Abstracting mobility flows from OD17 bike trips
Using data from a very comprehensive São Paulo origin-destination survey conducted by the São Paulo Metro Company, we grouped all bike trips from an origin region to a destination one into a single abstract flow, which represents those trips. Thus, urban planners can better visualize the distribution of bike trips through the city more clearly. The bottom image shows bike flows between the rectangular areas in the morning. Click on the image to see the interactive map.
Statistical analysis of bike trips from the OD17 travel survey
The OD17 travel survey has a lot of data regarding mobility, including coordinates of origin and destination, transportation modals used on the trips, demographic and socioeconomic profiles, and so on. We performed several statistical analyses of the OD17 data to provide a better overview of the survey.
Collecting of routes for the OD17 trips
The OD17 survey has the origin and destination coordinates of the trips. We collected suggested bike routes for the trips of the OD17 survey using the GraphHopper API. The routes let us identify suitable places where bike trips may occur. These routes are now used for several of our other analyses. We also collected routes for the other transport modes. Click on the image to see the interactive map. The routes dataset is available on our open datasets page .
Comparison of bike flow countings and OD17 bike trips
We compared the bike flow countings performed by CET with the number of trips each bike route represents. Thus, it is possible to see places that have bike trips and should be covered in future bike countings. It is also possible to compare the number of trips from OD17 with matching bike countings. The image below shows the locations where the counting occurred, some of them overlapping the OD17 Bike routes. Click on the images to see the interactive maps.
This other map shows bike counting locations that overlap with more bike routes.
Locations in São Paulo with more bike trips
We used the OD17 bike routes to estimate locations with a higher concentration of trips. To do this, we sum the number of trips of overlapping coordinates from all bike trips, plotting the results on a map for a better overview. The images below show the interactive maps with places with more daily bike trips and more overlapping bike routes, respectively. Click on the maps to see them in more details.
Comparison of sidewalks and OD17 pedestrian routes
In this analysis, we use shapefiles from sidewalks, pedestrian routes from OD17, and pedestrian counts from CET to identify sidewalks that should be prioritized for repair. It is also possible to compare locations with a higher concentration of pedestrian trips for other future policies. The following image shows a sample of the OD17 pedestrian routes in the middle of SP downtown.
The image below is a heatmap of pedestrian countings made by the CET staff during the morning.
Trip potential for new bike infrastructures
We cross the number of trips from OD17 bike routes and shapefiles from proposed bike infrastructures. Then, we created an index of those infrastructures that could have higher trip loads. This analysis can be used to help prioritize the construction of new bike infrastructure. The following map shows different load levels (daily trips). Access the map for more details.
The following image shows the computed potential for the cycling infrastructure that already exists, which allows us to compare the current load according to the OD17 data.
Grouping planned bike infrastructures by administrative regions
This work provides an overview of current and proposed bike infrastructures per administrative regions (e.g., subprefectures, districts). The maps were devised to be used in the public audiences for the discussion of the new bike infrastructures. The following map shows a choropleth map (density) with kilometers of planned bike lanes for each subprefecture.
This other map shows the density per subprefecture for the current bike infrastructure, also including subway and train stations.
Evolution of bike infrastructures
A collection of maps with the bike infrastructure of São Paulo through the years. We can see below the evolution between 2008 and 2021. The chart shows how many kilometers of bike lanes were built per year.
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Statistical analysis for the estimation of bike trip migrations
We produced several statistical charts from OD17 for all transportation modes (e.g., car trips with less than 6 kilometers) to provide a background for a study on migration for the bike mode. This information was used to perform an initial estimation of the number of trips that could be done using bicycles.
BikeScienceWeb
We implemented a web version of the BikeScience tool (BikeScienceWeb) to facilitate access to some of the analyses we are doing. Thus, those interested in active urban mobility can make their own analyses without knowledge of programming or installing any technology dependencies. The following image shows flows that start in the afternoon over OD zones. Access BikeScienceWeb here .
The map below shows bike flows of low-income cyclists starting trips in the morning over grid cells.
Bike owners by region in São Paulo
We also produced maps showing the locations where there are more biker owners according to the OD17 survey. These maps show the concentrations of bicycles in different aggregation regions, such as subprefectures and districts. The following map shows the density of bicycles per population for the city districts.
The image above shows the number of bibycles that cyclists have in their houses.
New bike routes near public transport stations
In this study, we are using census data from regions near public transport stations (e.g., subway and train) to suggest bike routes that would turn new bike lanes. The idea is that those regions with high population densities may suggest bike lanes that would carry a high number of trips.
Results are coming soon.
