geobr is an R package that allows users to easily access official spatial data sets of Brazil. The package includes a wide range of geospatial data as simple features, available at various geographic scales and for various years (see detailed list below):
# From CRAN
install.packages("geobr")
library(geobr)
# or use the development version with latest features
utils::remove.packages('geobr')
devtools::install_github("ipeaGIT/geobr")
library(geobr)
obs. If you use Linux, you need to install a couple dependencies before installing the libraries sf
and geobr
. More info here.
# 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
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 |
read_biomes (dev.) |
Biomes | 2004, 2019 | IBGE |
read_disaster_risk_area (dev.) |
Disaster risk areas | 2010 | CEMADEN and IBGE |
read_amazon (dev.) |
Brazil's Legal Amazon | 2012 | MMA |
read_conservation_units (dev.) |
Environmental Conservation Units | 201909 | MMA |
read_urban_area (dev.) |
Urban footprints | 2005, 2015 | IBGE |
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).
Geography | Years available | Source |
---|---|---|
read_census_tract |
2007 | IBGE |
Metropolitan areas | ... | IBGE and state legislations |
Longitudinal Database* of municipalities | ... | IBGE |
Longitudinal Database* of micro regions | ... | IBGE |
Longitudinal Database* of Census tracts | ... | IBGE |
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/.
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.
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