Skip to contents

Download spatial data of historically comparable municipalities

Source: R/read_comparable_areas.R
read_comparable_areas.Rd

This function downloads the shape file of minimum comparable area of municipalities, known in Portuguese as 'Areas minimas comparaveis (AMCs)'. The data is available for any combination of census years between 1872-2010. These data sets are generated based on the Stata code originally developed by Ehrl (2017) doi:10.1590/0101-416147182phe , and translated into R by the geobr team.

Usage

read_comparable_areas(
  start_year = 1970,
  end_year = 2010,
  simplified = TRUE,
  showProgress = TRUE,
  cache = TRUE
)

Arguments

start_year

Numeric. Start year to the period in the YYYY format. Defaults TO 1970.

end_year

Numeric. End year to the period in the 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

Details

These data sets are generated based on the original Stata code developed by Philipp Ehrl. If you use these data, please cite:

  • Ehrl, P. (2017). Minimum comparable areas for the period 1872-2010: an aggregation of Brazilian municipalities. Estudos Econômicos (São Paulo), 47(1), 215-229. https://doi.org/10.1590/0101-416147182phe

See also

Other area functions: read_amazon(), read_biomes(), read_capitals(), 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_state(), read_statistical_grid(), read_urban_area(), read_urban_concentrations(), read_weighting_area()

Examples

  amc <- read_comparable_areas(start_year=1970, end_year=2010)
#> Using year/date 1970