SiteSelection

Script for a site selection - Streets4All Project.

About

SiteSelection aims to find areas for a dynamic street realocation experiment.

It selects the cell locations of a giver city or neighborhood where the street space is more disputed by different transport modes and street activities. SiteSelection is a full script that uses a dynamic pipeline, and gathers and processes information on:

• Population density
• Road network centrality measures
• Traffic levels
• Public Transit demand
• POI and activities

This work is part of Streets4All Project, developed at the University of Lisbon and at the University of Coimbra, and funded by Fundação para a Ciência e Tecnologia (PT).

Sources

The SiteSelection package is based in Portuguese open datasets, such as census and GTFS data.

Although it is easy to run for any location in Portugal, you may adapt the code to run at other locations (considering you have the similar data needed).

Data needed for other locations:

• Census data (population and buildings)
• POIs
• GTFS data
• Administrative boundaries

Setup

Requirements

• QGis and qgis_process installed and working
• targets R package.
• siteselection R package [under development].

Change defaults

Open the _targets.R file and change the defaults to your needs (don’t forget to save the file before run!):

# Set defaults HERE ######################
CITY_input = "Almada"
cellsize_input = c(200, 200)
square_input = TRUE #TRUE = squares, FALSE = hexagons
build_osm = FALSE #clean osm road network again?

# Thresholds
population_min = mean # mean or median? default: mean
degree_min = mean # mean or median? default: mean
betweeness_range = 0.4 # percentile to exclude (upper and lower) default: 0.25
closeness_range = 0.25 # value to exclude (upper and lower) default: 0.25
entropy_min = 0.35 # value to exclude (lower) default: 0.5

Run the pipeline

library(targets)
tar_visnetwork(targets_only = FALSE) # or true, to hide objects

And you should have something like this

tar_make()
# let it run

tar_load(candidates_centrality)
mapview::mapview(candidates_centrality, zcol = "degree")

You can also load other objects, such as candidates_all, candidates_centrality, candidates_entropy, candidates_traffic, candidates_transit, candidates_density.

When the process is not complete, you may have an error like this

tar_visnetwork()

Work in Progress