A method to analyze variability and seasonality the visitors in mountain national park in period 2017–2020 (Stołowe Mts. National Park; Poland)

Abstract

Variance and seasonality are the key issues in the analysis of visitor traffic in mountain national parks. A high density of visitors at a given site and permanent increase in the number of visitors exceed the Tourism Carrying Capacity (TCC) of trails and produce the associated issue of overtourism. In order to pursue research in this area of study and find ways to counteract overtourism, visitor traffic in national parks should be monitored. The aim of this study was to determine the distribution of visitors and to measure the degree of seasonality of visitor flow in one of the most visited national park in Poland, named Stołowe Mountains National Park (SMNP). The analysis in the study includes variability of daily visitor flow over a 4-year study period based on a determination of tourist seasons and sub-seasons. In order to accomplish this goal two indices were determined: Visitor Index (VI), Seasonality Index (SI). The relevant data were collected daily over a 4-year time period (2017–2019; 1095 daily visitors) and preprocessed data during Covid-19 period in 2020, from a system of 39 pyroelectric sensors part of a Monitoring System of tourist traffic (MSTT). The research found four types of tourist seasons were identified in the study: high season in summer, mid-season in autumn, mid-season in spring, low season in late autumn and winter. The presented Seasonality Index of periods and sub-periods shows some variability in the intensity of weekend tourism. The interpretation of indices allowed to create a detailed description of visitor flow in SMNP. This made it possible to determine the variability of visitor flow on an annual or monthly basis, and to identify seasons and sub-seasons based on available daily data. The Covid-19 pandemic has substantially changed the temporal distribution of tourism visitor flow. New indices: Visitor Index (VI) and a Seasonality Index (SI). The greatest advantage of the proposed indices make it possible to define tourist season periods regardless of the division into months and/or weeks. Presented seasons and sub-seasons last regardless of the monthly and weekly division, and taking into account the daily resolution data, these seasons can be precisely defined. The proposed Visitor Index (VI) and a Seasonality Index (SI) indices provide more detailed insight and serve as accurate measures of tourist season periods The current literature is lacking such approach, where monthly values are usually presented. Paper presented in the analysis utilizing high resolution data, i.e. daily data of visitors. The period of analysis consists of three consecutive years, which gives an uninterrupted period of 1095 days covered with my analysis The Covid-19 pandemic has substantially changed the temporal distribution of visitor flow. Recent changes in visitors are shown by preprocessed data gathered in 2020, which do not confirm the data from 2017 to 2019.