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There were several attempts in identifying the urban poor communities in the cities and towns of Bangladesh in order to fix a correct target for poverty alleviation programmes. However, due to methodological problems, it was always problematic to set a correct target. It was felt by the authority and donor agencies that there was hardly any correct figure of the number of poor and realistic statistics on their characteristics. This paper highlights the methods of mapping and collection of some basic data on poor settlements. It has been possible to identify the poor easily as the poor themselves were involved in the process of identification of their own settlements. The community people, most of whom were little educated successfully conducted the task entrusted to them. This helped them understand the nature and issues of poverty which they can utilize when the actual poverty alleviation programme is launched. Although the study was conducted on 27 cities, this paper explains the mapping and poverty situation of only one city Chattagram. The exercise identified 301,527 households as poor in about 5,778 poor settlements in the Chattagram City Corporation area and estimates about 53.6% of the city’s total population were poor of which 44.6% of the poor households were extremely poor.

As bike-share systems proliferate across the US, a deeper understanding of current bike-share users could enable an expansion of these services and their benefits to a larger population. To grow bike-share demand sustainably and equitably, cities must understand how different segments of the population use this service. Understanding the different segments within a market enable operators to develop strategies that are tailored toward the needs of each segment. This study uses data from bike-share user surveys in the Sacramento region to perform market segmentation based on perceptions of the bike-share service, mode use patterns, and bike-share use. We focus on the market segments with more limited means of transportation: low-income individuals, zero-car households, students, and transit and car-share users. The results show that individuals with low incomes, those without cars, and students use the service frequently for commuting and a variety of non-commuting purposes. Bike-share is generally adopted by all mode user groups but is used at a higher rate by the super multimodal and active multimodal groups. The occasional users of the bike-share service are mainly those with higher incomes and individuals who have access to a personal car. The segments consisting of non- and infrequent-personal bike users use the bike-share service at a greater rate for different purposes than regular bicyclists, suggesting that bike-share may act as a lever for increasing bike travel for some users. Results from data mining suggest that bike-share operators should target low-income and zero-car owners for new recruitment as these groups are more likely to use bike-share frequently. The results provide insights that may be helpful to cities as they consider strategies to increase bike-share demand in a way that enhances social equity.

This study explores mode-specific problems faced by movement-challenged persons (MCPs) in making trips by different travel modes in Dhaka, Bangladesh. 400 MCPs were asked to rank the extent of mobility challenges of four modes on a scale of one to five through a questionnaire survey. MCPs reported lack of ramp and undulated surface are the most severe problems related to bus and walking respectively while excessive fared charged by drivers is found as the most severe problem for both rickshaw and CNG. This study captures the uneven effects of mode-specific challenges endured by MCPs of different gender, ages, and mobility aid users. Opinions on the lack of standardized slope along footpaths, the presence of cracks on footpaths, the lack of ramps on the buses, and rude behavior of bus staff vary significantly with gender, age, and mobility aids; the unwillingness of bus staff to carry MCPs varies significantly with age and walking instrument; the narrow width of footpaths, the additional fare charged by rickshaw pullers, the lack of space to keep the mobility supporting aids on buses and rickshaws, and the lack of available space to maneuver on a bus varies significantly with the walking instrument.

In this work, we analyzed the locations of existing bus stops in the Halifax Regional Municipality (HRM) area and then calculated the walking distance in time in order to understand the accessibility for pedestrians. In doing so, we employed geographic information systems (e.g., spatial and network analysis tools) to generate accessibility models from bus stops at 5, 10, 15, and 20 min of walking distance. After generating the service area of bus stops on maps, we overlaid socioeconomic variables (i.e., age group, income, and bus-stop accessibility) to better understand the HRM public transport network. We found that population density was an important consideration in providing the number of bus stops in specific communities, which may be related to the facilities offered by the urban hierarchy. Furthermore, we established a relationship between transit stops and accessibility for people in age groups of between 0 and 19 (e.g., school-going children) and 65+ (i.e., the older population) so as to obtain an understanding of the time required for them to access the bus stops on foot. Overall, 77% of the population in the HRM was served by public transport within 5 min of walking; however, for the 65+ cohort, this number was higher (82%). A significant amount of the young population (23%) was served over longer distances than 10′ of walking. We summarize that our findings are critical for planners, practitioners, and researchers in order for them to understand the present transit system in place based on accessibility to the bus stops within walking distance.