The goal of
osmenrich is to easily enrich geocoded data (
longitude) with geographic features from OpenStreetMap (OSM). The main language of the package is
R and this package is designed to work with the
osmdata packages for collecting and manipulating geodata.
To install the package, you first need to have the
remotes package installed. If you do not have this package yet, please install it first with:
If you do have this package, due to recent changes in GitHub’s naming of branches, please make sure you have the latest version of
remotes or at least version
Once you did this, to continue the installation of the
osmenrich package, run:
or, for the development version, run:
This will use the default public APIs for OSM data and routing (for computing driving/walking distances and durations). Do not use
osmenrich with default APIs for large datasets! If you want to learn how to use
osmenrich for large queries follow the instructions in section Local API Setup below.
Let’s enrich a spatial (
sf) dataset (
sf_example) with the number of waste baskets in a radius of 500 meters from each of the point specified in a dataset:
# Import libraries library(tidyverse) library(sf) library(osmenrich) # Create an example dataset to enrich sf_example <- tribble( ~person, ~lat, ~lon, "Alice", 52.12, 5.09, "Bob", 52.13, 5.08, ) %>% sf::st_as_sf( coords = c("lon", "lat"), crs = 4326 ) # Print it sf_example #> Simple feature collection with 2 features and 1 field #> geometry type: POINT #> dimension: XY #> bbox: xmin: 5.08 ymin: 52.12 xmax: 5.09 ymax: 52.13 #> CRS: EPSG:4326 #> # A tibble: 2 x 2 #> person geometry #> * <chr> <POINT [°]> #> 1 Alice (5.09 52.12) #> 2 Bob (5.08 52.13)
To enrich the
sf_example dataset with “waste baskets” in a 500m radius, you can create a query using the
enrich_osm() function. This function uses the bounding box created by the points present in the example dataset and searches for the specified
key = "amenity" and
value = "waste_basket. You can also add a custom
name for the newly created column and specify the radius (
r) used in the search. See Map Features on the website of OSM for a complete list of
# Simple OSMEnrich query sf_example_enriched <- sf_example %>% enrich_osm( name = "n_waste_baskets", key = "amenity", value = "waste_basket", r = 500 ) #> Downloading data for waste_baskets... Done. #> Downloaded 147 points, 0 lines, 0 polygons, 0 mlines, 0 mpolygons. #> Computing distance matrix for n_waste_baskets...Done.
The resulting enriched dataset
sf_example_enriched is a
sf object and can be printed as usual to inspect the newly added column
sf_example_enriched #> Simple feature collection with 2 features and 2 fields #> geometry type: POINT #> dimension: XY #> bbox: xmin: 5.08 ymin: 52.12 xmax: 5.09 ymax: 52.13 #> geographic CRS: WGS 84 #> # A tibble: 2 x 3 #> person geometry n_waste_baskets #> * <chr> <POINT [°]> <int> #> 1 Alice (5.09 52.12) 75 #> 2 Bob (5.08 52.13) 1
The waste baskets column is now the result of summing all the wastebaskets in a 500 meter radius for Alice and Bob:
OSM enrichment can ask for a lot of data, which can overload public APIs. If you intend to enrich large amounts of data or compute routing distances (e.g., driving duration) between many points, you should set up a local API endpoint.
docker-compose workflows for doing this are avaialble in the separate osmenrich_docker repository. Use the
README in the repository to select the workflow that fits your desired outcome.
Contributions are what make the open source community an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
In this project, the Gitflow workflow is used. Instead of having a single
main branch, the project makes use of two branches to record the history of the project:
main branch is used only for the official releases of the project, while the
develop branch is used to integrate the new features developed. Finally,
feature branches are used to develop new features or additions to the project that will be
rebased and squashed in the
The workflow to contribute with Gitflow becomes:
git checkout -b feature/<AmazingFeature>)
git commit -m 'Add some <AmazingFeature>')
git push origin feature/<AmazingFeature>)
osmenrich package is published under the MIT license. When using
osmenrich for academic work, please cite:
This package is developed and maintained by the ODISSEI Social Data Science (SoDa) team.
Do you have questions, suggestions, or remarks? File an issue in the issue tracker or feel free to contact Erik-Jan van Kesteren (
(https://twitter.com/ejvankesteren)) or Leonardo Vida (