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Open spaces function as the lungs of a city, providing environmental and social benefits. In a densely populated city like Dhaka, community-based open spaces play a crucial role in enhancing urban livability. The sustainability of such spaces largely depends on effective management. However, these spaces face multiple barriers in this regard. Therefore, this study aimed to explore the transformation of a community-based open space named Road No. 17 Park, understand the connection with other organizations and identify challenges faced. Employing Participatory Rural Appraisal (PRA) tools and Key Informant Interviews (KIIs), the research identifies that the committee’s strong relationships with the Ward Councillor and the local parliamentary member facilitated management activities, while unity among members remains its core strength. However, inadequate financial resources pose significant challenges. Hence, the study recommended future guidelines on the management of community-based open spaces, highlighting effective Public-Private Partnership and funding from NGOs and the local government.

This data article introduces a detailed and structured dataset derived from a survey exploring the psychological factors that influence transport mode choices in Pabna Municipality, northwest of Bangladesh. This dataset covers a wide range of socio-demographic factors, i.e., income, occupation level, and age, as well as the factors related to the choice of the mode of transportation, money expenditure, and a set of psychological determinants, i.e., the perceived safety, financial constraint, and environmental consciousness. These aspects are often under-represented in existing research. The data were collected using a carefully structured questionnaire survey of 348 samples conducted over a three weeks survey of urban residents on different points. The dataset is an important resource to researchers working on urban planning, transportation behaviour analysis, environmental psychology and public health as it provides a more detailed understanding of how psychological factors interact with mode choice in transportation. This will help in policy-making, to contribute to the broader field of urban transport planning. To validate the reliability and predictive capability of the dataset, several supervised machine learning models were applied, demonstrating strong classification performance for transport mode choice. The dataset can be used in future research on inclusion-based, user-friendly transport systems especially in Bangladesh as well as other rapidly urbanising regions, as it is in line with global sustainability.

Flooding is one of the most frequent and severe natural hazards in the coastal region of Bangladesh, where low-lying terrain, tidal incursion, and frequency of tropical storms enhance the degree of susceptibility. Mongla and Sharankhola Upazilas in Bagerhat district experience recurrent inundation driven by tidal surges, river overflow, and intense monsoonal rainfall, with exposure amplified by fragile geomorphology, inadequate drainage, and limited infrastructural resilience. An integrated Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) approach has been developed to comparatively assess the flood risk of these two upazilas, which is presented in this paper. The study integrates flood hazard and vulnerability to produce composite risk maps that are intended to aid local disaster management and planning. This was carried out by relative weight assignment of flood-controlling parameters through expert assessment and generating spatially explicit hazard, vulnerability and composite risk maps using GIS overlay analysis. Hazard factors were distance from rivers, slope, drainage density, average annual rainfall, elevation and Topographic Wetness Index (TWI). On the other hand vulnerability parameters were Land Use Land Cover (LULC), distance from roads, road-river intersections, population density and literacy rate.The results show different flood risk dynamics in these two study areas. In Mongla the two major factors that drive vulnerability are distance from roads (38%) and literacy rate (31%) which suggest that accessibility and educational awareness increase flood susceptibility but hazard is mainly determined by rainfall with average annual rainfall (37%) and drainage density (25%) being the most significant variables. In Mongla, about 59 % of area comes under moderate to high flood risk, and almost all of the unions are flood prone. However the unions of Chandpi and Sonailtala have been identified as most at risk. On the other hand, Sharankhola’s vulnerability is dominated by literacy rate (37%) and population density (24%), indicating the significance of social preparedness and population concentration, whereas distance from rivers (32%) and drainage density (25%) controlled the hazard in the area. While moderate-risk zones occupy the majority of Sharankhola (31 %), Southkhali and Royenda unions are identified as high-priority zones concerning flood risk. The consistent influence of drainage density across both upazilas underscores a hydrological vulnerability in the southern coastal plain. Overall, the integrated AHP–GIS approach outlines spatially explicit flood risk zones, which may identify regions of resilience and adaptation both directly and indirectly. This comparative analysis emphasizes the significance of local disaster management policies to handle physical variables and socio-economic causes underlying flood risk. Such essential information helps policy makers, developers, and local people to prioritize measures, increase flood preparation and make infrastructure more robust in exploitable coastal regions of Bangladesh.

Transport systems are an important aspect of social and economic growth of cities and especially those cities that rapidly grow such as Khulna City. This paper assesses operational performance of three unsignalized intersections; Shibbari, Zero Point and Moylapota in the heterogeneous traffic scenario taking into account diverse types of vehicles, such as non-motorized vehicles, semi-motorized vehicles, and motorized vehicles. The surveys on traffic volume were performed during the times of maximum traffic, and the data was used to calculate the approach capacities and to estimate the volume-to-capacity (V/C) ratios of the Level of Service (LOS) analysis. The results demonstrated that some methods, including the Khulna City Bypass and Khulna-Satkhira Road, work at LOS E-F, which implies that the methods are overloaded and the flow situation is unstable. Other methods, on the other hand, sustain LOS C, which is an indicator of moderate congestion. Another result of the study was the movement in modal share with an increasing use of motorized mode at peak hours. Its findings highlight the urgent need of capacity, adaptive traffic and web-enhanced public transportation and non-motorized transport infrastructure. This study not only addresses good insights on traffic management planning in Khulna but other mid cities in Bangladesh where the same is being experienced and thereby aiding in improved transportation planning and development of the city.

