Title:	Data from the 'Access to Opportunities Project (AOP)'
Version:	1.1.1
Description:	Download data from the 'Access to Opportunities Project (AOP)'. The 'aopdata' package brings annual estimates of access to employment, health, education and social assistance services by transport mode, as well as data on the spatial distribution of population, jobs, health care, schools and social assistance facilities at a fine spatial resolution for all cities included in the project. More info on the 'AOP' website https://www.ipea.gov.br/acessooportunidades/en/.
URL:	https://ipeagit.github.io/aopdata/, https://github.com/ipeaGIT/aopdata
BugReports:	https://github.com/ipeaGIT/aopdata/issues
License:	MIT + file LICENSE
Encoding:	UTF-8
Depends:	R (≥ 3.5.0)
Imports:	checkmate, curl (≥ 5.0.0), data.table, methods, sf (≥ 0.9-3), utils
Suggests:	covr, dplyr (≥ 0.8-3), ggplot2 (≥ 3.3.1), knitr, rmarkdown (≥ 2.6), scales, testthat, units
RoxygenNote:	7.3.2
VignetteBuilder:	knitr
NeedsCompilation:	no
Packaged:	2025-01-28 20:16:05 UTC; user
Author:	Rafael H. M. Pereira [aut, cre], Daniel Herszenhut [aut], Marcus Saraiva [aut], Carlos Kaue Vieira Braga [aut], Diego Bogado Tomasiello [ctb], Joao Bazzo [ctb], Ipea - Institute for Applied Economic Research [cph, fnd]
Maintainer:	Rafael H. M. Pereira <rafa.pereira.br@gmail.com>
Repository:	CRAN
Date/Publication:	2025-01-29 00:10:02 UTC

aopdata: Data from the 'Access to Opportunities Project (AOP)'

Description

Download data from the 'Access to Opportunities Project (AOP)'. The aopdata package brings annual estimates of access to employment, health, education and social assistance services by transport mode, as well as data on the spatial distribution of population, jobs, health care, schools and social assistance facilities at a fine spatial resolution for all cities included in the project. More info on the AOP website https://www.ipea.gov.br/acessooportunidades/en/.

Usage

Please check the vignettes on the website.

Author(s)

Maintainer: Rafael H. M. Pereira rafa.pereira.br@gmail.com (ORCID)

Authors:

• Daniel Herszenhut dhersz@gmail.com (ORCID)

• Marcus Saraiva marcus.saraiva@gmail.com (ORCID)

• Carlos Kaue Vieira Braga kaue@kauebraga.dev (ORCID)

Other contributors:

• Diego Bogado Tomasiello diegobt86@gmail.com [contributor]

• Joao Bazzo joao.bazzo@gmail.com [contributor]

• Ipea - Institute for Applied Economic Research [copyright holder, funder]

See Also

Useful links:

• https://ipeagit.github.io/aopdata/

• https://github.com/ipeaGIT/aopdata

• Report bugs at https://github.com/ipeaGIT/aopdata/issues

Merge land use and access data

Description

Merges landuse and access data

Usage

aop_merge(aop_landuse, aop_access)

Arguments

Value

Returns a data.table with landuse and access data

Spatial join of AOP data

Description

Merges land use or access data with H3 grid geometries

Usage

aop_spatial_join(aop_df, aop_sf)

Arguments

Value

Returns a ⁠data.frame sf⁠ with access/land use data and grid geometries

aopdata data dictionary

Description

Opens aopdata data dictionary on a web browser. This function requires internet connection.

Usage

aopdata_dictionary(lang = "en")

Arguments

Value

Opens aopdata data dictionary on a web browser

Examples

# Data dictionary in English
aopdata_dictionary(lang='en')

# Data dictionary in Portuguese
aopdata_dictionary(lang='pt')

Check internet connection with Ipea server

Description

Checks if there is an internet connection with Ipea server.

Usage

check_connection(
  url = "https://www.ipea.gov.br/geobr/aopdata/metadata/metadata.csv",
  silent = FALSE
)

Arguments

Value

Logical. TRUE if url is working, FALSE if not.

Check if object has been downloaded/created in global environment

Description

Check if object has been downloaded/created in global environment

Usage

check_downloaded_obj(obj)

Arguments

Value

Returns NULL with an informative message

Download data to a temporary directory.

Description

Save requested data (either an sf or a data.frame) to a temporary directory.

Usage

download_data(url, progress_bar = showProgress)

Arguments

Value

No visible output. The downloaded file (either an sf or a data.frame) is saved to a temporary directory.

Support function to download metadata internally used in aopdata

Description

Support function to download metadata internally used in aopdata

Usage

download_metadata()

Examples

## Not run:  if (interactive()) {
df <- download_metadata()
}
## End(Not run)

Load data from tempdir to global environment

Description

Reads data from tempdir to global environment.

