues/153.
The cycling mode of transport (i.e. the default value for mode
parameter) selects the OSM ways that meet the following conditions:
The highway tag is not missing;
The highway tag is not equal to abandoned, bus_guideway, byway,
construction, corridor, elevator, fixme, escalator, gallop,
historic, no, planned, platform, proposed, raceway or
steps;
The highway tag is not equal to motorway, motorway_link,
footway, bridleway or pedestrian unless the tag bicycle is equal
to yes, designated, permissive or destination (see
here
for more details);
The access tag is not equal to private or no unless bicycle is
equal to yes, permissive or designated (see #289);
The bicycle tag is not equal to no, use_sidepath, private, or
restricted;
The service tag does not contain the string private (i.e.
private, private_access and similar);
The walking mode of transport selects the OSM ways that meet the
following conditions:
The highway tag is not missing;
The highway tag is not equal to abandoned, bus_guideway,
byway, construction, corridor, elevator, fixme,
escalator, gallop, historic, no, planned, platform, proposed,
raceway, motorway or motorway_link;
The highway tag is not equal to cycleway unless the foot tag is
equal to yes;
The access tag is not equal to private or no unless foot is
equal to yes, permissive, or designated (see #289);
The foot tag is not equal to no, use_sidepath, private, or
restricted;
The service tag does not contain the string private
(i.e. private, private_access and similar).
The driving mode of transport selects the OSM ways that meet the
following conditions:
The highway tag is not missing;
The highway tag is not equal to abandoned,
bus_guideway, byway, construction, corridor, elevator, fixme,
escalator, gallop, historic, no, planned, platform, proposed,
cycleway, pedestrian, bridleway, path, or footway;
The access tag is not equal to private or no unless motor_vehicle is
equal to yes, permissive, or designated (see #289);
The service tag does not contain the string private (i.e. private,
private_access and similar).
Feel free to create a new issue in the github repo if you want to suggest modifications to the current filters or propose new values for alternative modes of transport.
An sf object.
# Copy the ITS file to tempdir() to make sure that the examples do not # require internet connection. You can skip the next 4 lines (and start # directly with oe_get_keys) when running the examples locally. its_pbf = file.path(tempdir(), "test_its-example.osm.pbf") file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = its_pbf, overwrite = TRUE ) # default value returned by OSM its = oe_get( "ITS Leeds", quiet = TRUE, download_directory = tempdir() ) plot(its["highway"], lwd = 2, key.pos = 4, key.width = lcm(2.75)) # walking mode of transport its_walking = oe_get_network( "ITS Leeds", mode = "walking", download_directory = tempdir(), quiet = TRUE ) plot(its_walking["highway"], lwd = 2, key.pos = 4, key.width = lcm(2.75)) # driving mode of transport its_driving = oe_get_network( "ITS Leeds", mode = "driving", download_directory = tempdir(), quiet = TRUE ) plot(its_driving["highway"], lwd = 2, key.pos = 4, key.width = lcm(2.75)) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())# Copy the ITS file to tempdir() to make sure that the examples do not # require internet connection. You can skip the next 4 lines (and start # directly with oe_get_keys) when running the examples locally. its_pbf = file.path(tempdir(), "test_its-example.osm.pbf") file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = its_pbf, overwrite = TRUE ) # default value returned by OSM its = oe_get( "ITS Leeds", quiet = TRUE, download_directory = tempdir() ) plot(its["highway"], lwd = 2, key.pos = 4, key.width = lcm(2.75)) # walking mode of transport its_walking = oe_get_network( "ITS Leeds", mode = "walking", download_directory = tempdir(), quiet = TRUE ) plot(its_walking["highway"], lwd = 2, key.pos = 4, key.width = lcm(2.75)) # driving mode of transport its_driving = oe_get_network( "ITS Leeds", mode = "driving", download_directory = tempdir(), quiet = TRUE ) plot(its_driving["highway"], lwd = 2, key.pos = 4, key.width = lcm(2.75)) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())
This function is used to match an input place with the URL of a .osm.pbf
file (and its file-size, if present). The URLs are stored in several
provider's databases. See oe_providers() and examples.
