Analyzing visitor flows in natural or touristic areas is key for assessing users’ preferences and behaviour, and for providing relevant input for infrastructure development and visitor management measures. Despite of the growing tendency of electronic device usage, in-person surveying still remains an invaluable approach for getting in-depth information on how visitors use and move along trails, alongside with their motivations, preferences and general mindset. An annual, survey-based visitor monitoring project was launched in 2017 in the UNESCO Pilis Biosphere Reserve in Central Hungary with the above aims, where trip routes are questioned from trail users and recorded via counting sheets. These data are compiled into a unified database, which provides a basis for a visitor flow map and various analyses. This paper aims to present the current state of the modeling and processing framework we have been developing for representing and processing the trip routes recorded in textual form and translated into trail graph routes, alongside with the key challenges and findings we have so far. Beyond its particular local relevance, our approach has revealed significant general route information modeling aspects and considerations that are useful when dealing with the duality of text-based, human-described geographical route representations and their (possible or assumed) exact geo-localized linestring representations.

Social media analysis has become a major instrument for data-driven tourism. It allows surveying visitor behavior on multiple scales. Considering the geographical characteristics of users’ posts from social media platforms, we were able to address more specific questions related to the place type selection patterns of the visitors. In this paper, we present OPENLOSTCAT, our first-order-logic-based location categorizer applicable for modeling location types depending on Open-StreetMap data. We report our findings revealed by this tool on more than one year’s collection of global-scale geotagged Twitter data, focused on potential trail-related hiking and trekking activities. We categorized visited locations in our experiments based on place accessibility – transport and trail infrastructure –, and analyzed these categories according to the travel distance taken by visitors in general to reach these areas. Our comparisons reveal seasonal characteristics, continental differences (between Europe and North America), as well as specifics related to selected recreational areas. Besides these preliminary findings available for further verification, we show both the perspectives and limitations of our approach for future improvements and experiments.

In this paper, we deal with the question of how the variety of trip opportunities can be modeled in – possibly complex – recreational trail networks (such as hiking paths or cycling ways). In order to quantify the variety of possible loop trips starting from specific trailheads (starting nodes accessible from outside the network) and the variety of connecting trips between specific origin-destination pairs, two novel measures of Loop Trip Variety Index (LTVI) and Connecting Trip Variety Index (CTVI) are proposed preliminarily and informally in [12], respectively, in the frame of assessing the impacts of some recent trail network developments. This paper establishes the formal definitions of improved variants of these measures, shows their well-definedness, presents the algorithms of their computation, investigates on their properties and benefits, and gives reasons of how and to what extent they can be treated as models of trip variety. Possible uses, application areas and future improvements are sketched especially for visitor management planning and profile-based trip recommendation systems.

Trail route networks provide an infrastructure for touristic and recreational walking activities worldwide. They can have a variety of layouts, signage systems, development and management patterns, involving multiple stakeholders and contributors, and tend to be determined by various interests on different levels and dynamically changing circumstances. This paper aims to develop the skeleton of TRAILSIGNER, a sound geospatial conceptual data model suite of trail networks, waymarked routes and their signage systems and assets, which can be used as a basis for creating an information system for the effective, organic and consistent planning, management, maintenance and presentation of trails and their signage. This reduces potential confusion, mistrust and danger for visitors caused by information mismatches including incomplete, incoherent or inconsistent route signposting. To ensure consistency of incrementally planned signposts with each other and with the (possibly changing) underlying trail network, a systematic, set-based approach is developed using generative logical rules and incorporated into the conceptual model suite as signpost logics. The paper also defines a reference ruleset for it. This approach may further be generalized, personalized and adapted to other fields or applications having similar requirements or phenomena.