geobr 0.1.5

geobr: Loads Shapefiles of Official Spatial Data Sets of Brazil

geobr

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

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

pip install geobr

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:

R

# 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

Python

from geobr import read_municipality

# 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

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_municipal_seat	Municipality seats (sedes municipais)	1872, 1900, 1911, 1920, 1933, 1940, 1950, 1960, 1970, 1980, 1991, 2010	IBGE
read_statistical_grid	Statistical Grid of 200 x 200 meters	2010	IBGE
read_metro_area	Metropolitan areas	1970, 2001, 2002, 2003, 2005, 2010, 2013, 2014, 2015, 2016, 2017, 2018	IBGE
read_urban_area	Urban footprints	2005, 2015	IBGE
read_amazon	Brazil's Legal Amazon	2012	MMA
read_biomes	Biomes	2004, 2019	IBGE
read_conservation_units	Environmental Conservation Units	201909	MMA
read_disaster_risk_area	Disaster risk areas	2010	CEMADEN and IBGE
read_indigenous_land	Indigenous lands	201907	FUNAI
read_semiarid	Semi Arid region	2005, 2017	IBGE
read_health_facilities	Health facilities	2015	CNES, DataSUS
read_neighborhood (dev)	Neighborhood limits	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)

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

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.

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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

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Credits

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.