https://github.com/nowosad/raceland
Pattern-Based, Zoneless Method for Analysis and Visualization of Racial Topography
https://github.com/nowosad/raceland
information-theory landscape r racial-diversity raster residential-segregation spatial
Last synced: 7 months ago
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Pattern-Based, Zoneless Method for Analysis and Visualization of Racial Topography
- Host: GitHub
- URL: https://github.com/nowosad/raceland
- Owner: Nowosad
- License: other
- Created: 2019-07-16T14:41:09.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2023-04-14T14:34:00.000Z (over 2 years ago)
- Last Synced: 2025-03-20T22:53:09.009Z (7 months ago)
- Topics: information-theory, landscape, r, racial-diversity, raster, residential-segregation, spatial
- Language: R
- Homepage: https://jakubnowosad.com/raceland/
- Size: 26.3 MB
- Stars: 9
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- 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%"
)
```
# raceland
[](https://github.com/Nowosad/raceland/actions)
[](https://app.codecov.io/gh/Nowosad/raceland?branch=master)
[](https://CRAN.R-project.org/package=raceland)
[](https://cran.r-project.org/package=raceland)
The **raceland** package implements a computational framework for a pattern-based, zoneless analysis, and visualization of (ethno)racial topography (Dmowska et al., 2020).
It is a reimagined approach for analyzing residential segregation and racial diversity based on the concept of ‘landscape’ used in the domain of landscape ecology.
A racial landscape, represented by a high-resolution raster grid with each cell containing only inhabitants of a single race, is quantified by two metrics (entropy and mutual information) derived from Information Theory concept (IT).
Entropy is the measure of racial diversity and mutual information measures racial segregation.
Racial landscape method is based on the raster gridded data, and unlike the previous methods, does not depend on the division of specific zones (census tract, census block, etc.).
Calculation of racial diversity (entropy) and racial segregation (mutual information) can be performed for the whole area of interests (i.e., metropolitan area) without introducing any arbitrary divisions.
Racial landscape method also allows for performing calculations at different spatial scales.
## Installation
You can install the released version of raceland from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("raceland")
```
You can install the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("remotes")
remotes::install_github("Nowosad/raceland")
```
## Example
```{r}
library(raceland)
library(terra)
```
```{r}
# Plot the input data
race_raster = rast(system.file("extdata/race_raster.tif", package = "raceland"))
plot(race_raster)
```
```{r}
# Construct racial landscape
real_raster = create_realizations(x = race_raster, n = 100)
race_colors = c("#F16667", "#6EBE44", "#7E69AF", "#C77213","#F8DF1D")
plot(real_raster, col = race_colors, maxnl = 9)
```
```{r}
# Plot racial ladnscape
plot_realization(x = real_raster[[1]], y = race_raster, hex = race_colors)
```
```{r}
# Calculate local subpopulation densities
dens_raster = create_densities(real_raster, race_raster, window_size = 10)
plot(dens_raster, maxnl = 9)
```
```{r}
# Calculate IT-metrics
metr_df = calculate_metrics(x = real_raster, w = dens_raster,
neighbourhood = 4, fun = "mean",
size = NULL, threshold = 1)
head(metr_df)
```
```{r}
# Summarize IT metrics
summary(metr_df[, c("ent", "mutinf")])
```
## References
- Dmowska, A., Stepinski T., Nowosad J. Racial landscapes – a pattern-based, zoneless method for analysis and visualization of racial topography. Applied Geography. 122:1-9, http://dx.doi.org/10.1016/j.apgeog.2020.102239
## Contribution
Contributions to this package are welcome.
The preferred method of contribution is through a GitHub pull request.
Feel free to contact us by creating [an issue](https://github.com/Nowosad/raceland/issues).