oe_match(place, ...) ## Default S3 method: oe_match(place, ...) ## S3 method for class 'bbox' oe_match(place, ...) ## S3 method for class 'sf' oe_match(place, ...) ## S3 method for class 'sfc' oe_match(place, provider = "geofabrik", level = NULL, quiet = FALSE, ...) ## S3 method for class 'numeric' oe_match(place, provider = "geofabrik", quiet = FALSE, ...) ## S3 method for class 'character' oe_match( place, provider = "geofabrik", quiet = FALSE, match_by = "name", max_string_dist = 1, ... )oe_match(place, ...) ## Default S3 method: oe_match(place, ...) ## S3 method for class 'bbox' oe_match(place, ...) ## S3 method for class 'sf' oe_match(place, ...) ## S3 method for class 'sfc' oe_match(place, provider = "geofabrik", level = NULL, quiet = FALSE, ...) ## S3 method for class 'numeric' oe_match(place, provider = "geofabrik", quiet = FALSE, ...) ## S3 method for class 'character' oe_match( place, provider = "geofabrik", quiet = FALSE, match_by = "name", max_string_dist = 1, ... )
place |
Description of the geographical area that should be matched with
a |
... |
arguments passed to other methods |
provider |
Which provider should be used to download the data? Available
providers can be browsed with |
level |
An integer representing the desired hierarchical level in case
of spatial matching. For the |
quiet |
Boolean. If |
match_by |
Which column of the provider's database should be used for
matching the input |
max_string_dist |
Numerical value greater or equal than 0. What is the
maximum distance in fuzzy matching (i.e. Approximate String Distance, see
|
If the input place is specified as a spatial object (either sf or sfc),
then the function will return a geographical area that completely contains
the object (or an error). The argument level (which must be specified as an
integer between 1 and 4, extreme values included) is used to select between
multiple geographically nested areas. We could roughly say that smaller
administrative units correspond to higher levels. Check the help page of the
chosen provider for more details on level field. By default, level = NULL, which means that oe_match() will return the area corresponding to
the highest available level. If there is no geographical area at the desired
level, then the function will return an error. If there are multiple areas at
the same level intersecting the input place, then the function will return
the area whose centroid is closest to the input place.
If the input place is specified as a character vector and there are multiple
plausible matches between the input place and the match_by column, then the
function will return a warning and it will select the first match. See
Examples. On the other hand, if the approximate string distance between the
input place and the best match in match_by column is greater than
max_string_dist, then the function will look for exact matches (i.e.
max_string_dist = 0) in the other supported providers. If it finds an exact
match, then it will return the corresponding URL. Otherwise, if match_by is
equal to "name", then it will try to geolocate the input place using the
Nominatim API,
and then it will perform a spatial matching operation (see Examples and
introductory vignette), while, if match_by != "name", then it will return
an error.
The fields iso3166_1_alpha2 and iso3166_2 are used by Geofabrik provider
to perform matching operations using ISO 3166-1 alpha-2 and ISO 3166-2 codes. See
geofabrik_zones for more details.
A list with two elements, named url and file_size. The first
element is the URL of the .osm.pbf file associated with the input
place, while the second element is the size of the file in bytes (which
may be NULL or NA)
oe_providers() and oe_match_pattern().
# The simplest example: oe_match("Italy") # The default provider is "geofabrik", but we can change that: oe_match("Leeds", provider = "bbbike") # By default, the matching operations are performed through the column # "name" in the provider's database but this can be a problem. Hence, # you can perform the matching operations using other columns: oe_match("RU", match_by = "iso3166_1_alpha2") # Run oe_providers() for reading a short description of all providers and # check the help pages of the corresponding databases to learn which fields # are present. # You can always increase the max_string_dist argument, but it can be # dangerous: oe_match("London", max_string_dist = 3, quiet = FALSE) # Match the input zone using an sfc object: milan_duomo = sf::st_sfc(sf::st_point(c(1514924, 5034552)), crs = 3003) oe_match(milan_duomo, quiet = FALSE) leeds = sf::st_sfc(sf::st_point(c(430147.8, 433551.5)), crs = 27700) oe_match(leeds, provider = "bbbike") # If you specify more than one sfg object, then oe_match will select the OSM # extract that covers all areas milan_leeds = sf::st_sfc( sf::st_point(c(9.190544, 45.46416)), # Milan sf::st_point(c(-1.543789, 