As more cities adopt bike share systems, questions regarding equity, accessibility, expansion, and bikability arise. Baltimore City implemented bike share in 2016 with plans to expand it up to 57 stations. This paper introduces a new methodology for an equity-based planning analysis which help minimize segregation and marginalization in planning practices. The proposed geographic methodology incorporates a modified population density-based bike equity index and develops a level of traffic stress index to prioritize bikeshare infrastructure. This study provides a parallel prioritization scheme for implementing bikeshare and supporting cycling infrastructure.

Background: Vulnerable communities are susceptible to and disproportionately affected by the impacts of the COVID-19 pandemic. Understanding the challenges faced, perceptions, lessons learned, and recommendations of the organizations that provide services in response to COVID-19 to vulnerable communities is critical to improving emergency response and preparedness in these communities. Methods: This study employed GIS mapping to identify the needs and assets that exist in communities in Baltimore City, where vulnerabilities related to social determinants of health and the burden of the COVID-19 pandemic were greatest. We also conducted an online survey between September 1, 2021, and May 30, 2022, to assess the COVID-19-related services provided by local organizations, challenges faced, perceptions, lessons learned, and recommendations to inform policies, programs, and funding related to improving the COVID-19 response in underserved communities. The survey was disseminated through the online Kobo Toolbox platform to leaders and representatives of organizations in Baltimore City. Results: Based on GIS mapping analysis, we identified three communities as the most vulnerable and 522 organizations involved in the COVID-19 response across Baltimore City. 247 surveys were disseminated, and 50 survey responses were received (20.24% response rate). Out of these organizations, nearly 80% provided services in response to COVID-19 to the identified vulnerable communities. Challenges experienced ranged from funding (29%), and outreach/recruitment (26%), to not having access to updated and accurate information from local officials (32%). Conclusions: This research highlights critical insights gained related to the experiences of vulnerable populations and suggests ways forward to address challenges faced during the emergency response by providing recommendations for policy and program changes. Furthermore, the findings will help better prepare vulnerable communities for public health emergencies and build more community resilience.

A food desert is a geographic area lacking spatial and socioeconomic access to healthy foods. Disparities in food access and availability hinder public health and individual wellbeing. Access to healthy food has been evaluated by many agencies and researches yet they do not comparably demarcate food deserts or identify vulnerable populations in methodical terms. Existing literature suggests a link between food deserts, income level, and vehicle ownership. This study evaluates the existing methods and proposes a novel data-driven method to identify food deserts in Baltimore, Maryland. This study evaluates responses from 573 respondents for an in-depth analysis of individual grocery store choice and travel decisions. Chi-square automatic interaction detector (CHAID) decision trees are used to develop a user-generated food desert metric. Income level is found to be a key indicator for food desert demarcation, more than vehicle ownership. Network distance was applied to develop the prioritization matrix for a food desert. This research provides a replicable method for determining food-insecure areas in a locality by aggregating individual data to identify such areas. Such a metric can aid policymakers to make investment decisions and to direct resources to areas of need.

Research has indicated that Thailand's future economic growth and industrial expansion will be relocated to peri-urban locations and secondary cities throughout the kingdom. As industrial activities extend into and transform rural areas, incompatible land use patterns emerge and produce pressures on environmental resources. This research investigates the dynamic of peri-urban growth in Sung Noen District, Nakhon Ratchasima Province, Thailand. The study area represents a new-growth secondary city with one of the largest metropolitan populations for a city disconnected from Bangkok's extended metropolitan region. Our study aims to provide a systematic analysis of peri-urban change in this area. We use a hybrid classification scheme to examine multitemporal Landsat TM and Landsat ETMC data, coupled with geographic information systems analyses to help assess the loss of peri-urban land between 1990 and 2014. The result can serve as a guide to answer future research questions relating to sustainability and environmentalism within urbanization and national development.