Smart City (SC) strategies developed by local governments reflect how governments and planners envision SC and apply smart technologies, and what challenges they face and try to address. Little attention, however, has been given to investigating SC strategies or applications, especially in the U.S. context. Moreover, there is insufficient attention paid to whether SC strategies address social issues such as equity and public participatory opportunities. Based on the documentation from the U.S. Department of Transportation 2015 Smart City Challenge, we developed a framework to evaluate SC strategies on urban transportation systems using six standards: Safety, Mobility, Sustainability, Opportunity, Efficiency, and Equity. In addition, we synthesized the challenges U.S. smart cities encounter, and SC strategies proposed by local municipal governments to tackle them. Our findings show that most SC strategies aimed to improve Efficiency (78%) and Mobility (57%), while less attention has been given to providing Equity (8%) or Opportunity (7%). The most well-acknowledged challenge that the local governments face is the limited data and tools for decision-making, with 416 SC strategies (27%) proposed to address related issues. Our framework and results contribute to the future SC strategy evaluation and inclusive smart city development. Our study also identified a broad spectrum of available SC strategies planners and policymakers can refer to when designing an SC or overcoming SC challenges.

During the COVID-19 pandemic, social media become an important hub for public discussions on vaccination. However, it is unclear how the rise of cyber space (i.e., social media) combined with traditional relational spaces (i.e., social circles), and physical space (i.e., spatial proximity) together affect the diffusion of vaccination opinions and produce different impacts on urban and rural population's vaccination uptake. This research builds an agent-based model utilizing the Mesa framework to simulate individuals' opinion dynamics towards COVID-19 vaccines, their vaccination uptake and the emergent vaccination rates at a macro level for New York State (NYS). By using a spatially explicit synthetic population, our model can accurately simulate the vaccination rates for NYS (mean absolute error=6.93) and for the majority of counties within it (81%). This research contributes to the modeling literature by simulating individuals vaccination behaviors which are important for disease spread and transmission studies. Our study extends geo-simulations into hybrid-space settings (i.e., physical, relational, and cyber spaces).

At the height of the 2022 Christmas travel season, Buffalo, New York, encountered a once-in-a-generation blizzard that dropped more than fifty inches of snow and formed snowdrifts up to fifteen fee...