R/read_metro_area.R
read_metro_area.RdThe function returns the shapes of municipalities grouped by their respective metro areas. Metropolitan areas are created by each state in Brazil. The data set includes the municipalities that belong to all metropolitan areas in the country according to state legislation in each year. Original data were generated by Institute of Geography. Data at scale 1:250,000, using Geodetic reference system "SIRGAS2000" and CRS(4674).
read_metro_area(
year = 2018,
code_state = "all",
simplified = TRUE,
showProgress = TRUE
)Numeric. Year of the data in YYYY format. Defaults to 2018.
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.
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
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_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 all official metropolitan areas for a given year
m <- read_metro_area(2005)
m <- read_metro_area(2018)