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More Information - See.Sense Data-Insights Dashboard

This is centralised reference for all layer types available in the See.Sense Data-Insights Dashboard.

Note: not all layers and features will be available in all dashboard versions.


Route Popularity


This shows the number of distinct cyclists travelling through each point. Note that we do not snap to roads, so true desire lines are shown.

How you can use this

Popular routes indicate cyclists perceptions of travel time, facility type, and safety.  Use this to examine the ‘desire lines’ where cyclists choose to travel. Consider if cyclists may be avoiding particular areas, or are there roads cyclists may be choosing to avoid rough surfaces or dangerous or congested intersections?

You can also use the AM/PM toggle to see if route popularity changes by morning or evening.



This shows the average speed of cyclists through each point.

How you can use this

Higher average speeds can be indicative of:

  • Downhill riding
  • Places where cyclists feel confident to cycle faster

However, with higher speeds the chance of an accident as well as its severity increases. Design for speeds that are safe for your community and infrastructure.

You can see if cyclists are flowing or if they’re having to start-stop a lot, fluid movement is indicative of good infrastructure.

Road Surface


The technology in See.Sense lights maps road surface roughness from the experience of the cyclist. 

  • Our SSRI score (See.Sense Roughness Index) is calculated from average scores in a tile
  • Darker colored tiles indicate smoother road surfaces and lighter tiles indicate rougher road surface

The SSRI scores has been shown to have a high correlation with a visual inspection. See research here conducted by AECOM for more information.

How you can use this

You can use this to identify areas where to prioritise cycle infrastructure maintenance.  Areas where there are a high volume of cyclists, or are showing areas where cyclists are experiencing difficulties such as heavy braking, swerving, collisions or where there are reports coming through on the perception report data should be prioritised from a risk management approach.

By improving road surface, you can improve cyclists' comfort and perception of safety, as well as help to reduce accidents.

The See.Sense Road Roughness data can also be used to help inform a Level of Service Analysis. See an example here.

Dwell Time


  • The darker the colour, the greater the number of cyclists that have occupied that space while motionless
  • The height corresponds to how long cyclists have waited in that point. The higher the point, the longer the wait

How you can use this

Dwell can time can show you where cyclist flow needs to be improved to make cycling more viable as well as more pleasant.

Higher dwell times can:

  • Make cycling less desirable
  • Add substantial time to a commute
  • Encourage risky behaviour like “beating the signal”
  • Make cyclists feel less safe when motionless and surrounded by vehicles



  • Cyclist data is aggregated into tiles
  • Darker tiles indicate heavier/more severe braking

How you can use this

Heavy braking indicates that cyclists are having to react to something at short notice. Examine the area of the road to determine what could contribute to this. For example, a car door opening along a bike path or pedestrian-cyclists conflict. Do you note any different patterns in braking between genders or age?


  • Cyclist data is aggregated into tiles
  • Darker tiles indicate more severe/sudden swerving

How you can use this

Cyclists can swerve or brake suddenly in response to:

  • Unexpected vehicle movements
  • Unexpected pedestrian movement
  • Traffic lights
  • Poor road surface quality
  • Other cyclists

You can use this information to identify areas of your network that are causing difficulty to cyclists.

Origin - Destination


  • Each journey a cyclist makes has a first and last GPS point (outside of any privacy zone)
  • We aggregate these points in a tile containing many cyclists to protect individual privacy
  • Please note cyclists may also set a privacy zone, which covers a radius up to 300m around their home or work, data will not be collected in this area.  
  • Hover the mouse over a chosen location, eg. train station or workplace. It will highlight the tiles which represent the popular origin-destinations for this location.

How you can use this

Origin-Destination reveals where cyclists are coming from and and where they are going, as well as where they aren’t going. This is important information for the design of an efficient network that can carry cyclists to areas that meet their needs. It can also help to identify demand for bike parking.




The AM/PM filter will restrict the data displayed to only AM hours or PM hours. This is most useful for separating out commuters going to and from work in the city.