Background information for Q2: Enter your cycling data

Data on cycling come in different formats, and can be of varying quality. A few considerations will help you to make best use of your data, and avoid mistakes.

Use of short-term counts and surveys

The main concern with short-term counts is that they do not accurately capture variations in cycling over time (i.e. time of the day, day of the week, season, as well as weather). If you count on a sunny day, you may see larger numbers than on a rainy day. Since HEAT assumes that the entered data reflect long-term average levels of cycling, data from short-term counts will distort the results.

This issue will mainly affect single facility evaluations (e.g. a footpath, or a bridge) where counts are conducted on the facility itself, or community-wide evaluations that are based on surveys conducted only during a certain time of the year.

Not affected by this issue are assessments based on large surveys, which are conducted on a rolling basis (e.g. national household surveys), or automated continuous counts.

Short term counts may also be adjusted for temporal variation, to better reflect long term levels of cycling. An example for how this can be done is provided by the US National Bicycle and Pedestrian Documentation Project

Use of data from few locations

Spatial variation in cycling may affect evaluations that are based on counts at a single or few locations. The choice of location may strongly influence the count numbers, which may not be representative of the wider level of cycling. Results need to be interpreted carefully, and should in general not be extrapolated beyond the locations where actual data were collected. Not affected by this issue are evaluations based on surveys that sample subjects randomly from a defined area (e.g. large household surveys), and to a lesser extent count-based evaluations on linear facilities, such as trails.

Use of trip or count data

In HEAT, trip or count data needs to be combined with an estimate for average trip length, to calculate the volume of cycling. An example is counts conducted on a bridge, where it remains unknown how far people bike beyond the bridge. Average trip distance estimates may be derived from user surveys on a specific facility, or from travel surveys.