Abstract Cities worldwide have initiated the installation of urban climate sensors to monitor air quality in real time and take proactive measures against the growing threat of climate change. This study focuses on the city of Chicago and utilizes Microsoft’s recently launched Project Eclipse sensors to evaluate air quality status.… read more
Combatting the mismatch: Modeling bike-sharing rental and return machine learning classification forecast in Seoul, South Korea
Abstract: Bike-sharing is rapidly gaining popularity due to health, transportation, and recreational benefits. As more people use bike-sharing, the burden of reallocating bikes will increase because of the mismatch between outgoing and incoming bikes. Optimizing truck routes, incentivizing users, and crowdsourcing are common suggestions to mitigate rebalancing issues. This research… read more
Impacts of COVID-19 on bike-sharing usages in Seoul, South Korea
Abstract: The COVID-19 pandemic and social distancing restrictions have had a significant impact on urban mobility. As micro mobility offers less contact with other people, docked or dockless e-scooters and bike-sharing have emerged as alternative urban mobility solutions. However, little empirical research has been conducted to investigate how COVID-19 might… read more
Understanding E-Scooter Incidents Patterns in Street Network Perspective: A Case Study of Travis County, Texas
Abstract: Dockless electric scooter (E-scooters) services have emerged in the United States as an alternative form of micro transit in the past few years. With the increasing popularity of E-scooters, it is important for cities to manage their usage to create and maintain safe urban environments. However, E-scooter safety in… read more
Tracking Property Ownership Variance and Forecasting Housing Price with Machine Learning and Deep Learning
Abstract— Big data and its production, management, and utilization are essential components in smart city planning. This paper presents a research framework for applying machine learning and deep learning using multiple big data sets on real estate. We built ensemble machine learning models to track property ownership variance in Austin,… read more
Identifying spatiotemporal transit deserts in Seoul, South Korea
Abstract: Transit deserts can result from the inequitable distribution of resources and services, and people living in transit deserts have limited access to transportation system. The aim of this study was to perform spatiotemporal data analysis to identify transit desert areas in Seoul in three steps. First, the transit gap… read more
Exploring Spatial Heterogeneity of E-scooter’s Relationship with Ridesourcing using Explainable Machine Learning
Abstract The expansion of e-scooter sharing system has led to several novel interactions within the existing transportation system. Although there is a potential for e-scooter sharing and ridesourcing to both compete and complement each other, few studies shed light on the relationship between e-scooter sharing and ridesourcing. To fill this… read more
How the single-family residence housing market capitalizes green property upgraded features: evidence from city of Austin
Abstract Purpose – By comparing regression models, this study aims to analyze the added home value of green sustainability features and green efficiency characteristics, rather than green certifications, in the city of Austin. Design/methodology/approach – The adoption of home green energy efficiency upgrades has emerged as a new trend in… read more
What Are the Relationships between Public Transit and Gentrification Progress? An Empirical Study in the New York–Northern New Jersey–Long Island Areas
Abstract: Transit-oriented development has been a widely accepted tool among transportation planning practitioners; however, there are concerns about the risk of increasing residential property values leading to gentrification or displacements. Therefore, it is critical to provide precise investigations of the relationships between public transit and gentrification. Although numerous studies have… read more
The relationship between E-scooter travels and daily leisure activities in Austin, Texas
Abstract: Shared micromobility programs, including dockless electric scooter-share (E-scooter), are popular in many U.S. cities, and with their adoption brings the hope that they may uphold better car-free accessibility. However, few studies provide clear answers to what activities drive its travel demand or whether it could actually generate more visiting… read more