Bicycle Trips by Time of Day
The Riderlog application which is the source of the data used to create this map, records the location of bicycle riders at approximately 40 second intervals. The map illustrates bicycle riders in the greater Sydney area on Mondays through Fridays from May 2010 through May 2014. The map shows 1,158 bicyclists on 13,484 bicycling routes. The map shows heavy bicycling activity in the Sydney CBD and Centennial Park. The time slider shows two pulses of heavy cycling activity, from 6:00 through 9:00 AM and from 4:30 – 7:30 PM.
Bicycle Trips by Gender
According to the Bicycle Network, the ratio of female to male riders is a leading indicator of cycling health within a city. Cities and routes that are bicycle friendly typically have greater than 35% female riders, more automobile focused areas will only have 15% - 20% female riders. Sydney falls into this second category. Using the Riderlog data for the Sydney region where bicycling routes are mapped by gender clearly illustrates those areas where there tend to be more female riders (highlighted in pink) as well as areas where there are mostly male riders (indicated in blue). In Sydney, female bicycling activity tends to occur where there is dedicated cycle infrastructure such as along Bourke St, Anzac Parade and in Centennial Park. Overall, the analysis of this cycling data by gender breakdown indicates that Sydney is currently not a bicycle friendly city.
Bicycle Trips by Age
The Riderlog application which is the source of the data used to create this map, records the age of the bicyclist. We can see from the map and the underlying data that the majority of riders fit into the following three age cohorts (i) 26-35yrs - 25%, (ii) 36-45yrs - 27% and (iii) 46-55yrs - 32%. The proportion of cyclists using the Riderlog app drops off significantly for the 18-25 yrs category - 2%. Preliminary analysis of this age based data would suggest policy makers might like to target bicycle promotion programs to those aged 25 years and below in order to increase bicyclist numbers across the City.
Bicycle Trips by Duration
This map illustrates the travel time required by bicyclists to travel from their origin to their destination. Most trips are in the range of just over ½ hour which allows bicyclists to travel about 9 kilometres. At the same time the map shows a willingness of riders from all areas, including outlying areas, to travel to the centre of Sydney. This sort of travel behaviour information is useful in understanding when developing and implementing strategies such as Sydney's Cycling Future where a 5km bike riding catchment is used as the key metric. Analysis of the riderlog duration data indicates that 35% of cycle journeys are made within the 5-10km distance with only 21% of journeys made between 0-5km. Therefore the analysis of the data suggests that the riding catchment should be extended to 10kms.
Bicycle Trips by Purpose
The Riderlog app allows users to input information indicating the purpose of each of their bicycling trips. The map shows the majority of trips that start or end in the Sydney local government area are indicated by app users as being for transportation purposes. While the map shows several categories of recreation and transportation, the data may be summarized as being 83.6% transport trips and 16.3 % recreational trips based on 7,121 observations. The map shows heavy recreational use of Centennial Park as well as recreational bicycling along Sydney Harbour and the eastern beaches. Most users of the Riderlog app are bicycling for transport purposes and this can provide us with a good understanding of commuting and other transport behaviours as bicyclists traverse the city.
Bicycle Trips by Origin
Mapping rider origin and cycling route shows both areas where bicyclists reside as well as use patterns across the city. As shown in the previous maps, most bicycle trips recorded using the Riderlog App are to the centre of the City of Sydney as the final destination. This rider origin data can be used to highlight suburbs and precincts where bicyclists reside. This can further assist planners in developing municipal specific bicycle infrastructure strategies. For example those areas where bicyclists live and which are in close proximity to a train station might then be candidates for a bicycle parkiteer (a secure parking station), which supports multi-modal commuter behaviour. More information here.
Pettit, C.J. Lieske, S.N. Leao, S.Z. Big Bicycle Data Processing: From Personal Data to Urban Applications, ISPRS XXIII Congress 2016, Prague, Czech Republic, July 12-19th 2016.
This data was acquired from Bicycle Network as collected through their RiderLog App.