Choose a tutorial for a short demonstration of the website. The videos demonstrate the main controls of each page, show how to explore mobility patterns and interpret differences between sensor data.
The About the Project page introduces the three datasets used in the dashboard.
Learn how to choose mobility layers, define a time period and select a feature to update the statistics and charts.
Use the split-map view to compare mobility during two selected periods and identify changes at the same road segment or sensor location.
Compare EnCLOD and Telraam counts at shared locations and learn how to interpret their agreement and differences.
Explore the main statistical findings on how weather conditions, academic terms and unusual daily events influenced mobility patterns across the Envelopa Campus.
Mobility refers to recorded movement through or around the study area. Its precise meaning depends on the selected dataset.
A mobility count represents a detected passage or recorded trip, not necessarily a unique person or vehicle. The same person or vehicle may therefore be counted more than once if they make several journeys or pass multiple monitoring locations.
Aggregation controls how individual observations are grouped. The available options include day, week, month, weekday within a month and academic term.
Longer aggregation periods combine more observations and show broader mobility patterns, while shorter periods make day-to-day changes easier to identify.
Uncertainty means that the displayed values are estimates of mobility rather than perfectly complete measurements of every journey.
Sensor results can be affected by the technology used, sensor position, observation area, visibility, classification methods, missing observations and data processing. EnCLOD and Telraam may therefore produce different counts even when they monitor corresponding road sections.
Nextbike data contain recorded trip origins and destinations which were used to model likely routes between the two endpoints. The actual route taken by a cyclist may differ from the modelled likely routes displayed on the map.
These uncertainties do not make the data unusable. The dashboard is intended to identify general patterns, differences and changes over time rather than provide exact counts of unique travellers.
EnCLOD, Telraam and Nextbike have different periods of data coverage:
Check that you have selected an aggregation level and an available time period. You can hover over the i buttons beside the controls to check data availability.
The datasets cover different dates, so some selected periods may contain data for only one or two datasets. A dataset with no observations for the selected period will not be displayed on the map.
The time-period controls combine the periods available across all mapped datasets. A period may therefore remain selectable because EnCLOD or Telraam contains observations, even when Nextbike does not.
Only the datasets containing observations for the selected period should be displayed on the map.
On the About the Project map, you can select sensor and station locations to learn more about how each dataset was collected.
On the Dashboard and Time Comparison maps, you can select an EnCLOD road segment, a Telraam sensor point or a Nextbike assumed route. A popup will show mobility information for the selected feature. The summary panels and available charts will also update where relevant.
On the Sensor Comparison map, you can select one of the matched road segments where EnCLOD and Telraam observations are compared. A popup will show the counts from both systems and the difference between them.
On all maps, you can hover over buildings to view their names, but the buildings have no further interactivity.
The datasets measure different aspects of mobility using different methods.
The datasets also represent mobility in different ways: EnCLOD observations are displayed on road segments, Telraam observations at sensor locations, and Nextbike trips along modelled likely routes.
Their values should therefore be interpreted as complementary views of mobility rather than directly interchangeable totals.
No - the datasets provide complementary views of mobility, but their totals are not directly interchangeable because they measure different transport modes and use different collection methods.
For comparisons over time, this should be made with the same dataset, location and transport category. The Sensor Comparison page is a separate analysis designed specifically to examine differences between matched EnCLOD and Telraam observations.
The original Nextbike dataset contained recorded trip origins and destinations, but did not contain complete GPS tracks showing the exact route taken.
The displayed lines are modelled likely routes between the recorded trip endpoints using a cycling index from NetAScore and a least-cost path algorithm. They routes therefore be interpreted as assumed routes rather than actual cyclist trajectories.
EnCLOD and Telraam can only be compared where the two systems monitored corresponding road sections.
The comparison therefore includes the matched locations at 17. Listopadu South and Šmeralova South. Only the matched road-segment lines are displayed to avoid repeating the same comparison as both a Telraam point and an EnCLOD line.
There are many factors that can contribute to differences in counts between the two systems.
The two systems use different sensor technologies, positions, observation areas, classification rules and processing methods.
Telraam also does not classify nighttime observations by transport mode, while some EnCLOD hourly records contain fewer than four complete 15-minute observations. Differences between the datasets do not necessarily mean that either sensor is incorrect.
Within the Sensor Comparison section, a period is classified as having extreme disagreement when the absolute symmetric percentage difference between the Telraam and EnCLOD counts is 30% or higher. Symmetric percentage difference treats the two datasets equally and does not assume that either system provides the correct reference value.