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Analysing hiker movement patterns using GPS data: Implications for park management

机译:使用GPS数据分析远足者的运动模式:对公园管理的意义

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In natural areas, park management organisations need to cater for economic, environmental, recreation and social demands and values. However, multifunctional land use also creates conflicts. Increased numbers of people using an area could exceed its ecological carrying capacity. The recreational quality of areas could be negatively impacted by conflicts in recreational behaviour. Therefore, park managers require spatio-temporal data on visitor flows, but there appears to be a shortage of suitable visitor data. If there are data available, these often do not deliver the information required by managers and there is little guidance on appropriate monitoring variables. This paper therefore combines user movement analysis with environmental and ecological factors for natural resource management. Through a case study we describe the entire working process from field data acquisition to usable park management information. GPS and itinerary data from 138 visitors to the Drents-Friese Wold National Park (the Netherlands) were collected to estimate visitor densities and distribution patterns within the park. Data acquisition is efficient in the working process, but careful error handling is a time consuming but necessary part of it. We introduce the definition of 'hard' and 'soft' errors to make spatial analysis more flexible. We show that walking speed, trip time and spatial distributions varied between park visitor groups. Classification and Regression Tree (CART) analysis showed that factors such as the presence of marked trails, distance to facilities but not land use (such as forest or arable land) explained visitor distributions. Patterns differ between respondent groups based on group size and composition, which is also true for itinerary variables such as walking speed and trip time. The combination of high resolution location data with itinerary information from respondents provides a good impression of the different walking preferences of different respondent groups. We conclude therefore that combining GPS data with itinerary information is a useful tool in profiling different natural park visitors. This is useful information for park managers in steering tourists and in catering for different visitor demands in natural parks.
机译:在自然地区,公园管理组织需要迎合经济,环境,娱乐和社会需求与价值。但是,多功能土地利用也会产生冲突。使用该地区的人数增加可能超过其生态承载力。娱乐行为冲突可能会对地区的娱乐质量产生负面影响。因此,公园管理者需要有关访客流量的时空数据,但是似乎缺少合适的访客数据。如果有可用数据,则这些数据通常无法提供管理人员所需的信息,并且关于适当的监视变量的指导也很少。因此,本文将用户移动分析与环境和生态因素相结合,以进行自然资源管理。通过案例研究,我们描述了从现场数据采集到可用的公园管理信息的整个工作过程。收集了来自Drents-Friese Wold国家公园(荷兰)的138位游客的GPS和路线数据,以估算游客在公园内的密度和分布方式。数据采集​​在工作过程中是有效的,但是仔细的错误处理是耗时但必不可少的部分。我们介绍“硬”和“软”错误的定义,以使空间分析更加灵活。我们显示,公园游客群体之间的步行速度,出行时间和空间分布各不相同。分类和回归树(CART)分析表明,诸如标记痕迹的存在,距设施的距离,而不是土地利用(例如森林或耕地)之类的因素解释了游客的分布。受访者群体之间的模式因群体大小和组成而异,对于诸如步行速度和行程时间之类的行程变量也是如此。高分辨率位置数据与受访者的行程信息相结合,对不同受访者群体的不同步行偏好产生了良好的印象。因此,我们得出的结论是,将GPS数据与行程信息相结合是在描述不同的自然公园游客时的有用工具。这对于公园管理员在引导游客和满足自然公园中不同游客需求方面是有用的信息。

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