https://github.com/danielvartan/orbis
🌎 Spatial Data Analysis Tools
https://github.com/danielvartan/orbis
api-clients brazil r-packages rstats sidra spatial-analysis spatial-data terra worldclim
Last synced: 6 months ago
JSON representation
🌎 Spatial Data Analysis Tools
- Host: GitHub
- URL: https://github.com/danielvartan/orbis
- Owner: danielvartan
- License: gpl-3.0
- Created: 2025-03-18T04:25:09.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2026-01-12T02:30:00.000Z (6 months ago)
- Last Synced: 2026-01-12T05:57:54.199Z (6 months ago)
- Topics: api-clients, brazil, r-packages, rstats, sidra, spatial-analysis, spatial-data, terra, worldclim
- Language: R
- Homepage: https://danielvartan.github.io/orbis/
- Size: 26.9 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
- Funding: .github/FUNDING.yml
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Codemeta: codemeta.json
Awesome Lists containing this project
README
# orbis 
[](https://www.repostatus.org/#active)
[](https://doi.org/10.5281/zenodo.18240800)
[](https://github.com/danielvartan/orbis/actions)
[](https://app.codecov.io/gh/danielvartan/orbis)
[](https://fairsoftwarechecklist.net/v0.2/?f=21&a=30112&i=32322&r=123)
[](https://fair-software.eu)
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://www.contributor-covenant.org/version/3/0/code_of_conduct/)
## Overview
`orbis` is an [R](https://www.r-project.org/) package with tools to
simplify spatial data analysis. It provides an intuitive interface that
follows [tidyverse
principles](https://tidyverse.tidyverse.org/articles/manifesto.html) and
integrates seamlessly with the [tidyverse
ecosystem](https://tidyverse.org/).
> If you find this project useful, please consider giving it a star!
> [](https://github.com/danielvartan/orbis/)
> The continuous development of `orbis` depends on community support. If
> you find this project useful, and can afford to do so, please consider
> becoming a sponsor.
> [](https://github.com/sponsors/danielvartan)
## Installation
You can install `orbis` using the
[`remotes`](https://github.com/r-lib/remotes) package:
``` r
# install.packages("remotes")
remotes::install_github("danielvartan/orbis")
```
## Usage
`orbis` is equipped with several functions to help with your analysis,
such as:
- [`shift_and_rotate()`](https://danielvartan.github.io/orbis/reference/shift_and_rotate.html):
Shift and rotate a `SpatVector` or a `SpatRaster`
- [`remove_unique_outliers()`](https://danielvartan.github.io/orbis/reference/remove_unique_outliers.html):
Remove unique outliers from raster files
- [`sidra_download_by_year()`](https://danielvartan.github.io/orbis/reference/sidra_download_by_year.html):
Download and aggregate data by year from
[SIDRA](https://sidra.ibge.gov.br/) API (to avoid overloading)
- [`worldclim_download()`](https://danielvartan.github.io/orbis/reference/worldclim_download.html):
Download [WorldClim](https://worldclim.org/) data
- [`worldclim_to_ascii()`](https://danielvartan.github.io/orbis/reference/worldclim_to_ascii.html):
Convert [WorldClim](https://worldclim.org/)
[GeoTIFF](https://www.ogc.org/standards/geotiff/) files to [Esri
ASCII](https://desktop.arcgis.com/en/arcmap/latest/manage-data/raster-and-images/esri-ascii-raster-format.htm)
raster format
Here are some examples of usage.
### `shift_and_rotate()`
[`shift_and_rotate()`](https://danielvartan.github.io/orbis/reference/shift_and_rotate.html)
was developed to simplify shifting and rotating spatial data, especially
for rasters and vectors that cross the [International Date
Line](https://en.wikipedia.org/wiki/International_Date_Line) (e.g. the
Russian territory).
