The attendance of tourist sites such as natural reserves, historic monuments, and resorts is significantly influenced
by weather conditions, the calendar (including seasons, public holidays, and special event dates),
and other environmental factors (such as tide timetables).
Accurately predicting the flow of visitors, particularly peak times, poses a significant challenge but is crucial for several reasons:
Quantifying Notoriety and Analyzing Economic Benefits: Understanding visitor trends helps gauge the site's popularity and its economic impact
Reducing Environmental Impacts: Effective visitor management can mitigate adverse effects on the environment
Dimensioning Infrastructure: Planning for adequate facilities such as car parks, hiking trails, cycle tracks, and other amenities is essential.
Anticipating Maintenance and Staffing Needs: Predicting visitor flow aids in scheduling necessary maintenance and ensuring sufficient staffing.
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By integrating past observations of tourist flows with weather, environmental, and calendar data, we develop models that improve our understanding of visitor behaviors and predict their numbers, sometimes even allowing us to influence these patterns. This approach has proven effective across a variety of tourist sites.
The raw data may have very different origins:
Automatic traffic meters and counters on roads or hiking trails...
Recorded entries in museums, overnight stays in hotels, and bus ticket sales...
Local observations by interviewers and technical teams...
Local observations by interviewers and technical teams.
It is crucial to correlate all this data with real in-situ observations to ensure accuracy!
This method allows for precise estimations not only temporally but also spatially. For instance, it is possible to estimate
visitor flows in very small areas or complex networks of adjacent paths.
We offer cloud-based solutions for online dashboards that visualize forecasts of visitor flows
in both space and time, continually updated with the latest weather data.
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