The attendance of touristic sites such as natural reserves, historic monuments, resorts is largely
influenced by the weather conditions, the calendar (seasons, public holydays, dates of specials events …)
and some other environmental conditions (tide timetables …).
Predicting the flow of visitors, and especially the peaks, is an important challenge in order to:
Quantify the notoriety and analyze the economic benefits
Find the appropriate measures to reduce the environmental impacts
Dimension the infrastructures (car parks, hiking trails, cycle tracks and other facilities)
Anticipate the needs for the maintenance and the technical teams
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By mixing past observations on the touristic flows with weather, environmental and calendar data, we create models that enable to better understand the behaviors of visitors, to predict their number and in some cases to act on it. This approach has been successfully used on various touristic sites.
The raw data may have very different origins:
Automatic traffic meters, counters on roads or hiking trails ...
Recorded entrances in museums, overnight stays in hotels, bus tickets ...
Local observations by interviewers, technical teams ...
Mobile data, Internet traffic, or any other divice sensors.
In any cases, it is crucial to correlate all this data with real in-situ observation!
This kind of approach enables to get precise estimations not only in time but also in space (it is for example possible
to estimate the flows of visitors in very small areas or complex networks of adjacent tracks).
We provide cloud based solutions for online dashboards to vizualize the forecasts of flows of visitors in space and time updated with the latest weather data.
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