53.7974)), # Leeds crs = 4326 ) oe_match(milan_leeds) # Match the input zone using a numeric vector of coordinates # (in which case crs = 4326 is assumed) oe_match(c(9.1916, 45.4650)) # Milan, Duomo using CRS = 4326 # The following returns a warning since Berin is matched both # with Benin and Berlin oe_match("Berin", quiet = FALSE) # If the input place does not match any zone in the chosen provider, then the # function will test the other providers: oe_match("Leeds") # If the input place cannot be exactly matched with any zone in any provider, # then the function will try to geolocate the input and then it will perform a # spatial match: ## Not run: oe_match("Milan") ## End(Not run) # The level parameter can be used to select smaller or bigger geographical # areas during spatial matching yak = c(-120.51084, 46.60156) ## Not run: oe_match(yak, level = 3) # error oe_match(yak, level = 2) # by default, level is equal to the maximum value oe_match(yak, level = 1) ## End(Not run)# The simplest example: oe_match("Italy") # The default provider is "geofabrik", but we can change that: oe_match("Leeds", provider = "bbbike") # By default, the matching operations are performed through the column # "name" in the provider's database but this can be a problem. Hence, # you can perform the matching operations using other columns: oe_match("RU", match_by = "iso3166_1_alpha2") # Run oe_providers() for reading a short description of all providers and # check the help pages of the corresponding databases to learn which fields # are present. # You can always increase the max_string_dist argument, but it can be # dangerous: oe_match("London", max_string_dist = 3, quiet = FALSE) # Match the input zone using an sfc object: milan_duomo = sf::st_sfc(sf::st_point(c(1514924, 5034552)), crs = 3003) oe_match(milan_duomo, quiet = FALSE) leeds = sf::st_sfc(sf::st_point(c(430147.8, 433551.5)), crs = 27700) oe_match(leeds, provider = "bbbike") # If you specify more than one sfg object, then oe_match will select the OSM # extract that covers all areas milan_leeds = sf::st_sfc( sf::st_point(c(9.190544, 45.46416)), # Milan sf::st_point(c(-1.543789, 53.7974)), # Leeds crs = 4326 ) oe_match(milan_leeds) # Match the input zone using a numeric vector of coordinates # (in which case crs = 4326 is assumed) oe_match(c(9.1916, 45.4650)) # Milan, Duomo using CRS = 4326 # The following returns a warning since Berin is matched both # with Benin and Berlin oe_match("Berin", quiet = FALSE) # If the input place does not match any zone in the chosen provider, then the # function will test the other providers: oe_match("Leeds") # If the input place cannot be exactly matched with any zone in any provider, # then the function will try to geolocate the input and then it will perform a # spatial match: ## Not run: oe_match("Milan") ## End(Not run) # The level parameter can be used to select smaller or bigger geographical # areas during spatial matching yak = c(-120.51084, 46.60156) ## Not run: oe_match(yak, level = 3) # error oe_match(yak, level = 2) # by default, level is equal to the maximum value oe_match(yak, level = 1) ## End(Not run)
This function is used to explore all provider's databases and look for
matches. This function can be useful in combination with oe_match() and
oe_get() for an exploratory analysis and an easy match. See Examples.
oe_match_pattern(pattern, ...) ## S3 method for class 'numeric' oe_match_pattern(pattern, full_row = FALSE, ...) ## S3 method for class 'sf' oe_match_pattern(pattern, full_row = FALSE, ...) ## S3 method for class 'bbox' oe_match_pattern(pattern, full_row = FALSE, ...) ## S3 method for class 'sfc' oe_match_pattern(pattern, full_row = FALSE, ...) ## S3 method for class 'character' oe_match_pattern(pattern, match_by = "name", full_row = FALSE, ...)oe_match_pattern(pattern, ...) ## S3 method for class 'numeric' oe_match_pattern(pattern, full_row = FALSE, ...) ## S3 method for class 'sf' oe_match_pattern(pattern, full_row = FALSE, ...) ## S3 method for class 'bbox' oe_match_pattern(pattern, full_row = FALSE, ...) ## S3 method for class 'sfc' oe_match_pattern(pattern, full_row = FALSE, ...) ## S3 method for class 'character' oe_match_pattern(pattern, match_by = "name", full_row = FALSE, ...)
pattern |
Description of the pattern. Can be either a length-1 character
vector, an |
... |
arguments passed to other methods |
full_row |
Boolean. Return all columns for the matching rows? |
match_by |
Name of the column in the provider's database that will be
used to find the match in case of character input. In all the other cases,
the match is performed using a spatial overlay operation and the output
returns the values stored in the |
A list of character vectors or sf objects (according to the value
of the parameter full_row). If no OSM zone can be matched with the input
string, then the function returns an empty list.
