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https://github.com/edwindj/sdcSpatial
Create privacy protected maps with R
https://github.com/edwindj/sdcSpatial
Last synced: 3 months ago
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Create privacy protected maps with R
- Host: GitHub
- URL: https://github.com/edwindj/sdcSpatial
- Owner: edwindj
- Created: 2018-05-29T14:19:59.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-07-09T08:09:42.000Z (4 months ago)
- Last Synced: 2024-07-09T10:37:49.432Z (4 months ago)
- Language: R
- Homepage: https://edwindj.github.io/sdcSpatial/
- Size: 35 MB
- Stars: 6
- Watchers: 3
- Forks: 1
- Open Issues: 11
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
Awesome Lists containing this project
README
---
output: github_document
---```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
[![CRAN status](https://www.r-pkg.org/badges/version/sdcSpatial)](https://cran.r-project.org/package=sdcSpatial)
[![R build status](https://github.com/edwindj/sdcSpatial/workflows/R-CMD-check/badge.svg)](https://github.com/edwindj/sdcSpatial/actions)
[![](https://cranlogs.r-pkg.org/badges/sdcSpatial)](https://cran.r-project.org/package=sdcSpatial)
[![status](https://tinyverse.netlify.com/badge/sdcSpatial)](https://CRAN.R-project.org/package=sdcSpatial)
[![Mentioned in Awesome Official Statistics](https://awesome.re/mentioned-badge.svg)](http://www.awesomeofficialstatistics.org)# sdcSpatial
_Publishing a raster density map can reveal sensitive values_.
`sdcSpatial` is an opensource R package for creating spatial density (raster)
maps from point data while protecting the privacy of individual observations.`sdcSpatial` offers a `sdc_raster` class that allows to:
- find out which locations are considered sensitive / unsafe for publishing: `plot_sensitive`, `is_sensitive`, `sensitivity_score`.
- apply protection methods that reduce sensitiviy and enhance spatial patterns: `protect_smooth`, `protect_quadtree`.
- remove sensitive locations: `remove_sensitive`.
- extract relative as well as absolute density `raster`s that can be used with visualisation packages, such as `tmap` and `leaflet`: `x$value$mean`, `x$value$sum`, `mean`, `sum`.## Installation
```r
install.packages("sdcSpatial")
```To install the current development version of `sdcSpatial` with `devtools`
```r
remotes::install_github("edwindj/sdcSpatial")
```## Example
```{r example, code=head(readLines("./example/protect_smooth.R")[-1],-1)}
```