DoU_classify_grid_urban_clusters {flexurba} | R Documentation |
Create the DEGURBA grid cell classification of urban clusters
Description
The Degree of Urbanisation identifies urban clusters as clusters of continuous grid cells (based on queen contiguity) with a minimum density of 300 inhabitants per km², and a minimum total population of 5000 inhabitants.
For more information about the Degree of Urbanisation methodology, see the methodological manual, GHSL Data Package 2022 and GHSL Data Package 2023.
The arguments of the function allow to adapt the standard specifications in the Degree of Urbanisation in order to construct an alternative version of the grid classification.
Usage
DoU_classify_grid_urban_clusters(
data,
classification,
density_threshold = 300,
size_threshold = 5000,
contiguity_rule = 8,
smooth_pop = FALSE,
smooth_pop_window = 5,
value = 2
)
Arguments
data |
path to the directory with the data, or named list with the data as returned by function |
classification |
SpatRaster. A grid with the classification of urban centres to which the classification of urban clusters will be added. Note that the grid will be adapted in-place. |
density_threshold |
numeric. Minimum population density per permanent land of a cell required to belong to an urban cluster |
size_threshold |
numeric. Minimum total population size required for an urban cluster |
contiguity_rule |
integer. Which cells are considered adjacent: |
smooth_pop |
logical. Whether to smooth the population grid before delineating urban clusters. If |
smooth_pop_window |
integer. Size of the moving window used to smooth the population grid before delineating urban clusters. Ignored when |
value |
integer. Value assigned to urban clusters in the resulting grid |
Value
SpatRaster with the grid cell classification of urban clusters
Examples
data_belgium <- DoU_load_grid_data_belgium()
classification <- DoU_classify_grid_urban_centres(data_belgium)
classification <- DoU_classify_grid_urban_clusters(data_belgium, classification = classification)
DoU_plot_grid(classification)