Prognoser för besökstryck på vandringsleder : En fallstudie av ett naturreservat i Stockholm

In recent times of increasing mental and physical health issues, visitation in areas for nature-based recreation has increased significantly. This increase highlights the need for accurate and proactive planning and maintenance of hiking trails and has led to additional funding by the Swedish government. The emerging field of visitation forecasting on hiking trails can benefit managers and visitors in these areas. This research aims to understand factors affecting demand for nature-based recreation and to explore the use of multiple linear regression in forecasting visitation levels on hiking trails. It also examines the data needed for producing these forecasts and their potential benefits for managers and visitors. This study found that weather factors were the most important factor for visitation on hiking trails, together with calendar-related factors such as seasonality and public holidays. In producing forecasts, historic visitation data is vital, together with data on other factors found to affect visitation. The multiple linear regression analysis produced for the study area explained a large part of the variations in visitation and correctly modelled seasonal and weekly patterns, even if exact numbers were not adequately accurate. Visitation levels forecasts for hiking trails were found to have several benefits for both managers, planners, and visitors of these areas. Future research should explore non-linear models as well as machine-learning approaches for potentially more accurate forecasting. Producing more granular forecasts for different times of the day, as well as the distribution of visitors in an area, should also be considered in future research. Also including variables not included in the analysis of this research could be relevant to better understand hiking trail visitation.