accessibility

Given a pre-computed travel cost matrix and a land use dataset (containing the location of jobs, healthcare and population, for example), the package allows one to calculate accessibility levels and accessibility poverty and inequality.
https://github.com/ipeagit/accessibility

Category: Consumption
Sub Category: Mobility and Transportation

Keywords

accessibility r transport transport-accessibility

Keywords from Contributors

public-transportation r5 routing transport-networks brazil geopackage geopandas sf spatial-data

Last synced: about 13 hours ago
JSON representation

Repository metadata

Calculate accessibility measures in R

• Host: GitHub
• URL: https://github.com/ipeagit/accessibility
• Owner: ipeaGIT
• License: other
• Created: 2022-05-31T17:54:29.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2025-01-17T18:06:29.000Z (3 months ago)
• Last Synced: 2025-04-10T15:53:42.090Z (17 days ago)
• Topics: accessibility, r, transport, transport-accessibility
• Language: R
• Homepage: https://ipeagit.github.io/accessibility/
• Size: 13 MB
• Stars: 56
• Watchers: 3
• Forks: 9
• Open Issues: 6
• Releases: 7
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md
  • License: LICENSE
  • Codemeta: codemeta.json

README.Rmd

          ---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# accessibility 

[![CRAN
status](https://www.r-pkg.org/badges/version/accessibility)](https://CRAN.R-project.org/package=accessibility)
[![rcmdcheck](https://github.com/ipeaGIT/accessibility/workflows/rcmdcheck/badge.svg)](https://github.com/ipeaGIT/accessibility/actions)
[![CRAN/METACRAN Total
downloads](https://cranlogs.r-pkg.org/badges/grand-total/accessibility?color=yellow)](https://CRAN.R-project.org/package=accessibility)
[![Codecov test
coverage](https://codecov.io/gh/ipeaGIT/accessibility/branch/main/graph/badge.svg)](https://app.codecov.io/gh/ipeaGIT/accessibility?branch=main)
[![Lifecycle:
stable](https://lifecycle.r-lib.org/articles/figures/lifecycle-stable.svg)](https://lifecycle.r-lib.org/articles/stages.html)

**accessibility** offers a set of fast and convenient functions to help
conducting accessibility analyses. Given a pre-computed travel cost matrix and a
land use dataset (containing the location of jobs, healthcare and population,
for example), the package allows one to calculate accessibility levels and
accessibility poverty and inequality. The package covers the majority of the
most commonly used accessibility measures (such as cumulative opportunities,
gravity-based and floating catchment areas methods), as well as the most
frequently used inequality and poverty metrics (such as the Palma ratio, the
concentration and Theil indices and the FGT family of measures).

## Installation

Stable version:

```{r, eval = FALSE}
install.packages("accessibility")
```

Development version:

```{r, eval = FALSE}
# install.packages("remotes")
remotes::install_github("ipeaGIT/accessibility")
```

## Usage

This section aims to present a very brief overview of some of the packages'
features. Fore more details please read the vignettes:

- [Introduction to **accessibility**: calculating accessibility
  measures](https://ipeagit.github.io/accessibility/articles/accessibility.html)
- [Decay
  functions](https://ipeagit.github.io/accessibility/articles/decay_functions.html)
- [Calculating accessibility inequality and
  poverty](https://ipeagit.github.io/accessibility/articles/inequality_and_poverty.html)

To calculate accessibility levels, one simply needs a pre-calculated travel
matrix and some land use data. Below we showcase some of the available
functions:

```{r}
library(accessibility)

data_dir <- system.file("extdata", package = "accessibility")
travel_matrix <- readRDS(file.path(data_dir, "travel_matrix.rds"))
land_use_data <- readRDS(file.path(data_dir, "land_use_data.rds"))

cum_cutoff <- cumulative_cutoff(
  travel_matrix,
  land_use_data,
  opportunity = "jobs",
  travel_cost = "travel_time",
  cutoff = 30
)
head(cum_cutoff)

grav <- gravity(
  travel_matrix,
  land_use_data,
  opportunity = "schools",
  travel_cost = "travel_time",
  decay_function = decay_exponential(decay_value = 0.2)
)
head(grav)

fca <- floating_catchment_area(
  travel_matrix,
  land_use_data,
  opportunity = "jobs",
  travel_cost = "travel_time",
  demand = "population",
  method = "2sfca",
  decay_function = decay_binary(cutoff = 50)
)
head(fca)
```

Calculating inequality and poverty levels is equally easy. Below we use the
previously calculated cumulative accessibility dataset to show some of the
available inequality and poverty functions:

```{r}
palma <- palma_ratio(
  cum_cutoff,
  sociodemographic_data = land_use_data,
  opportunity = "jobs",
  population = "population",
  income = "income_per_capita"
)
palma

poverty <- fgt_poverty(
  cum_cutoff,
  sociodemographic_data = land_use_data,
  opportunity = "jobs",
  population = "population",
  poverty_line = 95368
)
poverty
```

## Related work:

- [r5r](https://github.com/ipeaGIT/r5r): Rapid Realistic Routing with R5 in R
- [tracc](https://github.com/jamaps/tracc): Transport accessibility measures in
  Python
- [access](https://access.readthedocs.io/en/latest/): Spatial Access for PySAL
- [aceso](https://github.com/tetraptych/aceso): a lightweight Python package for
  measuring spatial accessibility

## Acknowledgement 

**accessibility** is developed by a team at the Institute for Applied Economic Research (Ipea), Brazil.

        

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Owner metadata

• Name: IpeaDIRUR
• Login: ipeaGIT
• Email:
• Kind: organization
• Description:
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• Icon url: https://avatars.githubusercontent.com/u/18657547?v=4
• Repositories: 19
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• Profile URL: https://github.com/ipeaGIT

---

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Last Year

• Issues event: 1
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Committers metadata

Last synced: 6 days ago

Name	Email	Commits
Daniel Herszenhut	d****z@g****m	203
rafapereirabr	r****r@g****m	99
rafapereirabr	r****r@g****m	5
Antonio Paez	p****a@g****m	2
olivroy	5****y	1
Joey Reid	b****e	1

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Issue and Pull Request metadata

Last synced: 1 day ago

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Package metadata

• Total packages: 1
• Total downloads:
  • cran: 502 last-month
• Total dependent packages: 1
• Total dependent repositories: 0
• Total versions: 7
• Total maintainers: 1

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Dependencies

Score: 12.141470122344515