Search

The general transit feed specification is becoming a popular data format for the publication of public transport schedules, making possible the collection of a nation-wide public transport schedule dataset, which enables monitoring of transit supply at an up-to-date and more precise level across a country than previously possible. In this paper, we use general transit feed specification data to measure local-scale public transport availability across England based on service frequency and spatial proximity to public transport stops/stations. Moreover, to demonstrate the usefulness of public transport availability measures, we examine inequalities of public transport provision and identify areas at risk of transport poverty across England. Furthermore, we estimate population (number of households) who are likely to suffer from transport poverty, accounting for public transport availability, time-based job accessibility by public transport or walking, household income and car ownership levels. Based on the criteria, we have used to identify public transport risk, we find that investment in the development of public transport services should prioritise West Midlands, East of England, South East and South West as those regions have more households who are likely to suffer from transport poverty. This paper contributes by (1) defining more comprehensive transit availability measures than existing measures at a variety of geography levels and (2) integrating fours aspects (i.e. public transport availability, job accessibility by public transport or walking, household income and car availability) to analyse transport poverty comprehensively.

Improvement on assessment of air pollution exposure will enhance assessment of health risk-benefit when active travel (cycling and walking). Earlier studies assessed air pollution exposure according to travel time and city-level air pollution. The lack of spatially fine-grained travel data is a barrier to an accurate assessment of air pollution exposure. Due to a high-level spatial granularity, Strava Metro provides an opportunity to assessing air pollution exposure in combination with spatially varying air pollution concentrations. Strava Metro anonymized and aggregated a large volume of users’ traces to streets for each city. In this study, to explore the potential of crowdsourced geographic information in research of active travel and health, we used Strava Metro data and GIS technologies to assess air pollution exposure in Glasgow, UK. Particularly, we incorporated time of the trip to assess average inhaled dose of pollutant during a single cycling or pedestrian trip. Empirical results demonstrate that Strava Metro data provides an opportunity to an assessment of average air pollution exposure during active travel. Additionally, to demonstrate the potential of Strava Metro data in policy-making, we explored the spatial association of air pollution concentration and active travel. As a result, we identified areas that require investment priority, and finally offered implications for policies.

Shifts in phenology are important traces of climate change affecting mountainous ecosystems. We present an analysis of changes in spring phenology using a suite of Earth observation based parameters, that is, start of season (SOS), snow cover extent and meteorological variables from 1991 up to 2012/2014 for the European Alps. Our results show that SOS tends to occur earlier throughout the Alps during this period and spring temperatures have increased in the Eastern Alps. Spring temperatures presented a predominant influence on SOS for both, grasslands and forests across elevations between 500 and 2,200 m asl, while this effect is particularly pronounced in the northeastern Alps. Snow cover duration and snow cover melting days showed secondary impact on SOS. Our research provides a comprehensive observation of spatiotemporal changes in alpine spring vegetation phenology and its driving factors. They improve our understanding of the sensitivity of the European Alps ecosystems to a changing climate. Spring phenology (start of season, SOS) advanced approximately two weeks across the European Alps, with annual trends depending on elevationRegional shifts in SOS coincide with simultaneous variation in spring temperature and snow cover seasonalityThe sensitivity of SOS to variation in spring temperature is especially pronounced in the northeastern Alps Spring phenology (start of season, SOS) advanced approximately two weeks across the European Alps, with annual trends depending on elevation Regional shifts in SOS coincide with simultaneous variation in spring temperature and snow cover seasonality The sensitivity of SOS to variation in spring temperature is especially pronounced in the northeastern Alps