oe_match_pattern("Yorkshire") res = oe_match_pattern("Yorkshire", full_row = TRUE) lapply(res, function(x) sf::st_drop_geometry(x)[, 1:3]) oe_match_pattern(c(9, 45)) # long/lat for Milan, Italyoe_match_pattern("Yorkshire") res = oe_match_pattern("Yorkshire", full_row = TRUE) lapply(res, function(x) sf::st_drop_geometry(x)[, 1:3]) oe_match_pattern(c(9, 45)) # long/lat for Milan, Italy
This function is used to display a short summary of the major characteristics of the databases associated to all available providers.
oe_providers(quiet = FALSE)oe_providers(quiet = FALSE)
quiet |
Boolean. If |
A data.frame with 4 columns representing the name of each available
provider, the name of the corresponding database and the number of features
and fields.
oe_providers()oe_providers()
This function is used to read a .pbf or .gpkg object from file or URL. It
is a wrapper around oe_download(), oe_vectortranslate(), and
sf::st_read(), creating an easy way to download, convert, and read a .pbf
or .gpkg file. Check the introductory vignette and the help pages of the
wrapped function for more details.
oe_read( file_path, layer = "lines", ..., provider = NULL, download_directory = oe_download_directory(), file_size = NULL, force_download = FALSE, max_file_size = 5e+08, download_only = FALSE, skip_vectortranslate = FALSE, vectortranslate_options = NULL, osmconf_ini = NULL, extra_tags = NULL, force_vectortranslate = FALSE, never_skip_vectortranslate = FALSE, boundary = NULL, boundary_type = c("spat", "clipsrc"), quiet = FALSE )oe_read( file_path, layer = "lines", ..., provider = NULL, download_directory = oe_download_directory(), file_size = NULL, force_download = FALSE, max_file_size = 5e+08, download_only = FALSE, skip_vectortranslate = FALSE, vectortranslate_options = NULL, osmconf_ini = NULL, extra_tags = NULL, force_vectortranslate = FALSE, never_skip_vectortranslate = FALSE, boundary = NULL, boundary_type = c("spat", "clipsrc"), quiet = FALSE )
file_path |
A URL or the path to a |
layer |
Which |
... |
(Named) arguments that will be passed to |
provider |
Which provider should be used to download the data? Available
providers can be browsed with |
download_directory |
Directory to store the file containing OSM data?. |
file_size |
How big is the file? Optional. |
force_download |
Should the |
max_file_size |
The maximum file size to download without asking in
interactive mode. Default: |
download_only |
Boolean. If |
skip_vectortranslate |
Boolean. If |
vectortranslate_options |
Options passed to the |
osmconf_ini |
The configuration file. See documentation at
gdal.org. Check details in the
introductory vignette and the help page of |
extra_tags |
Which additional columns, corresponding to OSM tags, should
be in the resulting dataset? |
force_vectortranslate |
Boolean. Force the original |
never_skip_vectortranslate |
Boolean. This is used in case the user
passed its own |
boundary |
An |
boundary_type |
A character vector of length 1 specifying the type of
spatial filter. The |
quiet |
Boolean. If |
The arguments provider, download_directory, file_size,
force_download, and max_file_size are ignored if file_path points to
an existing .pbf or .gpkg file.
Please note that you cannot add any field to an existing .gpkg file using
the argument extra_tags without rerunning the vectortranslate process on
the corresponding .pbf file. On the other hand, you can extract some of
the tags in other_tags field as new columns. See examples and
oe_get_keys() for more details.
An sf object or, when download_only argument equals TRUE, a
character vector.
