Introduction
As a major cultural, commercial, and transportation hub with a
population of over 1.7 million people, Montreal boasts diverse
neighborhoods and a vibrant arts and cultural scene. With an extensive
network of cycling infrastructure, the city is also ideal for
bike-sharing programs. In this presentation, I will explore bike-sharing
and cycling infrastructure in Montreal and propose recommendations to
enhance bike-sharing accessibility.
Hypothesis
Based on my analysis of bike-sharing stations and cycling
infrastructure in Montreal, I hypothesize that the low density of
bike-sharing stations leads to the underutilization of cycling as a mode
of transportation, contributing to increased air pollution in the
city.
Data Collection
Define the bounding box for Montreal
```{rmontreal_bbox <- c(-73.9860, 45.4121, -73.4730, 45.7006)
Download bike-sharing stations and cycling infrastructure data for
Montreal
```{rbike_sharing_query <- opq(bbox = montreal_bbox) %>%
add_osm_feature(key = “amenity”, value = “bicycle_rental”) %>%
osmdata_sf()
```{rcycling_infra_query <- opq(bbox = montreal_bbox) %>%
add_osm_feature(key = “highway”, value = “cycleway”) %>%
osmdata_sf()
Count the total number of bike-sharing stations
```{rtotal_stations <- nrow(bike_sharing_query$osm_points)
Calculate the total length of cycling infrastructure
```{rtotal_infra_length <-
sum(st_length(cycling_infra_query$osm_lines), na.rm = TRUE)
Create a data frame with the calculated values
```{rmontreal_data <- data.frame( category = c(“Bike-Sharing
Stations”, “Cycling Infrastructure Length (km)”), value =
c(total_stations, total_infra_length / 1000) )
Current State of Bike-Sharing Stations and Cycling
Infrastructure
The bar chart indicates a relatively low density of bike-sharing
stations compared to the length of cycling infrastructure. This
information is crucial for understanding the current accessibility of
bike-sharing programs in Montreal and can guide future recommendations
for network improvement.
Visualize the data using a bar chart
```{rbar_plot <- ggplot(montreal_data, aes(x = category, y =
value)) + geom_bar(stat = “identity”, fill = “steelblue”) +
theme_minimal() + labs(title = “Montreal Bike-Sharing Stations and
Cycling Infrastructure”, x = “Category”, y = “Value”)
Print the total number of bike-sharing stations and the total length
of cycling infrastructure
```{rcat(paste0(“Total bike-sharing stations:”, total_stations, “”))
cat(paste0(“Total cycling infrastructure length:”, total_infra_length, ”
km“))
Calculate the ratio of bike-sharing stations per 0.5 km of cycling
infrastructure
```{rstations_per_half_km <- total_stations / (total_infra_length
/ 2)
Print the ratio
```{rcat(paste0(“There are”, round(stations_per_half_km, 2), ”
bike-sharing stations per 0.5 km of cycling infrastructure in
Montreal.“))
Calculate the ratio of bike-sharing stations per linear km of
cycling infrastructure
```{rstations_per_km <- total_stations / (total_infra_length /
1000)
Print the ratio
```{rcat(paste0(“There are”, round(stations_per_km, 2), ”
bike-sharing stations per linear km of cycling infrastructure in
Montreal.“))
Current Density of Bike Sharing Stations
The map of Montreal highlights the locations of bike-sharing
stations and cycling infrastructure throughout the city, allowing us to
identify areas with gaps in bike-sharing accessibility or high
concentrations of bike-sharing stations and cycling infrastructure. This
information helps us make informed decisions about prioritizing the
placement of new bike-sharing stations and expanding cycling
infrastructure in Montreal.
Create a leaflet map showing the bike-sharing stations
```{rbike_sharing_map <- leaflet(bike_sharing_query$osm_points)
%>% addTiles() %>% addMarkers(clusterOptions =
markerClusterOptions())
Recommended Density of Bike-Sharing Stations
I propose increasing the density of bike-sharing stations in
Montreal using the Institute for Transportation and Development Policy’s
(ITDP) recommended density as a guide. The ITDP recommends a station
density of one station every 0.3-0.5 kilometers for dense urban areas
and one station every 0.5-1 kilometer for less densely populated areas.
Currently, Montreal’s bike-sharing density is low, with 0 stations per
0.5 km of cycling infrastructure.
Display the bar chart and the leaflet map
{rprint(bar_plot){rprint(bike_sharing_map)
Bike-Sharing Impact
Implementing bike-sharing programs in cities can bring numerous
benefits, including generating economic activity and promoting
sustainable transportation. By increasing the availability of
bike-sharing stations in Montreal, the city can work towards a more
sustainable future and positively impact the health and wellbeing of its
citizens.