Download accessibility estimates with population and land use data

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

city: Character. A city name or three-letter abbreviation. If city="all", the function returns data for all cities.
mode: Character. A transport mode. Modes available include 'public_transport', 'bicycle', or 'walk' (the default).
peak: Logical. If TRUE (the default), returns accessibility estimates during peak time, between 6am and 8am. If FALSE, returns accessibility during off-peak, between 2pm and 4am. This argument only takes effect when mode is either car or public_transport.
year: Numeric. A year number in YYYY format. Defaults to 2019.
geometry: Logical. If FALSE (the default), returns a regular data.table of aop data. If TRUE, returns an sf data.frame with simple feature geometry of spatial hexagonal grid H3. See details in read_grid.
showProgress: Logical. Defaults to TRUE display progress bar.

Value

A data.frame object

Data dictionary:

data_type	column	description	values
temporal	year	Year of reference
transport	mode	Transport mode	walk; bicycle; public_transport; car
transport	peak	Peak and off-peak	1 (peak); 0 (off-peak)

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

Indicator	Description	Observation
CMA	Cumulative opportunity measure (active)
CMP	Cumulative opportunity measure (passive)
TMI	Travel time to closest opportunity	Value = Inf when travel time is longer than 2h (public transport or car) or 1,5h (walking or bicycle)

2) Type of opportunity / population

Type of opportunity	Description	Observation: available in combination with
TT	All jobs	CMA indicator
TB	Jobs with primary education	CMA indicator
TM	Jobs with secondary education	CMA indicator
TA	Jobs with tertiary education	CMA indicator
ST	All healthcare facilities	CMA and TMI indicators
SB	Healthcare facilities - Low complexity	CMA and TMI indicators
SM	Healthcare facilities - Medium complexity	CMA and TMI indicators
SA	Healthcare facilities - High complexity	CMA and TMI indicators
ET	All public schools	CMA and TMI indicators
EI	Public schools - early childhood	CMA and TMI indicators
EF	Public schools - elementary schools	CMA and TMI indicators
EM	Public schools - high schools	CMA and TMI indicators
MT	All school enrollments	CMA and TMI indicators
MI	School enrollments - early childhood	CMA and TMI indicators
MF	School enrollments - elementary schools	CMA and TMI indicators
MM	School enrollments - high schools	CMA and TMI indicators
CT	All Social Assistance Reference Centers (CRAS)	CMA and TMI indicators

People	Description	Observation: available in combination with
PT	All population	CMP indicator
PH	Men	CMP indicator
PM	Women	CMP indicator
PB	White population	CMP indicator
PA	Asian-descendent population	CMP indicator
PI	Indigenous population	CMP indicator
PN	Back population	CMP indicator
P0005I	Population between 0 and 5 years old	CMP indicator
P0614I	Population between 6 and 14 years old	CMP indicator
P1518I	Population between 15 and 18 years old	CMP indicator
P1924I	Population between 19 and 24 years old	CMP indicator
P2539I	Population between 25 and 39 years old	CMP indicator
P4069I	Population between 40 and 69 years old	CMP indicator
P70I	Population with 70 years old or more	CMP indicator

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

Time threshold	Description	Observation: only applicable to
15	Opportunities accessible within 15 min.	Active transport modes
30	Opportunities accessible within 30 min.	All transport modes
45	Opportunities accessible within 45 min.	Active transport modes
60	Opportunities accessible within 60 min.	All transport modes
90	Opportunities accessible within 90 min.	Public transport and car
120	Opportunities accessible within 120 min.	Public transport and car

4) Cities available

City name	Three-letter abbreviation	Transport modes
Belem	`bel`	Active
Belo Horizonte	`bho`	All
Brasilia	`bsb`	Active
Campinas	`cam`	All
Campo Grande	`cgr`	Active
Curitiba	`cur`	Active
Duque de Caxias	`duq`	Active
Fortaleza	`for`	All
Goiania	`goi`	All
Guarulhos	`gua`	Active
Maceio	`mac`	Active
Manaus	`man`	Active
Natal	`nat`	Active
Porto Alegre	`poa`	All
Recife	`rec`	All
Rio de Janeiro	`rio`	All
Salvador	`sal`	Active
Sao Goncalo	`sgo`	Active
Sao Luis	`slz`	Active
Sao Paulo	`spo`	All

Examples

# Read accessibility estimates of a single city
df <- read_access(city = 'Fortaleza', mode = 'public_transport', year = 2019, showProgress = FALSE)
#> Using mode public_transport
#> Downloading accessibility data for the year 2019
#> Downloading land use data for the year 2019
#> Downloading population data for the year 2010
df <- read_access(city = 'Goiania', mode = 'public_transport', year = 2019, showProgress = FALSE)
#> Using mode public_transport
#> Downloading accessibility data for the year 2019
#> Downloading land use data for the year 2019
#> Downloading population data for the year 2010

# Read accessibility estimates for all cities
all <- read_access(city = 'all', mode = 'walk', year = 2019, showProgress = FALSE)
#> Using mode walk
#> Downloading accessibility data for the year 2019
#> Downloading land use data for the year 2019
#> Downloading population data for the year 2010