A MULTIDISCIPLINARY ANALYTICAL FRAMEWORK FOR STUDYING ACTIVE MOBILITY PATTERNS
- 1LlactaLAB CIudades Sustentables. Departamento de Espacio y Población. Universidad de Cuenca, Av. 12 de Abril, Cuenca, Ecuador
- 2Facultad de Ciencias Agropecuarias. Universidad de Cuenca, Av. 12 de Octubre, Cuenca, Ecuador
- 3Escuela de Arquitectura, Universidad del Azuay, Av. 24 de Mayo, Cuenca, Ecuador
Keywords: Active mobility, Movement Analysis, Spatial Behaviour, Sustainable Cities
Abstract. Intermediate cities are urged to change and adapt their mobility systems from a high energy-demanding motorized model to a sustainable low-motorized model. In order to accomplish such a model, city administrations need to better understand active mobility patterns and their links to socio-demographic and cultural aspects of the population. During the last decade, researchers have demonstrated the potential of geo-location technologies and mobile devices to gather massive amounts of data for mobility studies. However, the analysis and interpretation of this data has been carried out by specialized research groups with relatively narrow approaches from different disciplines. Consequently, broader questions remain less explored, mainly those relating to spatial behaviour of individuals and populations with their geographic environment and the motivations and perceptions shaping such behaviour. Understanding sustainable mobility and exploring new research paths require an interdisciplinary approach given the complex nature of mobility systems and their social, economic and environmental impacts. Here, we introduce the elements for a multidisciplinary analytical framework for studying active mobility patterns comprised of three components: a) Methodological, b) Behavioural, and c) Perceptual. We demonstrate the applicability of the framework by analysing mobility patterns of cyclists and pedestrians in an intermediate city integrating a range of techniques, including: GPS tracking, spatial analysis, auto-ethnography, and perceptual mapping. The results demonstrated the existence of non-evident spatial behaviours and how perceptual features affect mobility. This knowledge is useful for developing policies and practices for sustainable mobility planning.