geobr (version 1.9.1)

read_semiarid: Download spatial data of the Brazilian Semiarid region

Description

This data set covers the whole of Brazilian Semiarid as defined in the resolution in 23/11/2017). The original data comes from the Brazilian Institute of Geography and Statistics (IBGE) and can be found at https://www.ibge.gov.br/geociencias/cartas-e-mapas/mapas-regionais/15974-semiarido-brasileiro.html?=&t=downloads

Usage

read_semiarid(
  year = 2017,
  simplified = TRUE,
  showProgress = TRUE,
  cache = TRUE
)

Value

An "sf" "data.frame" object

Arguments

year

Numeric. Year of the data in YYYY format. Defaults to 2017.

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.

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_municipality(), read_neighborhood(), read_pop_arrangements(), read_region(), read_schools(), read_state(), read_statistical_grid(), read_urban_area(), read_urban_concentrations(), read_weighting_area()

Examples

if (FALSE) { # identical(tolower(Sys.getenv("NOT_CRAN")), "true")
# Read Brazilian semiarid
a <- read_semiarid(year=2017)
}