The COVID-19 pandemic has caused incredible impacts on people’s travel behavior. Recent studies suggest that while the demand for public transport has decreased due to passengers’ inability to maintain physical distance inside this mode, the demand for private automobile and active transport modes (walking and cycling) has increased during the pandemic. Policymakers should take this opportunity given by the pandemic and encourage people to use active transport more in the new normal situation to achieve sustainable transportation outcomes. This study explores the expected change in active transport mode usage in the new normal situation in Bangladesh based on the data from a questionnaire survey. The study finds that 56% and 45% of the respondents were expected to increase travel by walking and cycling, respectively, during the new normal situation. On the other hand, 19% of the respondents were expected to do the opposite. The study further identifies the factors influencing the expected change in travel by active transport modes during the new normal situation by developing multinomial logistic regression models. Finally, this study proposes policies to increase active transport use beyond the pandemic and ensure sustainable mobility for city dwellers and their well-being.

Understanding the nature of transit travel demand is at the heart of transportation policy making and the success of transit systems. Unfortunately, most existing studies focus narrowly on a single or a few transit systems or metropolitan areas to analyze the determinants of transit travel demand. It is, therefore, difficult to generalize their findings over a broader geographic scale. This paper examines and explores the determinants of transit travel demand by bus generalizable to the entire U.S. by investigating internal and external factors at the U.S. metropolitan statistical area (MSA) level for 2010. The authors collected and used data for all 358 MSAs nationwide. Internal factors are those that the transit managers and operators have some control over (e.g., transit supply, transit coverage), whereas external factors are those that they do not have control over (e.g., population density, vehicles per household). Several variables came directly from the U.S. Census Bureau and National Transit Database, whereas the authors constructed others using data from these two sources. The paper employs a log-log regression model to address the issues of non-normality, non-linearity, and heteroscedasticity. Findings suggest that internal factors tend to be significant predictors of travel demand by bus mode compared with external ones. As such, transit authorities have the ability to attract ridership by adjusting the influential internal factors under their control.

The impacts of COVID-19 on the transportation system have received attention from researchers all over the world. Initial findings reveal that patronage of public transport has gone down, while the use of active transport has increased in general. To the best of our knowledge, no study has focused on the pandemic’s effects on motorcycle mode, let alone in the context of an Asian city. We attempted to fill this void in literature by investigating if COVID-19 has influenced people to purchase motorcycles and determining the factors driving their intentions. The study is based on an online survey of 368 people in Dhaka, the capital of Bangladesh. The study found that around 46% of the respondents were expected to increase travel by motorcycle during the post-lockdown period. About 21% of the respondents were also expected to do the opposite. Around 31% of the respondents planned to purchase a motorcycle by August 2021, and the results indicated that the pandemic has influenced more people to purchase motorcycles compared to the pre-pandemic period. The study further identified factors that influenced the respondents’ plan for purchasing a motorcycle during the post-lockdown period applying the binary logistic regression. Based on the findings of the study, policy measures were proposed for controlling the growth of motorcycle numbers and increasing the use of active transport modes as its alternative, and consequently, helping to achieve sustainable transportation outcomes.

Chalan Beel, the largest wetland in Bangladesh, plays a crucial role in maintaining ecological balance and supporting local community livelihoods. This vital ecosystem has undergone significant landscape transformations over the past five decades due to increasing anthropogenic pressures. This is the first study that examines spatiotemporal changes in land cover, Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST) in the Chalan Beel wetland ecosystem from 1973 to 2023 using remote sensing (RS) and Geographic Information System (GIS). Landsat imagery was utilized, and an unsupervised classification was performed to categorize land cover into five major classes: developed land, farmland, high vegetation, water, and wetland. The results reveal a clear trend of increasing anthropogenic activities, particularly the expansion of farmlands and developed areas, alongside a decline in high vegetation and wetlands, with the most pronounced changes occurring between 2013 and 2023. Accuracy assessments yielded overall accuracies of 72.5% (1973), 73.8% (1980), 75.0% (1993), 73.8% (2003), 72.5% (2013), and 77.5% (2023). NDVI analysis indicates declining vegetation health from 1973 to 2023, while LST trends reflect a consistent rise in surface temperatures from 1993 to 2023. These findings highlight intensified land use pressures driven by population growth and economic activities. The study provides critical insights into the environmental dynamics of Chalan Beel, emphasizing the urgent need for sustainable land management and wetland conservation strategies. It contributes to evidence-based policymaking and supports global efforts to achieve Sustainable Development Goal 6, Target 6, which is related to protecting and conserving resources like mountains, forests, wetlands, rivers, aquifers, and lakes throughout the globe, including Bangladesh. Graphical Abstract This graphical abstract provides a comprehensive, step-by-step visual summary of the spatiotemporal assessment of Chalan Beel, Bangladesh’s largest wetland ecosystem, from 1973 to 2023. It illustrates the methodological flow from satellite image retrieval and preprocessing through land cover classification, NDVI, and LST computation using ArcGIS Pro 3.1. The workflow highlights the use of thermal and spectral bands to derive key environmental indicators. On the left, land cover change maps reveal a sharp increase in developed and farmland areas, alongside a decline in high vegetation and wetlands. The NDVI trend chart shows a progressive decrease in vegetation health, while the LST trend graph confirms a steady rise in surface temperatures. These results demonstrate clear signs of ecological stress driven by increased anthropogenic activities. Combining time-series maps, diagrams, and classification outputs creates a visually intuitive It effectively communicates how landscape transformations and environmental degradation interrelate over the last five decades. This visual summary is an essential bridge between technical methodology and actionable insights, reinforcing the urgency of adopting sustainable land management and wetland conservation policies in Chalan Beel of Bangladesh.

By employing descriptive statistics and multinomial logistic regression models, the paper investigates factors that affect the travel mode choice behavior of a college community for both commuting to the campus from their residences and commuting on campus from one facility to another. Results show that car ownership, travel distance, age, gender, academic status, income, perception of safety, number of weekly trips, and weather conditions affect people’s mode choice decisions significantly. The study finds that increasing travel distance, age, and being a staff member positively impact car mode choice, faculty members are more likely to bike and walk compared to undergraduate students, and unlike the authors’ predictions, the higher-income people are more likely to walk on campus. Results also reveal that car users change travel modes more often than active transport mode users based on semesters and that although women are less likely to bike to the campus, they are more likely to walk and bike on campus. If the number of trips increases, people prefer cars to walk, bike, and ride a bus to commute to the campus while they prefer walking to driving a car on campus. The study contributes to help create pollution-free and healthy urban college campuses that, on larger scales, will further contribute to developing sustainable cities to achieve the Sustainable Development Goals as described by the United Nations, particularly goal number 11, “to make cities and human settlements inclusive, safe, resilient and sustainable,” and thereby contribute to improving urban living conditions.