Abstract

Active tourism is an increasingly important motivation for spending free time worldwide and in Hungary as well. One popular form of this is cycling, the popularity of which increased further during the Covid-19 epidemic. Cycling is also one of the key factors of sustainable tourism. Hungarian Public Roads Plc operates measuring instruments at 65 points in the country in order to count automatically the cycling traffic. We received the data of the cycling counters for the period 2019-2023. The dataset contains the daily number of cyclists who passed in front of the measuring device. According to our examination, the raw data can be used to a limited extent, as only a few measuring instruments worked reliably over a longer period of time. Some cycling counters worked continuously, others only failed for a few days, but some cycling counters failed and did not send data for up to 1-2 years. We applied a two step procedure in order to impute the missing data for the measuring device located around the greatest Hungarian lakes: first the missForest algoritm in Phython was used in order to impute the daily traffic, then the aggregated monthly data was analyzed in time series with the monthly indicator of accomodation guest data in the relevant settlements. We found that the imputed data on monthly level is suitable to be published as the bicycle traffic around the greatest Hungarian lake together with the accommodation guest data in a map display.