README.md

Tool to estimate bicycle flows throughout the network of metropolitan Paris, France.

How?

Start by installing and loading the package:

remotes::install_github ("UrbanAnalyst/paris-bikes")
library (parisbikes)

Then just two steps. First, get the street network of Paris (or anywhere) from Open Street Map.

path <- "<local>/<directory>/<for>/<paris>/<data>"
pb_get_network (location = "Paris France", path)

That function will create a file called “paris-sc.Rds” in the location specified by “path”. Then load the resultant network and use that to calculate centrality:

dat <- readRDS ("/<path>/<to>/paris-sc.Rds")
network <- pb_centrality (dat, mode = "bicycle")

It is also possible to calculate centrality including the effects of elevation changes, by specifying an additional “elev_file” parameter as the path to a local ‘geotiff’ elevation file. See the function documentation of pb_centrality for details.

Visualising the results

The following code can be used to visualise the resultant network centrality, using the mapdeck package (which first requires an API token, as explained in the documentation). The following code rescales the centrality measures using a value of 3.71 derived elsewhere to optimally match observed distributions of cycling densities in Paris.

index <- which (network$centrality > 0)
network <- dodgr::merge_directed_graph (network [index, ])
network$flow <- network$centrality / max (network$centrality)
network$flow <- network$flow ^ (1 / 3.71)
network$width <- 5 * network$flow

The following lines will then open an interactive visualization of the flow densities throughout Paris.

library (mapdeck)
mapdeck (style = mapdeck_style ()) %>%
    add_line (net, 
              origin = c (".vx0_x", ".vx0_y"),
              destination = c (".vx1_x", ".vx1_y"),
              stroke_colour = "flow",
              stroke_width = "width",
              stroke_opacity = "flow",
              palette = "matlab_like2",
              legend = TRUE)