read_municipality {geobr}

Download spatial data of Brazilian municipalities

Description

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

Usage

read_municipality(
  code_muni = "all",
  year = 2010,
  simplified = TRUE,
  showProgress = TRUE
)

Arguments

code_muni

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.

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.

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_neighborhood(), read_pop_arrangements(), read_region(), read_schools(), read_semiarid(), read_state(), read_statistical_grid(), read_urban_area(), read_urban_concentrations(), read_weighting_area()

Examples

# 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)