uci: Urban Centrality Index

uci is an R package to calculate the Urban Centrality Index (UCI) originally proposed by Pereira et al., (2013). The UCI measures the extent to which the spatial organization of a city or region varies from extreme polycentric to extreme monocentric in a continuous scale from 0 to 1. Values close to 0 indicate more polycentric patterns and values close to 1 indicate a more monocentric urban form. More info on this vignette.

• Link to ungated PDF of the Pereira et al., (2013) paper

Installation

# from CRAN
install.packages('uci')

# or use the development version with latest features
utils::remove.packages('uci')
devtools::install_github("ipeaGIT/uci")

Basic Usage

library(uci)

# load data
data_dir <- system.file("extdata", package = "uci")
grid <- readRDS(file.path(data_dir, "grid_bho.rds"))

head(grid)
#> Simple feature collection with 6 features and 4 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -43.96438 ymin: -19.97414 xmax: -43.93284 ymax: -19.96717
#> Geodetic CRS:  WGS 84
#>                id population jobs schools                       geometry
#> 1 89a881a5a2bffff        439  180       0 POLYGON ((-43.9431 -19.9741...
#> 2 89a881a5a2fffff        266  134       0 POLYGON ((-43.94612 -19.972...
#> 3 89a881a5a67ffff       1069  143       0 POLYGON ((-43.94001 -19.972...
#> 4 89a881a5a6bffff        245   61       0 POLYGON ((-43.9339 -19.9728...
#> 5 89a881a5a6fffff        298   11       0 POLYGON ((-43.93691 -19.971...
#> 6 89a881a5b03ffff        555 1071       0 POLYGON ((-43.96136 -19.970...

# calculate UCI
df <- uci(
       sf_object = grid,
       var_name = 'jobs',
       bootstrap_border = FALSE,
       showProgress = TRUE
       )

head(df)
#>         UCI location_coef spatial_separation spatial_separation_max
#> 1 0.2538635     0.5278007           3880.114               7475.899

Citation

The R package uci is developed by a team at the Institute for Applied Economic Research (Ipea), Brazil. If you use this package in research publications, please cite it as:

• Pereira, R. H. M., Nadalin, V., Monasterio, L., & Albuquerque, P. H. (2013). Urban centrality: a simple index. Geographical analysis, 45(1), 77-89. https://www.doi.org/10.1111/gean.12002

BibTeX:

@article{pereira2013urbancentrality,
  title = {Urban {{Centrality}}: {{A Simple Index}}},
  author = {Pereira, Rafael H. M. and Nadalin, Vanessa and Monasterio, Leonardo and Albuquerque, Pedro H. M.},
  year = {2013},
  journal = {Geographical Analysis},
  volume = {45},
  number = {1},
  pages = {77--89},
  issn = {1538-4632},
  doi = {10.1111/gean.12002}
}

Acknowledgement

The Hex image above illustrates Christaller’s Central Place Theory. It was adapted from an image originally created by Christaller and adapted by Becerra, 2015.