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Easy access to official spatial data sets of Brazil in R (and soon in Python too)
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README.md

geobr logo logo

geobr is a computational package to download official spatial data sets of Brazil. The package includes a wide range of geospatial data as simple features or geopackages, available at various geographic scales and for various years with harmonized attributes, projection and topology (see detailed list of available data sets below).

The package is currently available in R. The Python version is under development.

R Python
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(under development)

Installation R

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

# or use the development version with latest features
  utils::remove.packages('geobr')
  devtools::install_github("ipeaGIT/geobr", subdir = "r-package")
  library(geobr)

obs. If you use Linux, you need to install a couple dependencies before installing the libraries sf and geobr. More info here.

Installation Python

under development

obs. If you use Linux, you need to install a couple dependencies before installing the libraries sf and geobr. More info here.

Basic Usage

The syntax of all geobr functions operate one the same logic so it becomes intuitive to download any data set using a single line of code. Like this:

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

# Read all municipalities of given state at a given year
mun <- read_municipality(code_muni=33, year=2010) # or
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_intermediate_region Intermediate region 2017 IBGE
read_immediate_region Immediate region 2017 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 Indigenous lands 201907 FUNAI
read_biomes Biomes 2004, 2019 IBGE
read_disaster_risk_area Disaster risk areas 2010 CEMADEN and IBGE
read_amazon Brazil's Legal Amazon 2012 MMA
read_conservation_units Environmental Conservation Units 201909 MMA
read_urban_area Urban footprints 2005, 2015 IBGE
read_semiarid Semi Arid region 2005, 2017 IBGE
read_metro_area Metropolitan areas 1970, 2001, 2002, 2003, 2005, 2010, 2013, 2014, 2015, 2016, 2017, 2018 IBGE
read_municipal_seat Municiopal seat (sede dos municipios) 1872, 1900, 1911, 1920, 1933, 1940, 1950, 1960, 1970, 1980, 1991, 2010 IBGE

Other functions:

Function Action
list_geobr List all datasets available in the geobr package
lookup_muni Look up municipality codes by their name, or the other way around
grid_state_correspondence_table Loads a correspondence table indicating what quadrants of IBGE's statistical grid intersect with each state
... ...

Note 1. Data sets and 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
Longitudinal Database* of municipalities various years IBGE
Longitudinal Database* of micro regions various years IBGE
Longitudinal Database* of Census tracts various years IBGE
Schools 2019 School Census (Inep)
... ... ...

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

Contributing to geobr

If you would like to contribute to geobr and add new functions or data sets, please check this guide to propose your contribution.


Related projects

As of today, there are two other R packages with similar functionalities: simplefeaturesbr and brazilmaps. The geobr package has a few advantages when compared to these other packages, including for example:

  • A same syntax structure across all functions, making the package very easy and intuitive to use
  • 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

Credits ipea

Original shapefiles are created by official government institutions. 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.; et. all (2019) geobr: Loads Shapefiles of Official Spatial Data Sets of Brazil. GitHub repository - https://github.com/ipeaGIT/geobr.
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