R/read_intermediate_region.R
read_intermediate_region.RdThe intermediate Geographic Areas are part of the geographic division of Brazil created in 2017 by IBGE. These regions were created to replace the "Meso Regions" division. Data at scale 1:250,000, using Geodetic reference system "SIRGAS2000" and CRS(4674)
read_intermediate_region(
code_intermediate = "all",
year = 2019,
simplified = TRUE,
showProgress = TRUE,
cache = TRUE
)4-digit code of an intermediate region. If the
two-digit code or a two-letter uppercase abbreviation of a state is
passed, (e.g. 33 or "RJ") the function will load all intermediate
regions of that state. If code_intermediate="all" (Default), the
function downloads all intermediate regions of the country.
Numeric. Year of the data in YYYY format. Defaults to 2019.
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.
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.
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_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 an specific intermediate region
im <- read_intermediate_region(code_intermediate=1202)
# Read intermediate regions of a state
im <- read_intermediate_region(code_intermediate=12)
im <- read_intermediate_region(code_intermediate="AM")
# Read all intermediate regions of the country
im <- read_intermediate_region()
im <- read_intermediate_region(code_intermediate="all")