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- Forecasting daily foot traffic in recreational trails using machine learningPublication . Madden, Kyle; Lukoseviciute, Goda; Ramsey, Elaine; Panagopoulos, Thomas; Condell, JoanThis paper discusses weather factors that may affect the level of visitation at recreational walking trails and provides insights into how specific factors (wind, rain etc.) can influence visitation. The quantity of visitors received affects trail management strategies, as there are often damaging effects attributed to the excessive visitation of natural areas. Therefore, accurate forecasting can inform trail management plans. Trail partners have expressed a demand for a system that can deliver qualitative insights to inform trail management while also providing accurate visitor forecasts. This study applied the approach, utilising Machine Learning and historic footfall data from electronic people-counting sensors alongside weather data; our model is a first in the introduction of Tourism Climate Indexes into forecasting models. Factors influencing visitation levels at three walking trails across the Atlantic Area of Europe were discussed. The results highlight that the model predicts trail use with satisfactory accuracy to inform adaptive management frameworks measuring visitor experience indicators. Management implications:center dot Environmental monitoring can gather insights into the situational factors that affect visitation levels on their trails, or if there are other contributing factors aside from weather data that could be investigated.center dot Trail-related recreation operators can formulate and develop strategies and plans to prevent the occurrence of tourist crowding or congestion in periods of high demand and increase trail visitor arrivals in low demand.center dot Trail managers can develop new service that will attract visitors under different weather conditions such as shelters, indoor museums, tents that hosts visitors during rainy or sunny days.center dot Trail managers can prepare for a lower trail visitation demand through marketing and offering alternative recreational activities.
- Recreational trail development within different geographical contexts as a determinant of income multiplier and local economic impactPublication . Lukoseviciute, Goda; Pereira, Luis; Panagopoulos, Thomas; Fedeli, Giancarlo; Ramsey, Elaine; Madden, Kyle; Condell, JoanThe development of recreational trails has gained popularity in recent years and therefore many scholars have studied various aspects of them. However, the recreational trail theoretical framework lacks an understanding of the relationship between the stage of trail development and income multiplier value. This research aims to examine this relationship and thus advance the traditional theory of recreational trail economic impact by providing an explanation of the relationship between the stage of trail development and the income multiplier. This study applied a combined approach of Recreation Opportunity Spectrum (ROS) to assess the stage of trail development and the Ad hoc model to estimate the income multiplier and economic impact. The results of this study reveal that there is a strong correlation between the stage of trail development and income multiplier and provide a novelty in traditional recreational trail management and economic impact theory thus enriching the topical literature.