Although the built environment and certain psychosocial factors are related to adolescents’ active commuting to and from school (ACS), their interrelationships have not been explored in depth. This study describes these interrelationships and behavioral profiles via a self-organizing map (SOM) analysis. The sample comprised 465 adolescents from the IPEN (International Physical Activity and the Environment Network) Adolescent study in Valencia, Spain. ACS, barriers to ACS, physical self-efficacy, social support and sociodemographics were measured by questionnaire. Street-network distance to school, net residential density and street intersection density were calculated from the Geographic Information System. The clustering of the SOM outcomes resulted in eight areas or clusters. The clusters which correspond to the lowest and highest ACS levels were then explored in depth. The lowest ACS levels presented interactions between the less supportive built environments (i.e., low levels of residential density and street connectivity in the neighborhood and greater distances to school) and unfavorable psychosocial variables (i.e., low values of physical self-efficacy and medium social support for ACS) and good access to private motorized transport at home. The adolescents with the lowest ACS values exhibited high ACS environment/safety and planning/psychosocial barrier values. Future interventions should be designed to encourage ACS and change multiple levels of influence, such as individual, psychosocial and environmental factors.

Mountain protected areas play a fundamental role in the conservation of natural environment and at the same time provide the population with social benefits such as offering space for leisure and recreation. Understanding motivations and behavior of protected area visitors is crucial to effectively manage vulnerable areas. Our objective was to identify the profiles of visitors to a heavily used tourist destination—Kasprowy Wierch within the Tatra National Park (Poland), using the self-organizing maps (SOM) analytical method. In order to explore the socio-demographic and behavioral characteristics of the visitors a total sample of 2488 respondents were interviewed on site. Self-organizing map analysis is based on cerebral processes for managing and storing information in order to classify subjects and/or find relationships among variables. As a result, four heterogeneous tourist profiles were identified. Interestingly, two of these groups (Cluster 1 and Cluster 3), which were found to be the most challenging groups for management purposes, visited the national park for reasons other than its natural attractions. Especially, one sub-segment of Cluster 3 was mainly motivated by the possibility to use a cable car, admiring views and stayed within close proximity of the upper cable car station. Less than a half of visitors to Kasprowy Wierch (42%) were seeking a nature experience during their trip (Cluster 2 and Cluster 4). The results bring a new point of view in the discussion on visitor management within Kasprowy Wierch region, in particular by overlapping presented visitor segmentation with trip types and/or purchased cable car tickets. Within international context, we highlight the SOM technique as a valuable tool in profiling of tourists and underline the problem of the existence of mass tourism destinations within protected areas.

The emergence of COVID-19 caused a new public health crisis, leading to major changes in daily life routines, often including physical activity (PA) levels. The main goal of this study was to analy...

Mountain protected areas (PAs) aim to preserve vulnerable environments and at the same time encourage numerous outdoor leisure activities. Understanding the way people use natural environments is crucial to balance the needs of visitors and site capacities. This study aims to develop an approach to evaluate the structure and use of designated skiing zones in PAs combining Global Positioning System (GPS) tracking and analytical methods based on graph theory. The study is based on empirical data (n = 609 GPS tracks of backcountry skiers) collected in Tatra National Park (TNP), Poland. The physical structure of the entire skiing zones system has been simplified into a graph structure (structural network; undirected graph). In a second step, the actual use of the area by skiers (functional network; directed graph) was analyzed using a graph-theoretic approach. Network coherence (connectivity indices: β, γ, α), movement directions at path segments, and relative importance of network nodes (node centrality measures: degree, betweenness, closeness, and proximity prestige) were calculated. The system of designated backcountry skiing zones was not evenly used by the visitors. Therefore, the calculated parameters differ significantly between the structural and the functional network. In particular, measures related to the actually used trails are of high importance from the management point of view. Information about the most important node locations can be used for planning sign-posts, on-site maps, interpretative boards, or other tourist infrastructure.