#### Set the Environment
``` r
library(orbis)
library(dplyr)
library(geodata)
library(ggplot2)
library(terra)
library(tidyterra)
```
#### Define a World Vector
``` r
world_vector <- world(path = tempdir())
```
#### Visualize the World Vector
``` r
world_vector |>
ggplot() +
geom_spatvector(fill = "#3243A6", color = "white")
```
#### Define a Country Vector
``` r
russia_vector <- gadm(country = "rus", level = 0, path = tempdir())
```
#### Visualize the Country Vector
``` r
russia_vector |>
ggplot() +
geom_spatvector(fill = "#3243A6", color = "white")
```
#### Shift and Rotate the Country Vector 45 Degrees to the Left
``` r
russia_vector |>
shift_and_rotate(-45) |>
ggplot() +
geom_spatvector(fill = "#3243A6", color = "white")
```
### `remove_unique_outliers()`
[`remove_unique_outliers()`](https://danielvartan.github.io/orbis/reference/remove_unique_outliers.html)
was developed to simplify the removal of abnormal values in raster
files. It can be used with
[GeoTIFF](https://www.ogc.org/standards/geotiff/) and [Esri
ASCII](https://desktop.arcgis.com/en/arcmap/latest/manage-data/raster-and-images/esri-ascii-raster-format.htm)
raster formats.
#### Set the Environment
``` r
library(orbis)
library(dplyr)
library(readr)
library(stars)
```
#### Create a Fictional Esri ASCII File
``` r
asc_content <- c(
"ncols 5",
"nrows 5",
"xllcorner 0.0",
"yllcorner 0.0",
"cellsize 1.0",
"NODATA_value -9999",
"1 2 3 4 5 ",
"6 7 8 9 10 ",
"11 12 1000 14 15 ", # Extreme outlier (1000)
"16 1 18 19 20 ",
"21 22 23 24 25 "
)
```
``` r
file <- tempfile(fileext = ".asc")
asc_content |> write_lines(file)
```
#### Visualize Values Before `remove_unique_outliers()`
``` r
file |> read_stars() |> pull(1) |> as.vector()
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 1000 14
#> [15] 15 16 1 18 19 20 21 22 23 24 25
```
#### Visualize Values After `remove_unique_outliers()`
``` r
file |> remove_unique_outliers()
```
``` r
file |> read_stars() |> pull(1) |> as.vector()
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 NA 14 15 16 1 18 19 20 21 22 23 24
#> [25] 25
```
Click [here](https://danielvartan.github.io/orbis/reference/) to see the
full list of `orbis` functions.
## Citation
If you use this package in your research, please cite it to acknowledge
the effort put into its development and maintenance. Your citation helps
support its continued improvement.
``` r
citation("orbis")
#> To cite orbis in publications use:
#>
#> Vartanian, D. (2026). orbis: Spatial data analysis tools [Computer
#> software]. https://doi.org/10.5281/zenodo.18240800
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Misc{,
#> title = {orbis: Spatial data analysis tools},
#> author = {Daniel Vartanian},
#> year = {2026},
#> doi = {10.5281/zenodo.18240800},
#> }
```
## License
[](https://www.gnu.org/licenses/gpl-3.0)
``` text
Copyright (C) 2025 Daniel Vartanian
orbis is free software: you can redistribute it and/or modify it under the
terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later
version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with
this program. If not, see .
```
## Contributing
[](https://www.contributor-covenant.org/version/3/0/code_of_conduct/)
Contributions are always welcome! Whether you want to report bugs,
suggest new features, or help improve the code or documentation, your
input makes a difference.
Before opening a new issue, please check the [issues
tab](https://github.com/danielvartan/orbis/issues) to see if your topic
has already been reported.
[](https://github.com/sponsors/danielvartan)
You can also support the development of `orbis` by becoming a sponsor.
Click [here](https://github.com/sponsors/danielvartan) to make a
donation. Please mention `orbis` in your donation message.