https://github.com/r-spatial/deckglgeoarrow
https://github.com/r-spatial/deckglgeoarrow
Last synced: 15 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/r-spatial/deckglgeoarrow
- Owner: r-spatial
- License: other
- Created: 2025-02-10T15:11:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2026-07-03T09:48:39.000Z (17 days ago)
- Last Synced: 2026-07-03T11:26:08.914Z (17 days ago)
- Language: R
- Homepage: https://r-spatial.github.io/deckglgeoarrow/
- Size: 30.7 MB
- Stars: 19
- Watchers: 2
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# deckglgeoarrow
[](https://github.com/r-spatial/deckglgeoarrow/actions/workflows/R-CMD-check.yaml)
## About
Easy and efficient rendering of very large geospatial data in the browser.
`deckglgeoarrow` provides functionality to efficiently visualise potentially
very large geospatial data as [`Deck.gl`](https://deck.gl/) layers on top of a
[`maplibre`](https://maplibre.org/projects/gl-js/)/[`mapbox`](https://www.mapbox.com/)
map created with package [`mapgl`](https://walker-data.com/mapgl/).
For very quick and efficient data transfer from R memory to the browser,
[`geoarrowWidget`](https://r-spatial.github.io/geoarrowWidget/) is used. Layer
creation is done in 'JavaScript' using [`geoarrow/deck.gl-geoarrow`](https://github.com/geoarrow/deck.gl-geoarrow)
(see [Features](https://github.com/geoarrow/deck.gl-geoarrow#features) section
for details on how and why layer creation is efficient).
## Features
Currently, `(MULTI)POINT`, `(MULTI)LINESTRING` and `(MULTI)POLYGON` features are
supported by the following layer functions:
* [`addGeoarrowScatterplotLayer`](https://r-spatial.github.io/deckglgeoarrow/reference/addGeoArrowScatterplotLayer.html) for point data
* [`addGeoarrowPathLayer`](https://r-spatial.github.io/deckglgeoarrow/reference/addGeoArrowPathLayer.html) for linestring data
* [`addGeoarrowPolygonLayer`](https://r-spatial.github.io/deckglgeoarrow/reference/addGeoArrowPolygonLayer.html) for polygon data
Support for other layers, such as `discrete global grid` layers (`S2`, `A5`, `H3`),
`origin-destination` layers (`Arc`, `trips`) and `point-cloud` layers,
among others, will follow.
## Supported data sources
#### R
Spatial classes from the following R packages are supported (via `data` argument):
* [`wk`](https://paleolimbot.r-universe.dev/wk)
* [`sf`](https://r-spatial.r-universe.dev/sf)
* [`geos`](https://paleolimbot.github.io/geos/)
* [`terra`](https://rspatial.r-universe.dev/terra)
#### Others
The following local or remotely hosted files types are supported (via `file`/`url` argument):
* [`GeoArrow`](https://geoarrow.org/)
* [`GeoParquet`](https://geoparquet.org/)
Note, that due to a [restriction](https://github.com/geoarrow/deck.gl-geoarrow/issues/170) in the upstream JavaScript dependency, only files
with native `GeoArrow` geometry encoding are supported. `WKB` encoded geometries
will not render!
In addition, [`nanoarrow`](https://apache.r-universe.dev/nanoarrow) `array_streams` (as files) are supported.
## Installation
The development version of deckglgeoarrow can be installed from [GitHub](https://github.com/r-spatial/deckglgeoarrow) with:
```r
# install.packages("pak")
pak::pak("r-spatial/deckglgeoarrow")
```
## Example
To showcase what the package can do, consider [this](https://raw.githubusercontent.com/r-spatial/deckglgeoarrow/refs/heads/main/inst/experiments/mapgl.R) example.
Here, we visualise
* 1M random points with random sizes and colors +
* ~11k polygons colored by river basin +
* ~155k lines colored and sized according to their [Strahler number](https://en.wikipedia.org/wiki/Strahler_number)
in one map.
Here's how quickly this renders:
More examples can be found [here](https://github.com/r-spatial/deckglgeoarrow/tree/main/inst/experiments)
### Acknowledgment
This project has been realized with financial [support](https://r-consortium.org/all-projects/2025-group-2.html#modernizing-rs-web-mapping-capabilities) from the