# Read an existing .pbf file. First we need to copy a .pbf file into a # temporary directory its_pbf = file.path(tempdir(), "test_its-example.osm.pbf") file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = its_pbf ) oe_read(its_pbf) # Read a new layer oe_read(its_pbf, layer = "points") # The following example shows how to add new tags names(oe_read(its_pbf, extra_tags = c("oneway", "ref"), quiet = TRUE)) # Read an existing .gpkg file. This file was created internally by oe_read(). its_gpkg = file.path(tempdir(), "test_its-example.gpkg") oe_read(its_gpkg) # You cannot add any new layer to an existing .gpkg file but you can extract # some of the tags in other_tags. Check oe_get_keys() for more details. names(oe_read(its_gpkg, extra_tags = c("maxspeed"))) # doesn't work # Instead, use the query argument names(oe_read( its_gpkg, quiet = TRUE, query = "SELECT *, hstore_get_value(other_tags, 'maxspeed') AS maxspeed FROM lines " )) # Read from a URL my_url = "https://github.com/ropensci/osmextract/raw/master/inst/its-example.osm.pbf" # Please note that if you read from a URL which is not linked to one of the # supported providers, you need to specify the provider parameter: ## Not run: oe_read(my_url, provider = "test", quiet = FALSE) ## End(Not run) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())# Read an existing .pbf file. First we need to copy a .pbf file into a # temporary directory its_pbf = file.path(tempdir(), "test_its-example.osm.pbf") file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = its_pbf ) oe_read(its_pbf) # Read a new layer oe_read(its_pbf, layer = "points") # The following example shows how to add new tags names(oe_read(its_pbf, extra_tags = c("oneway", "ref"), quiet = TRUE)) # Read an existing .gpkg file. This file was created internally by oe_read(). its_gpkg = file.path(tempdir(), "test_its-example.gpkg") oe_read(its_gpkg) # You cannot add any new layer to an existing .gpkg file but you can extract # some of the tags in other_tags. Check oe_get_keys() for more details. names(oe_read(its_gpkg, extra_tags = c("maxspeed"))) # doesn't work # Instead, use the query argument names(oe_read( its_gpkg, quiet = TRUE, query = "SELECT *, hstore_get_value(other_tags, 'maxspeed') AS maxspeed FROM lines " )) # Read from a URL my_url = "https://github.com/ropensci/osmextract/raw/master/inst/its-example.osm.pbf" # Please note that if you read from a URL which is not linked to one of the # supported providers, you need to specify the provider parameter: ## Not run: oe_read(my_url, provider = "test", quiet = FALSE) ## End(Not run) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())
This (only internal and experimental) function provides a simple interface to the nominatim service for finding the geographical location of place names.
oe_search( place, base_url = "https://nominatim.openstreetmap.org", destfile = tempfile(fileext = ".geojson"), ... )oe_search( place, base_url = "https://nominatim.openstreetmap.org", destfile = tempfile(fileext = ".geojson"), ... )
place |
Text string containing the name of a place the location of
which is to be found, such as |
base_url |
The URL of the nominatim server to use. The main open server hosted by OpenStreetMap is the default. |
destfile |
The name of the destination file where the output
of the search query, a |
... |
Extra arguments that are passed to |
An sf object corresponding to the input place. The sf object is
read by sf::st_read() and it is based on a geojson file returned by
Nominatim API.
This function is used to re-download all .osm.pbf files stored in
download_directory that were firstly downloaded through oe_get(). See
Details.
oe_update( download_directory = oe_download_directory(), quiet = FALSE, delete_gpkg = TRUE, max_file_size = 5e+08, ... )oe_update( download_directory = oe_download_directory(), quiet = FALSE, delete_gpkg = TRUE, max_file_size = 5e+08, ... )
download_directory |
Character string of the path of the directory
where the |
quiet |
Boolean. If |
delete_gpkg |
Boolean. if |
max_file_size |
The maximum file size to download without asking in
interactive mode. Default: |
... |
Additional parameter that will be passed to |
This function is used to re-download .osm.pbf files that are
stored in a directory (specified by download_directory param) and that
were firstly downloaded through oe_get() . The name of the files must
begin with the name of one of the supported providers (see
oe_providers()) and it must end with .osm.pbf. All other
files in the directory that do not match this format are ignored.
The process for re-downloading the .osm.pbf files is performed using the
function oe_get() . The appropriate provider is determined by looking at
the first word in the path of the .osm.pbf file. The place is determined
by looking at the second word in the file path and the matching is
performed through the id column in the provider's database. So, for
example, the path geofabrik_italy-latest-update.osm.pbf will be matched
with the provider "geofabrik" and the geographical zone italy through
the column id in geofabrik_zones.
The parameter delete_gpkg is used to delete all .gpkg files in
download_directory. We decided to set its default value to TRUE to
minimize the possibility of reading-in old and non-synchronized .gpkg
files. If you set delete_gpkg = FALSE, then you need to manually
reconvert all files using oe_get() or oe_vectortranslate() .
