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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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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