read_country: Download spatial data of Brazil's national borders

View source: R/read_country.R

read_countryR Documentation

Download spatial data of Brazil's national borders


Data at scale 1:250,000, using Geodetic reference system "SIRGAS2000" and CRS(4674).


read_country(year = 2010, simplified = TRUE, showProgress = TRUE)



Numeric. Year of the data in YYYY format. Defaults to 2010.


Logic FALSE or TRUE, indicating whether the function should return the data set with 'original' spatial resolution or a data set with 'simplified' geometry. Defaults to TRUE. For spatial analysis and statistics users should set simplified = FALSE. Borders have been simplified by removing vertices of borders using ⁠st_simplify{sf}⁠ preserving topology with a dTolerance of 100.


Logical. Defaults to TRUE display progress bar.


An ⁠"sf" "data.frame"⁠ object

See Also

Other area functions: read_amazon(), read_biomes(), read_capitals(), read_comparable_areas(), read_disaster_risk_area(), read_health_facilities(), read_health_region(), read_immediate_region(), read_indigenous_land(), read_intermediate_region(), read_meso_region(), read_metro_area(), read_micro_region(), read_municipal_seat(), read_municipality(), read_neighborhood(), read_pop_arrangements(), read_region(), read_schools(), read_semiarid(), read_state(), read_statistical_grid(), read_urban_area(), read_urban_concentrations(), read_weighting_area()


# Read specific year
br <- read_country(year = 2018)

geobr documentation built on Sept. 21, 2023, 9:07 a.m.