If you set the parameter quiet to FALSE, then the function will print
some useful messages regarding the characteristics of the files before and
after updating them. More precisely, it will print the output of the
columns size, mtime and ctime from file.info(). Please note that
the meaning of mtime and ctime depends on the OS and the file system.
Check file.info().
The path(s) of the .osm.pbf file(s) that were updated.
## Not run: # Set up a fake directory with .pbf and .gpkg files fake_dir = tempdir() # Fill the directory oe_get("Andorra", download_directory = fake_dir, download_only = TRUE) # Check the directory list.files(fake_dir, pattern = "gpkg|pbf") # Update all .pbf files and delete all .gpkg files oe_update(fake_dir, quiet = TRUE) list.files(fake_dir, pattern = "gpkg|pbf") ## End(Not run)## Not run: # Set up a fake directory with .pbf and .gpkg files fake_dir = tempdir() # Fill the directory oe_get("Andorra", download_directory = fake_dir, download_only = TRUE) # Check the directory list.files(fake_dir, pattern = "gpkg|pbf") # Update all .pbf files and delete all .gpkg files oe_update(fake_dir, quiet = TRUE) list.files(fake_dir, pattern = "gpkg|pbf") ## End(Not run)
This function is used to translate a .osm.pbf file into .gpkg format.
The conversion is performed using
ogr2ogr via the
vectortranslate utility in sf::gdal_utils() . It was created following
the suggestions
of the maintainers of GDAL. See Details and Examples to understand the basic
usage, and check the introductory vignette for more complex use-cases.
oe_vectortranslate( file_path, layer = "lines", vectortranslate_options = NULL, osmconf_ini = NULL, extra_tags = NULL, force_vectortranslate = FALSE, never_skip_vectortranslate = FALSE, boundary = NULL, boundary_type = c("spat", "clipsrc"), quiet = FALSE )oe_vectortranslate( file_path, layer = "lines", vectortranslate_options = NULL, osmconf_ini = NULL, extra_tags = NULL, force_vectortranslate = FALSE, never_skip_vectortranslate = FALSE, boundary = NULL, boundary_type = c("spat", "clipsrc"), quiet = FALSE )
file_path |
Character string representing the path of the input
|
layer |
Which |
vectortranslate_options |
Options passed to the |
osmconf_ini |
The configuration file. See documentation at
gdal.org. Check details in the
introductory vignette and the help page of |
extra_tags |
Which additional columns, corresponding to OSM tags, should
be in the resulting dataset? |
force_vectortranslate |
Boolean. Force the original |
never_skip_vectortranslate |
Boolean. This is used in case the user
passed its own |
boundary |
An |
boundary_type |
A character vector of length 1 specifying the type of
spatial filter. The |
quiet |
Boolean. If |
The new .gpkg file is created in the same directory as the input
.osm.pbf file. The translation process is performed using the
vectortranslate utility in sf::gdal_utils(). This operation can be
customized in several ways modifying the parameters layer, extra_tags,
osmconf_ini, vectortranslate_options, boundary and boundary_type.
The .osm.pbf files processed by GDAL are usually categorized into 5
layers, named points, lines, multilinestrings, multipolygons and
other_relations. Check the first paragraphs
here for more details. This
function can covert only one layer at a time, and the parameter layer is
used to specify which layer of the .osm.pbf file should be converted.
Several layers with different names can be stored in the same .gpkg file.
By default, the function will convert the lines layer (which is the most
common one according to our experience).
The arguments osmconf_ini and extra_tags are used to modify how GDAL
reads and processes a .osm.pbf file. More precisely, several operations
that GDAL performs on the input .osm.pbf file are governed by a CONFIG
file, that can be checked at the following
link.
The basic components of OSM data are called
elements and they are
divided into nodes, ways or relations, so, for example, the code at
line 7 of that file is used to determine which ways are assumed to be
polygons (according to the simple-feature definition of polygon) if they
are closed. Moreover, OSM data is usually described using several
tags, i.e pairs of two items:
a key and a value. The code at lines 33, 53, 85, 103, and 121 is used to
determine, for each layer, which tags should be explicitly reported as
fields (while all the other tags are stored in the other_tags column).
The parameter extra_tags is used to determine which extra tags (i.e.
key/value pairs) should be added to the .gpkg file (other than the
default ones).
