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Download spatial data of Brazilian states

Source: R/read_state.R
read_state.Rd

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

Usage

read_state(
  code_state = "all",
  year = 2010,
  simplified = TRUE,
  showProgress = TRUE,
  cache = TRUE
)

Arguments

code_state

The two-digit code of a state or a two-letter uppercase abbreviation (e.g. 33 or "RJ"). If code_state="all" (the default), the function downloads all states.

year

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

simplified

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.

showProgress

Logical. Defaults to TRUE display progress bar.

cache

Logical. Whether the function should read the data cached locally, which is faster. Defaults to cache = TRUE. By default, geobr stores data files in a temporary directory that exists only within each R session. If cache = FALSE, the function will download the data again and overwrite the local file.

Value

An "sf" "data.frame" object

See also

Other area functions: read_amazon(), read_biomes(), read_capitals(), read_comparable_areas(), read_country(), 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_statistical_grid(), read_urban_area(), read_urban_concentrations(), read_weighting_area()

Examples

# Read specific state at a given year
  uf <- read_state(code_state=12, year=2017)
#> Using year/date 2017

# Read specific state at a given year
  uf <- read_state(code_state="SC", year=2000)
#> Using year/date 2000

# Read all states at a given year
  ufs <- read_state(code_state="all", year=2010)
#> Using year/date 2010