Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.733977
Title: Predicting user numbers of an urban fringe Pennine moorland using time and weather variables
Author: Hoyle, M.
ISNI:       0000 0004 6496 8045
Awarding Body: Liverpool John Moores University
Current Institution: Liverpool John Moores University
Date of Award: 2018
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Abstract:
This study develops and conducts a 15-month, high resolution 24/7 user counting exercise on an area of urban-fringe moorland. The results of this study are discussed and used to predict future land use. The results of this study are compared with results from lower resolution user counts in other wilderness areas. This study was conceived to address a gap in data around recreational moorland use and provide 24/7 data on user numbers in order to develop models to attempt to predict use of urban-fringe moorland from time and weather variables. The data collection strategies utilised were manual counts by an observer, supplemented by Arduino micro-computers and passive infrared sensors. These sensors were designed and developed specifically for the purpose of remote high resolution counting of visitors at low cost, producing reliable 24/7 data for 15-months. Time and synchronous local weather variables at 30 minute, 1 hour, 3 hour and 6 hour resolution were compared with 30 minute moorland user data to assess how these factors affected counts. The study found that the strongest variable affecting visitor counts was daylight. User counts were highest in summer, at weekends and during afternoons. Surprisingly, very little change in user counts was detected during school, bank or religious holidays. Generally, there are trends toward using the moor when temperature is higher and humidity lower. Cloud, visibility, wind chill, wind speed and wind direction had no influence on user counts. User counts, time and weather information were modelled using two approaches: (1) weighting factors and (2) multiple regression. The best model was able to explain 52% of variation in use. The predictive capability of the model increased to 58% during summer and on weekends. Data suggest that there are two groups of users on the moor. A group that have become acclimatised to the prevailing weather conditions and use the area regardless of the weather, this first group will use the moor regularly throughout the week. The second user group is more likely to use the moor during the weekend. These users are more influenced by time and weather factors. An important social discovery was made through anecdotal observation and discussion indicating that the urban fringe moorland is utilised by users beyond the expected dog walkers, hikers and cyclists.
Supervisor: Stott, T. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.733977  DOI:
Keywords: GV Recreation Leisure ; HD Industries. Land use. Labor
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