By default, the vectortranslate operations are skipped if the function
detects a file having the same path as the input file, .gpkg extension, a
layer with the same name as the parameter layer and all extra_tags. In
that case the function will simply return the path of the .gpkg file.
This behaviour can be overwritten setting force_vectortranslate = TRUE.
The vectortranslate operations are never skipped if osmconf_ini,
vectortranslate_options, boundary or boundary_type arguments are not
NULL.
The parameter osmconf_ini is used to pass your own CONFIG file in case
you need more control over the GDAL operations. Check the package
introductory vignette for an example. If osmconf_ini is equal to NULL
(the default value), then the function uses the standard osmconf.ini file
defined by GDAL (but for the extra tags).
The parameter vectortranslate_options is used to control the options that
are passed to ogr2ogr via sf::gdal_utils() when converting between
.osm.pbf and .gpkg formats. ogr2ogr can perform various operations
during the conversion process, such as spatial filters or SQL queries.
These operations can be tuned using the vectortranslate_options argument.
If NULL (the default value), then vectortranslate_options is set equal
to
c("-f", "GPKG", "-overwrite", "-oo", paste0("CONFIG_FILE=", osmconf_ini), "-lco", "GEOMETRY_NAME=geometry", layer).
Explanation:
"-f", "GPKG" says that the output format is GPKG;
"-overwrite is used to delete an existing layer and recreate
it empty;
"-oo", paste0("CONFIG_FILE=", osmconf_ini) is used to set the
Open Options
for the .osm.pbf file and change the CONFIG file (in case the user
asks for any extra tag or a totally different CONFIG file);
"-lco", "GEOMETRY_NAME=geometry" is used to change the
layer creation options
for the .gpkg file and modify the name of the geometry column;
layer indicates which layer should be converted.
If vectortranslate_options is not NULL, then the options c("-f", "GPKG", "-overwrite", "-oo", "CONFIG_FILE=", path-to-config-file, "-lco", "GEOMETRY_NAME=geometry", layer) are always appended unless the user
explicitly sets different default parameters for the arguments -f, -oo,
-lco, and layer.
The arguments boundary and boundary_type can be used to set up a
spatial filter during the vectortranslate operations (and speed up the
process) using an sf or sfc object (POLYGON or MULTIPOLYGON). The
default arguments create a rectangular spatial filter which selects all
features that intersect the area. Setting boundary_type = "clipsrc" clips
the geometries. In both cases, the appropriate options are automatically
added to the vectortranslate_options (unless a user explicitly sets
different default options). Check Examples in oe_get() and the
introductory vignette.
See also the help page of sf::gdal_utils() and
ogr2ogr for more examples and
extensive documentation on all available options that can be tuned during
the vectortranslate process.
Character string representing the path of the .gpkg file.
# First we need to match an input zone with a .osm.pbf file (its_match = oe_match("ITS Leeds")) # Copy ITS file to tempdir so that the examples do not require internet # connection. You can skip the next 3 lines (and start directly with # oe_download()) when running the examples locally. file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = file.path(tempdir(), "test_its-example.osm.pbf"), overwrite = TRUE ) # The we can download the .osm.pbf file (if it was not already downloaded) its_pbf = oe_download( file_url = its_match$url, file_size = its_match$file_size, download_directory = tempdir(), provider = "test" ) # Check that the file was downloaded list.files(tempdir(), pattern = "pbf|gpkg") # Convert to gpkg format its_gpkg = oe_vectortranslate(its_pbf) # Now there is an extra .gpkg file list.files(tempdir(), pattern = "pbf|gpkg") # Check the layers of the .gpkg file sf::st_layers(its_gpkg, do_count = TRUE) # Add points layer its_gpkg = oe_vectortranslate(its_pbf, layer = "points") sf::st_layers(its_gpkg, do_count = TRUE) # Add extra tags to the lines layer names(sf::st_read(its_gpkg, layer = "lines", quiet = TRUE)) its_gpkg = oe_vectortranslate( its_pbf, extra_tags = c("oneway", "maxspeed") ) names(sf::st_read(its_gpkg, layer = "lines", quiet = TRUE)) # Adjust vectortranslate options and convert only 10 features # for the lines layer oe_vectortranslate( its_pbf, vectortranslate_options = c("-limit", 10) ) sf::st_layers(its_gpkg, do_count = TRUE) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())# First we need to match an input zone with a .osm.pbf file (its_match = oe_match("ITS Leeds")) # Copy ITS file to tempdir so that the examples do not require internet # connection. You can skip the next 3 lines (and start directly with # oe_download()) when running the examples locally. file.copy( from = system.file("its-example.osm.pbf", package = "osmextract"), to = file.path(tempdir(), "test_its-example.osm.pbf"), overwrite = TRUE ) # The we can download the .osm.pbf file (if it was not already downloaded) its_pbf = oe_download( file_url = its_match$url, file_size = its_match$file_size, download_directory = tempdir(), provider = "test" ) # Check that the file was downloaded list.files(tempdir(), pattern = "pbf|gpkg") # Convert to gpkg format its_gpkg = oe_vectortranslate(its_pbf) # Now there is an extra .gpkg file list.files(tempdir(), pattern = "pbf|gpkg") # Check the layers of the .gpkg file sf::st_layers(its_gpkg, do_count = TRUE) # Add points layer its_gpkg = oe_vectortranslate(its_pbf, layer = "points") sf::st_layers(its_gpkg, do_count = TRUE) # Add extra tags to the lines layer names(sf::st_read(its_gpkg, layer = "lines", quiet = TRUE)) its_gpkg = oe_vectortranslate( its_pbf, extra_tags = c("oneway", "maxspeed") ) names(sf::st_read(its_gpkg, layer = "lines", quiet = TRUE)) # Adjust vectortranslate options and convert only 10 features # for the lines layer oe_vectortranslate( its_pbf, vectortranslate_options = c("-limit", 10) ) sf::st_layers(its_gpkg, do_count = TRUE) # Remove .pbf and .gpkg files in tempdir oe_clean(tempdir())
An sf object containing the URLs, names, and file-sizes of the OSM
extracts stored at http://download.openstreetmap.fr/.
openstreetmap_fr_zonesopenstreetmap_fr_zones
An sf object with 1187 rows and
7 columns:
A unique ID for each area. It is used by oe_update().
The, usually English, long-form name of the city.
The identifier of the next larger excerpts that contains this one, if present.
An integer code between 1 and 4. Check http://download.openstreetmap.fr/polygons/ to understand the hierarchical structure of the zones. 1L correspond to the biggest areas. This is used only for matching operations in case of spatial input.
Link to the latest .osm.pbf file for this region.
Size of the pbf file in bytes.
The sfg for that geographical region, rectangular. See
also oe_get_boundary() to extract the proper geographical boundaries.
http://download.openstreetmap.fr/
Other provider's-database:
bbbike_zones,
geofabrik_zones
.poly file.Read a .poly file.
read_poly(input, crs = "OGC:CRS84", ...)read_poly(input, crs = "OGC:CRS84", ...)
input |
Character vector representing a polygon object saved using the
|
crs |
The Coordinate Reference System (CRS) of the input polygon. |
... |
Further arguments passed to |
The Polygon Filter File Format (.poly) is defined
here.
The code behind the function was inspired by the parse_poly function
defined
here.
Geofabrik stores the .poly files used
to generate their extracts. Furthermore, a nice collection of exact-border
poly files created from cities with an OSM Relation ID is available in this
git repository on github: https://github.com/jameschevalier/cities.
The default value for the crs argument is "OGC:CRS84" instead of "4326"
or "EPSG:4326" since, by definition, the coordinates are provided as
"longitude, latitude" (but these differences should be relevant only when
sf::st_axis_order() is TRUE).
A sfc_MULTIPOLYGON/sfc object.
toy_poly <- c( "test_poly", "first_area", "0 0", "0 1", "1 1", "1 0", "0 0", "END", "END" ) (out <- read_poly(toy_poly)) plot(out) ## Not run: italy_poly <- "https://download.geofabrik.de/europe/italy.poly" plot(read_poly(italy_poly)) ## End(Not run)toy_poly <- c( "test_poly", "first_area", "0 0", "0 1", "1 1", "1 0", "0 0", "END", "END" ) (out <- read_poly(toy_poly)) plot(out) ## Not run: italy_poly <- "https://download.geofabrik.de/europe/italy.poly" plot(read_poly(italy_poly)) ## End(Not run)
This object represent a minimal provider's database and it should be used only for examples and tests.
test_zonestest_zones
An object of class sf (inherits from data.frame) with 2 rows and 7 columns.