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https://github.com/ipeagit/rosmium

R Bindings for Osmium Tool
https://github.com/ipeagit/rosmium

openstreetmap osm osmium r

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R Bindings for Osmium Tool

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README 

        
---

output: github_document

---



```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-"

)

```



# rosmium



[![CRAN

status](https://www.r-pkg.org/badges/version/rosmium)](https://CRAN.R-project.org/package=rosmium)

[![B

status](https://github.com/ipeaGIT/rosmium/workflows/check/badge.svg)](https://github.com/ipeaGIT/rosmium/actions?query=workflow%3Acheck)

[![Codecov test

coverage](https://codecov.io/gh/ipeaGIT/rosmium/branch/main/graph/badge.svg)](https://app.codecov.io/gh/ipeaGIT/rosmium?branch=main)

[![Lifecycle:

experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html)



**rosmium** allows one to use [Osmium Tool](https://osmcode.org/osmium-tool/)

from R. Osmium is a multipurpose command line tool that enables one to

manipulate and analyze OpenStreetMap (OSM) files through several different

commands. Currently, this package does not aim to offer functions that cover the

entirety of Osmium's API, instead making available functions that wrap only a

very limited set of Osmium's features. 



## Installation



Development version:



```r

# install.packages("remotes")

remotes::install_github("ipeaGIT/rosmium")

```



Please note that **rosmium** requires Osmium to be installed and added to the

PATH environment variable of your local system. For instructions on how to

install Osmium, please check [its official

website](https://osmcode.org/osmium-tool/#download).



## Usage



The package currently includes only three entrypoints to Osmium's API. To

demonstrate them, we will use some sample data bundled with the package.



```{r, eval = requireNamespace("ggplot2", quietly = TRUE), fig.width = 6, fig.height = 5.5}

library(rosmium)

library(ggplot2)



cur_pbf <- system.file("extdata/cur.osm.pbf", package = "rosmium")



cur_pbf_lines <- sf::st_read(cur_pbf, layer = "lines", quiet = TRUE)



ggplot(cur_pbf_lines) + geom_sf()

```



### `extract()`



`extract()` creates geographical extracts from OSM files. In its most basic

form, the function takes the path to the OSM file whose geographical extent

should be extracted from, the extent, either as a bounding box or as a

(multi)polygon, and the path to the file where the output should be written to.

Additionally, the function can also take the strategy to be used when creating

the extract, which defaults to `"complete_ways"`. Please check the function

documentation for details on the available strategies and their behavior.



```{r, eval = requireNamespace("ggplot2", quietly = TRUE), fig.width = 6, fig.height = 4.5}

# buffering the pbf bounding box 4000 meters inward and using the result

# extent to extract the osm data inside it. transforming the crs because

# inward buffers only work with projected crs



bbox <- sf::st_bbox(cur_pbf_lines)

bbox_polygon <- sf::st_as_sf(sf::st_as_sfc(bbox))

smaller_bbox_poly <- sf::st_buffer(sf::st_transform(bbox_polygon, 5880), -4000)

smaller_bbox_poly <- sf::st_transform(smaller_bbox_poly, 4326)



output_path <- extract(

  cur_pbf,

  smaller_bbox_poly,

  tempfile(fileext = ".osm.pbf"),

  spinner = FALSE

)



extracted_pbf_lines <- sf::st_read(output_path, layer = "lines", quiet = TRUE)



ggplot() +

  geom_sf(data = extracted_pbf_lines) +

  geom_sf(data = smaller_bbox_poly, color = "red", fill = NA)

```



### `tags_filter()`



`tags_filter()` filters OSM files, keeping objects matching at least one of the

specified expressions from the input. In its most basic form, the function takes

the path to the OSM file to which the filters should be applied, the filter

expressions that should be applied and the path to the file where the output

should be written to. Please check the function documentation for a description

of the filter expression format.



By default, not only the objects matching the expressions will be kept in the

output, but also the objects referenced by them. This behavior can be changed

with the `omit_referenced` parameter. The function also includes the

`invert_match` parameter, that inverts the sense of matching (excluding objects

that match the filters), and the `remove_tags` parameter, used to remove tags

from objects that are referenced by objects matching the filters, but which do

not match the filter themselves. Both arguments default to `FALSE`.



```{r}

# get all amenity nodes

output <- tags_filter(cur_pbf, "n/amenity", tempfile(fileext = ".osm.pbf"))

nodes <- sf::st_read(output, layer = "points", quiet = TRUE)

head(nodes$other_tags)



# get all objects (nodes, ways or relations) with an addr:* tag

output <- tags_filter(

  cur_pbf,

  "addr:*",

  tempfile(fileext = ".osm.pbf"),

  omit_referenced = TRUE,

  spinner = FALSE

)

nodes <- sf::st_read(output, layer = "points", quiet = TRUE)

head(nodes$other_tags)

```



### `show_content()`



Finally, `show_content()` displays the content of an OSM file either in `.html`,

`.xml` or `.opl` format. The function takes as input the path to the OSM file

whose content should be shown, the output format in which the content should be

displayed (defaulting to `.html`, the most human readable format, although also

the slowest to open and inspect, depending on the size of the input file) and

the type of objects that should be included in the output (defaulting to all

existing objects in the input). The function returns the path to the temporary

file in which the OSM file content was saved and opens the content in the web

browser or the most appropriate application, depending on the output format.



```{r}

# displays the content of the previous tags_filter() output in html format

show_content(output, spinner = FALSE)

```



```{r, echo = FALSE}

knitr::include_graphics("man/figures/filtered_file_content.png")

```



## Acknowledgement



**rosmium** is developed by a team at the Institute for Applied Economic

Research (Ipea), Brazil. We would like to thank the authors and contributors of

Osmium for the development of [Osmium

Tool](https://github.com/osmcode/osmium-tool).