There is growing evidence that active mobility can have a range of positive outcomes for the wider community. Active mobility, or non-motorised modes of transport, refers to any kind of transport other than motor vehicles. The most common modes of active transport are walking and cycling. The increased amount of walking and cycling in cities benefits health through increased physical activity. The years 2020–2021 were disruptive due to the COVID-19 pandemic, and during these challenging times, active mobility became more important than ever before. Due to this, understanding the impact of built environment (BE) characteristics on active travel (walking and cycling) in cities has become increasingly important. In recent years, the proliferation of data, visualizations, dashboards, and interactive mapping and GIS technologies has created new opportunities for data modelling, data-driven approaches, and analytics, especially in the field of active mobility. While significant developments have been achieved in the field of modelling active mobility in cities, the recent COVID-19 crisis amplified the increasing need for more research in this area. This Special Issue includes papers focusing on new datasets, innovative techniques and analytical tools, new areas of applications, and emerging ways to encourage public and stakeholder participation in active mobility. Special attention was paid to the mobility challenges caused by COVID-19.
In this regard, Ref. [1] study offers new techniques and datasets for analysing micro-mobility that account for COVID-19 avoidance. This study contributes to our knowledge of micro-mobility and policy guidelines in the post-pandemic era. Ref. [2] studied patterns of active mobility in schools in New Zealand and provide us with important insights about the spatial patterns and characteristics of active mobility, and reasons for actively travelling to school or travelling by vehicle. Ref. [3] develop an innovative digital bicycle planning tool that is informed through citizens’ feedback. Such planning support system tools can be used by cities when engaging in cycle prioritisation initiatives. This work complements other attempts made here to better understand mobility patterns. Ref. [4] analysed whether it would be possible to make the 30-min city a “reality” across Australia; their study found that if commuters switch to a more active mode of transport (e.g., cycling), an estimated 29.5% of workers will be able to reach their current workplace within 30 min. In a similar vein, Ref. [5] focus on improving accessibility to medical facilities using an interesting case study in Wuhan, China during the COVID-19 pandemic. To complement this, Ref. [6] offer the use of GWR (geographically weighted regression) methods to better understand the effects of natural environmental and socioeconomic factors on spreading diseases in China on a seasonal and spatial level. In summary, this Special Issue is dedicated to exploring current trends concerning the technological, methodological, conceptual, and social dimensions of active mobility in the post-COVID-19 era. We hope the work presented here will inspire our readers and scholars to conduct further research in this area and increase our knowledge of geo-information applications in active mobility and health in cities.
Author Contributions
Ori Gudes and Simone Zarpelon Leao have prepared to this editorial and approved it. All authors have read and agreed to the published version of the manuscript.
Conflicts of Interest
The authors declare no conflict of interest.
References
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