Extracts surface areas by urban and rural categories from GHS-SMOD

Calculates the surface area (in km2) of urban, rural, or all settlement classes every 5 years between 1985 and 2030 using the GHS-SMOD R2023A dataset. This product applies the Degree of Urbanization methodology (Stage I) to the GHS-POP R2023A and GHS-BUILT-S R2023A layers. The function summarizes areas by category and year over the specified region.

Usage

l4h_urban_rural_area(
  region,
  category = "all",
  scale = 1000,
  sf = TRUE,
  quiet = FALSE,
  force = FALSE,
  ...
)

Arguments

region: An sf object defining the region of interest.
category: Character. Settlement category to extract: "urban", "rural", or "all".
scale: Numeric. Spatial resolution (in meters) to use for area calculation (e.g., 30).
sf: Logical. If TRUE, returns an sf object. Default is TRUE.
quiet: Logical. If TRUE, suppresses progress messages. Default is FALSE.
force: Logical. If TRUE, forces the extraction request even if cached results exist.
...: Additional arguments passed to ee_extract() from the rgee package.

Value

A tibble with estimated settlement area (in km2) by year and category.

Credits

Pioneering geospatial health analytics and open‐science tools. Developed by the Innovalab Team, for more information send a email to imt.innovlab@oficinas-upch.pe

References

European Commission, Joint Research Centre (JRC). GHS Settlement Grid R2023A (1975–2030). Available at: https://data.jrc.ec.europa.eu/dataset/a0df7a6f-49de-46ea-9bde-563437a6e2ba#dataaccess

Examples

if (FALSE) { # \dontrun{
library(land4health)
ee_Initialize()

# Define region as a bounding box (Ucayali, Peru)
region <- st_as_sf(st_sfc(
  st_polygon(list(matrix(c(
    -74.1, -4.4,
    -74.1, -3.7,
    -73.2, -3.7,
    -73.2, -4.4,
    -74.1, -4.4
  ), ncol = 2, byrow = TRUE))),
  crs = 4326
))

# Extract surface area of urban category (in km2)
urban_area <- l4h_urban_area(
  category = "urban",
  region = region)

head(urban_area)

# Extract surface area of rural category (in km2)
rural_area <- l4h_urban_area(
  category = "rural",
  region = region)

head(rural_area)

# Extract total surface area (urban + rural) (in km2)
all_area <- l4h_urban_area(
  category = "all",
  region = region)

head(all_area)
} # }