geobr

geobr is an R package that allows users to easily access shapefiles of the Brazilian Institute of Geography and Statistics (IBGE) and other official spatial data sets of Brazil. The package includes a wide range of geographic datasets as simple features, available at various geographic scales and for various years (see detailed list below):

Installation

# From CRAN
  install.packages("geobr")
  library(geobr)

# or use the development version with latest features
  devtools::install_github("ipeaGIT/geobr")
  library(geobr)

Basic Usage

# Read specific municipality at a given year
mun <- read_municipality(code_muni=1200179, year=2017)

# Read all municipalities of a state at a given year
mun <- read_municipality(code_muni=33, year=2010)
# alternatively
mun <- read_municipality(code_muni="RJ", year=2010)

# Read all municipalities in the country at a given year
mun <- read_municipality(code_muni="all", year=2018)

More examples here and in the intro Vignette

Available datasets:

Function	Geographies available	Years available	Source
read_country	Country	1872, 1900, 1911, 1920, 1933, 1940, 1950, 1960, 1970, 1980, 1991, 2000, 2001, 2010, 2013, 2014, 2015, 2016, 2017, 2018	IBGE
read_region	Region	2000, 2001, 2010, 2013, 2014, 2015, 2016, 2017, 2018	IBGE
read_state	States	1872, 1900, 1911, 1920, 1933, 1940, 1950, 1960, 1970, 1980, 1991, 2000, 2001, 2010, 2013, 2014, 2015, 2016, 2017, 2018	IBGE
read_meso_region	Meso region	2000, 2001, 2010, 2013, 2014, 2015, 2016, 2017, 2018	IBGE
read_micro_region	Micro region	2000, 2001, 2010, 2013, 2014, 2015, 2016, 2017, 2018	IBGE
read_municipality	Municipality	1872, 1900, 1911, 1920, 1933, 1940, 1950, 1960, 1970, 1980, 1991, 2000, 2001, 2005, 2007, 2010, 2013, 2014, 2015, 2016, 2017, 2018	IBGE
read_weighting_area	Census weighting area (área de ponderação)	2010	IBGE
read_census_tract	Census tract (setor censitário)	2000, 2010	IBGE
read_statistical_grid	Statistical Grid of 200 x 200 meters	2010	IBGE
read_health_facilities	Health facilities	2015	CNES, DataSUS
read_indigenous_land (dev.)	Indigenous lands	201907	FUNAI

Note 1. Functions marked with "dev." are only available in the development version of geobr.

Note 2. All datasets use geodetic reference system "SIRGAS2000", CRS(4674). Most data sets are available at scale 1:250,000 (see documentation for details).

Coming soon:

Geography	Years available	Source
read_census_tract	2007	IBGE
read_indigenous_territory	201907	FUNAI
Metropolitan areas	...	IBGE and state legislations
Longitudinal Database* of municipalities	...	IBGE
Longitudinal Database* of micro regions	...	IBGE
Longitudinal Database* of Census tracts	...	IBGE
Urbanized areas	2005, 2015	IBGE
Disaster risk areas	2010	IBGE/Cemaden
Schools	2019	School Census (Inep)
...	...	...
...	...	...

'*' Longitudinal Database refers to áreas mínimas comparáveis (AMCs)

• Quadro geográfico de referência para produção, análise e disseminação de estatísticas
• Regiões Metropolitanas, Aglomerações Urbanas e Regiões Integradas de Desenvolvimento
• Outros arquivos e recortes estão disponiveis em ftp://geoftp.ibge.gov.br/.

Credits

The shapefiles are created by IBGE. The geobr package is developed by a team at the Institute for Applied Economic Research (Ipea), Brazil. If you want to cite this package, you can cite it as:

• Pereira, R.H.M.; Gonçalves, C.N.; Araujo, P.H.F. de; Carvalho, G.D.; Nascimento, I.; Arruda, R.A. de. (2019) geobr: an R package to easily access shapefiles of the Brazilian Institute of Geography and Statistics. GitHub repository - https://github.com/ipeaGIT/geobr.

Advantages of geobr and related projects

As of today, there are two other R packges with similar functionalities. These are the packages simplefeaturesbr and brazilmaps. The geobr package follows an intuitive syntax and it has a few advantages when compared to other packages, including for example:

• Access to a wider range of official spatial data sets, such as states and municipalities, but also macro-, meso- and micro-regions, weighting areas, census tracts, urbanized areas, etc
• Access to shapefiles with updated geometries for various years
• Harmonized attributes and geographic projections across geographies and years