Usage

load_data(temps = NULL)

Arguments

Value

Returns either an sf or a data.frame, depending of the data set that was downloaded

Download accessibility estimates with population and land use data

Description

Download estimates of access to employment, health, education and social assistance services by transport mode and time of the day for the cities included in the AOP project. See the documentation 'Details' for the data dictionary. The data set reports information for each heaxgon in a H3 spatial grid at resolution 9, with a side of 174 meters and an area of 0.10 km2. More information about H3 at https://h3geo.org/docs/core-library/restable/.

Usage

read_access(
  city = NULL,
  mode = "walk",
  peak = TRUE,
  year = 2019,
  geometry = FALSE,
  showProgress = TRUE
)

Arguments

Value

A data.frame object

Data dictionary:

The name of the columns with accessibility estimates are the junction of three components: 1) Type of accessibility indicator 2) Type of opportunity / population 3) Time threshold

1) Type of accessibility indicator

2) Type of opportunity / population

3) Time threshold (only applicable to CMA and CMP estimates)

4) Cities available

Examples

# Read accessibility estimates of a single city
df <- read_access(city = 'Fortaleza', mode = 'public_transport', year = 2019, showProgress = FALSE)
df <- read_access(city = 'Goiania', mode = 'public_transport', year = 2019, showProgress = FALSE)

# Read accessibility estimates for all cities
all <- read_access(city = 'all', mode = 'walk', year = 2019, showProgress = FALSE)

Download spatial hexagonal grid H3

Description

Results of the AOP project are spatially aggregated on a H3 spatial grid at resolution 9, with a side of 174 meters and an area of 0.10 km2. More information about H3 at https://h3geo.org/docs/core-library/restable/. See the documentation 'Details' for the data dictionary.

Usage

read_grid(city = NULL, showProgress = FALSE)

Arguments

Value

An ⁠sf data.frame⁠ object

Data dictionary:

Cities available

Examples

# Read spatial grid of a single city
nat <- read_grid(city = 'Natal', showProgress = FALSE)

# Read spatial grid of all cities in the project
# all <- read_grid(city = 'all', showProgress = FALSE)

Download land use and population data

Description

Download data on the spatial distribution of population, jobs, schools, health care and social assitance facilities at a fine spatial resolution for the cities included in the AOP project. See the documentation 'Details' for the data dictionary. The data set reports information for each heaxgon in a H3 spatial grid at resolution 9, with a side of 174 meters and an area of 0.10 km2. More information about H3 at https://h3geo.org/docs/core-library/restable/.

Usage

read_landuse(city = NULL, year = 2019, geometry = FALSE, showProgress = TRUE)

Arguments

Value

A data.frame object or an ⁠sf data.frame⁠ object

Data dictionary:

Cities available

Examples

# a single city
bho <- read_landuse(city = 'Belo Horizonte', year = 2019, showProgress = FALSE)
bho <- read_landuse(city = 'bho', year = 2019, showProgress = FALSE)

# all cities
all <- read_landuse(city = 'all', year = 2019)

Download population and socioeconomic data

Description

Download population and socioeconomic data from the Brazilian Census at a fine spatial resolution for the cities included in the AOP project. See the documentation 'Details' for the data dictionary. The data set reports information for each heaxgon in a H3 spatial grid at resolution 9, with a side of 174 meters and an area of 0.10 km2. More information about H3 at https://h3geo.org/docs/core-library/restable/.

Usage

read_population(
  city = NULL,
  year = 2010,
  geometry = FALSE,
  showProgress = TRUE
)

Arguments

Value

A data.frame object or an ⁠sf data.frame⁠ object

Data dictionary:

Cities available

Examples

# a single city
bho <- read_population(city = 'Belo Horizonte', year = 2010, showProgress = FALSE)
bho <- read_population(city = 'bho', year = 2010, showProgress = FALSE)

# all cities
all <- read_population(city = 'all', year = 2010)

Select city input

Description

Subsets the metadata table by 'city'.

Usage

select_city_input(temp_meta = temp_meta, city = NULL)

Arguments

Value

A data.frame object with metadata subsetted by 'city'

Select metadata

Description

Subsets the metadata table by data 'type', 'city', 'year' and 'mode'

Usage

select_metadata(t = NULL, c = NULL, y = NULL, m = NULL)

Arguments

Value

A data.frame object with metadata subsetted by data type, 'city', 'year' and 'mode'

Select mode input

Description

Subsets the metadata table by 'mode'.

Usage

select_mode_input(temp_meta = temp_meta, mode = NULL)

Arguments

Value

A data.frame object with metadata subsetted by 'mode'

Select year input

Description

Subsets the metadata table by 'year'.

Usage

select_year_input(temp_meta = temp_meta, year = NULL)

Arguments

Value

A data.frame object with metadata subsetted by 'year'