read_meso_region: Download spatial data of meso regions

View source: R/read_meso_region.R

read_meso_regionR Documentation

Download spatial data of meso regions

Description

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

Usage

read_meso_region(
  code_meso = "all",
  year = 2010,
  simplified = TRUE,
  showProgress = TRUE
)

Arguments

code_meso

The 4-digit code of a meso 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 meso regions of that state. If code_meso="all" (Default), the function downloads all meso regions of the country.

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_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


# Read specific meso region at a given year
  meso <- read_meso_region(code_meso=3301, year=2018)

# Read all meso regions of a state at a given year
  meso <- read_meso_region(code_meso=12, year=2017)
  meso <- read_meso_region(code_meso="AM", year=2000)

# Read all meso regions of the country at a given year
  meso <- read_meso_region(code_meso="all", year=2010)


geobr documentation built on Sept. 21, 2023, 9:07 a.m.