R/read_municipality.R
read_municipality.Rd
Data at scale 1:250,000, using Geodetic reference system "SIRGAS2000" and CRS(4674).
read_municipality(
code_muni = "all",
year = 2010,
simplified = TRUE,
showProgress = TRUE
)
The 7-digit identification code of a municipality. If
code_muni = "all"
(Default), the function downloads all
municipalities of the country. Alternatively, if a two-digit
identification code or a two-letter uppercase abbreviation of a state
is passed (e.g. 33
or "RJ"
), all municipalities of that state will
be downloaded. Municipality identification codes can be consulted with
the geobr::lookup_muni()
function.
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
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_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 municipality at a given year
mun <- read_municipality(code_muni = 1200179, year = 2017)
# Read all municipalities of a state at a given year
mun <- read_municipality(code_muni = 33, year = 2010)
mun <- read_municipality(code_muni = "RJ", year = 2010)
# Read all municipalities of the country at a given year
mun <- read_municipality(code_muni = "all", year = 2018)