GPS as a Method for Assessing Spatial and Temporal Use Distributions of Nature-Based Tourists

Abstract

The locations people visit, their travel routes, and the amount of time spent at these locations are some of the most basic, but relevant, data on recreation. Specifically, spatial and temporal distributions of use influence the extent of recreationrelated resource impacts (Hammitt and Cole 1998). Also, use distributions affect experiential aspects of nature-based recreation, such as facility capacities, perceptions of crowding, and conflict among users (Manning 2011).Collection of spatial and temporal data describing naturebased recreational use patterns has traditionally involved asking visitors to record their own travel routes and times on paper map diaries or questionnaires (Gimblett et al. 2003;Hallo et al. 2005;Potter and Manning 1984;Shechter and Lucas 1978). These methods of collecting data on recreation use patterns are subject to much error and imprecision. For example, the ability of visitors to specify their location on a map (as used in studies employing map diaries) or to know the name of a specific location (as used in a questionnaire) is highly variable. This can lead to a misrepresentation of the places that were visited (Stedman et al. 2004;Stopher and Greaves 2007). Also, when recording times of stay on a map or questionnaire, the precision of responses may be influenced by the rounding of time units used to indicate a length of stay (Stopher and Greaves 2007).Traditional methods of collecting spatial and temporal use data are also burdensome to both survey respondents and researchers. These methods require respondents to track their travel routes on blank maps and record the time spent at locations. Studies involving larger nature-based tourist destinations such as parks, complex trail systems, or unmarked sites and trails make it too time-consuming or unfeasible for visitors to record the entirety of their travels. Also, respondents must be attentive to the research instruments instead of focusing on their recreational experience. Additionally, researchers must devote both time and resources to interpreting, categorizing, and transferring the data from paper maps or questionnaires to a computer for analysis.More recently, geospatial technologies have been used to collect and visually represent spatial recreational use 431325J TRXXX10.

Seasonal Spatial Activity Patterns of Visitors with a Mobile Exercise Application at Seoraksan National Park, South Korea

“…Such in-depth monitoring and predictive analytics are only possible via the use of ordinary visitors' real-time activity data. For instance, accumulated visitors' movement data can provide an important 'early warning' indicator of crowding and other issues experienced during a certain time and place [19]. The Korean National Park Service defines risky points as being related to falling-rocks, risk of structure collapse, or lightning.…”

Tourist mobility at coastal mass destinations: implications for sustainability

“…The time at the sites/activities is more important than the space. However, in studies applied to natural spaces the enjoyment of the space is more important than saving time to concentrate it on the sites or points of interest (Hallo et al [10]). This behaviour presents clear analogies with beach destinations, where the tourist is not so conditioned by visits to a certain number of tourist attractions.…”

“…The majority of the studies are centred on urban environments (Edwards and Griffin [6], Grinberger et al [7], Lau and McKercher [8], Shoval and Isaacson [5]) and, to a lesser extent, on natural destinations (Donaire et al [9], Hallo et al [10]), fewer studies having been conducted in coastal environments, usually associated with sun and sand tourism. Obviously, these destinations do not pose the same problems with regard to mobility as the large urban agglomerations, whilst at the same time the behaviour of the demand tends to be more passive in comparison with urban destinations.…”

The effect of heads-up-display (HUD) goggles on skiing and snowboarding speeds

“…The benefit of using of GPS and GIS techniques is the extremely high resolution of data (Taczanowska et al, 2008), providing much more precise, accurate and reliable information on visitor behaviour (Hallo et al, 2012;D'Antonio et al, 2010) than the coarse spatial scale of data generated by surveys, interviews and counters (Wolf, Stricker, & Hagenloh, 2012 Injuries in alpine skiing are associated with a number of factors including excessive speed (Shealy & Thomas, 1996;Zuckerman, 2007; see section 2.4 for further details). Common management techniques to control skier speed include ski area codes of conduct, speed warning signs e.g.…”