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A resilient urban system should cope with the dynamic human activities in its subsystems. Since travel allows people to have their needs satisfied in scattered locales, the dynamics of travel and its effects on people's well-being can vary across different spatial scales (including different subsystems) and over time. However, little empirical research has been done regarding these spatiotemporal variations. In this article, we introduced a trip resilience (TR) index to measure the time-varying travel characteristics, especially trip attraction changes, across different spatial scales. Using empirical data from Hong Kong, we quantified the TR indices for metro trips at a station across three spatial scales: local, neighborhood, and citywide. Then, we examined the spatial distribution of the TR and investigated which station (area) characteristics could explain the stations' TR indices for trips in different scales. We found that the TR indices and their predictors varied across the scales. The diversity of points of interest significantly predicted the TR indices across all the scales. Yet, other characteristics, such as the median age of residents, street density, working population, and provisions of parking spaces, only predicted the TR indices for trips at one or two of the scales. These findings shed light on more refined urban and transport planning strategies and policies concerning travel demand management across spatial scales in the post-COVID-19 era. [ABSTRACT FROM AUTHOR]

Abstract Existing studies have yet reached consistent conclusions on accessibility benefits of buses. Most existing studies have been conducted in the context of the West, where bus patronage is generally low. In this study, we used a database of 22,586 secondhand residential properties in 358 residential estates in Xiamen, China to develop four non-spatial hedonic pricing models (one standard and three Box-Cox transformed) and two spatial econometric models to quantify the effects of bus accessibility on property prices and analyze how the introduction of spatial econometric models would influence estimates of such benefits. Our findings are as follows. (1) Access to bus stops is positively correlated with property prices. This outcome is in contrast with findings of mainstream research (or conventional wisdom). For every bus stop within 500 m, the price of a property is 0.5% higher, all else being equal. (2) Bus travel times to essential destinations significantly influence housing prices. (3) Spatial econometric models that account for spatial autocorrelation outperform traditional hedonic pricing models. A few robustness check analyses further guarantee the plausibility of this study. However, the price premiums offered by bus accessibility may be gradually decreased, even eventually discarded, because of declining attractiveness for bus travel and continuous transit service enhancement in the forthcoming years. Highlights • Add an empirical study on pricing bus accessibility in a bus-served city in China • Decompose bus accessibility into local (to-bus) and regional (by-bus) accessibility • Gain a deeper understanding of the benefits arising from local and regional bus accessibility • Offer insights for value capture schemes of financing bus investments [ABSTRACT FROM AUTHOR]

Transit-Oriented Development (TOD) degree, the correlation between transit-based accessibility and urban development, reflects to what extent TOD shapes urban form. This paper empirically examines the shifting patterns of TOD degree and its correlates by using publicly available big and/or open data (BOD) such as point of interest (POI) and OpenStreetMap data for Shenzhen, China, a city experiencing rapid growth/changes in recent decades. The BOD used contain up-to-date information of human activities in finer spatiotemporal resolutions than traditional data. The paper illustrates how BOD can be utilized to quantify TOD degree and its correlates in 2014 and 2017. The main findings are twofold. First, bus stops, a proxy for bus-based accessibility, were found to markedly influence urban development (measued by the number of POIs with social media check-ins) around a (planned) metro station in 2014, when the local metro system was still in devleopment. Second, the impacts of the metro-based accessibility (measured by the average time to the two central business districts) on urban development became larger than those of the accessibility to bus stops as the local metro system matured. It is recommended that decision-makers should systematically consider and harness those effects over time to better promote TOD degree. • It examines transit-based accessibility and urban development in Shenzhen • It uses publicly available big and/or open data • It illustrates new ways to quantify transit-based accessibility and urban development • It finds two effects of the accessibility: Path-dependence and Substitution/Enhancement. [ABSTRACT FROM AUTHOR]

This paper seeks to understand extreme public transit riders in Beijing using both traditional household surveys and emerging new data sources such as Smart Card Data (SCD). We focus on four types of extreme transit behaviors: public transit riders who (1) travel significantly earlier than average riders (‘early birds’); (2) ride in unusual late hours (‘night owls’); (3) commute in excessively long distance (‘tireless itinerants’); and (4) make significantly more trips per day (‘recurring itinerants’). SCD are used to identify the spatiotemporal patterns of these four extreme transit behaviors. In addition, household surveys are employed to supplement the socioeconomic background and tentatively profile extreme travelers. While the research findings are useful to guide urban governance and planning in Beijing, our methodology and procedures can be extended to understand travel patterns elsewhere. [ABSTRACT FROM AUTHOR]