Rapid urbanization and increasing vehicle density have placed severe pressure on transportation systems in developing cities like Khulna, Bangladesh. The city’s heterogeneous traffic, composed of various vehicle types such as Easy-Bikes, Mahindras, rickshaws, buses, and private cars, creates complex flow patterns and frequent congestion, particularly at unsignalized intersections. Understanding these dynamics is crucial for designing efficient, safe, and sustainable traffic management solutions. The primary objective of this study was to develop, calibrate, and validate a microscopic traffic simulation model using PTV VISSIM to accurately represent Khulna’s mixed-traffic conditions and evaluate the model’s reliability in reflecting real-world scenarios. The research utilized detailed field data collected from two key intersections— Shibbari and Zero Point—during peak hours, including traffic volume, vehicle composition, turning movements, and parking activities. The model incorporated realistic lane usage, conflict areas, and reducedspeed zones to simulate authentic driver behavior under non-lane-based, mixed-traffic conditions. Calibration was performed using the Wiedemann 74 car-following model, adjusting parameters such as standstill distance and safety distance to reflect local driving characteristics. Validation was achieved through the Geoffrey E. Havers (GEH) statistic and Mean Absolute Percentage Error (MAPE), where GEH values ranged from 0.75 to 3.4 and MAPE from 1.79% to 9.84%, indicating strong agreement between simulated and observed traffic volumes. The results confirm that the model accurately reproduces Khulna’s heterogeneous traffic behavior and congestion patterns. This study demonstrates that a well-calibrated VISSIM model can serve as a powerful decision-support tool for traffic engineers and urban planners, aiding in evaluating existing infrastructure, forecasting future traffic conditions, and designing targeted interventions such as signalization, dedicated lanes, or parking management strategies. Overall, the research contributes to developing more efficient, safer, and environmentally sustainable urban transport systems in growing South Asian cities.

Road traffic accidents (RTAs) are one of the leading causes of mortality and morbidity throughout the world and in low and middle-income countries such as Bangladesh in particular where roads are being developed faster, additional infrastructures are inadequate and necessary actions have been established to reduce the vice to ensure that it escalates even more. In this paper, I analyze the spatial and statistical features of RTAs in Khulna City, Bangladesh, over the period of 2010 to 2019 and identify the areas likely to experience the accidents as well as those factors influencing the building up. The analysis provides a detailed examination that combines the spatial modeling of Geographic Information System (GIS) with more complex statistical analysis to provide the entire picture of dynamics of accidents in the urban environment. Accident data were analysed using Kernel Density Estimation (KDE) and Getis-Ord Gi star statistic over a period of 9 years in order to determine how data clustered spatially and statistically significant areas of greatest occurrence. These spatial results were supplemented by chi-square tests and binary logistic regression models in establishing the existence of a correlation between the accident hotspots and the factors that impacted them which include a vehicle type, time of the day, driver age, conditions of the road, the consequences of the crash. The result indicated that the spatial clustering of RTAs was higher around Khulna Sadar, Khan Jahan Ali and Sonadanga thanas (high density of traffic, the geometries of roads, and mixed modes of travel). The statistical results coincided with the preliminary results that time of day (p = 0.035), age group of the driver (p = 0.041), and the result of the accident (p = 0.004) showed significant results in the development of hotspots, but the type and speed of the vehicle was also weak or meaningless. The logistic regression equation (Nagelkerke R2 = 0.462) established that the blend of spatial, temporal and human variables to clarify the fluctuation in the incidence of the hotspots clarifies nearly fifty percent of the fluctuation. This spatial analysis and statistical analysis demonstrate that RTAs in Khulna are not scattered everywhere statistically, but they are very clustered in certain permanent clusters that have been intensified over time. The study reveals that local solutions of safety interventions (enhancing light into roads, more vigilance during rush time and certain driver education) are urgently required. The results provide a practical conceptual framework that may be utilized by policy makers and urban planners in implementing evidence-based policies in reducing the risks of accidents and enhancing sustainable urbanism in Khulna and other urban areas in Bangladesh.

This study provides an in-depth analysis of the gender justice challenges faced by transgender individuals in Khulna, Bangladesh through the lens of just city theory. Despite the legal recognition of the Transgender community in 2013, they continue to experience social isolation, violence and systemic discrimination. The research investigates how democratic practices are undermined, how the preservation of transgender identity as a distinct group is obstructed and how material inequality continues to weaken their pursuit of social justice. Using purposive sampling, 15 in-depth face-to-face interviews with transgender individuals were conducted to capture lived experiences. The findings highlight four critical factors: the daily social, economic, political and cultural struggles transgender people endure; the structural issues driving these struggles; the impact of these problems on democracy, identity and equality; and their broader implications for social justice when assessed against the just city paradigm. The study also reveals a persistent behavioral challenge within the majority population who often fail to recognize transgender people as distinct genders beyond male and female. This lack of recognition perpetuates fear and exclusion, trapping transgender individuals in a cycle that limits their rights, equality and full participation in society.

Salinity has been a serious problem in Bangladesh’s coastal region for several decades. Coastal vulnerability and the water crisis are exacerbated by sea-level rise, changing climate patterns, frequent natural disasters, and man-made changes to natural settings. Bangladesh’s coastal areas, which are home to 20 million people, face a variety of water-related hazards, ranging from chronic salinity, which reduces agricultural yields and impacts drinking water quality, which affects livelihoods and wipes out agricultural production. In addition, concurrent floods and cyclones contribute to the deterioration of freshwater availability. Water hazards and a lack of sufficient quantity and quality of water aggravate poverty in coastal areas. Understanding the complex dynamics between climate change, water security, human well-being, and economic growth is necessary. This study employs both quantitative and qualitative approaches to comprehend the complexities. By analyzing water pH, the electrical conductance of saturated extract, and other factors associated with salinity, this study investigates the salinity level, its impact on portable water sources, and changes in the natural environment of Anwara coast (South-eastern coast) in Chattogram District. Furthermore, the FGD (Focus Group Discussions) technique is used to understand the long-term effects of water security on local livelihood patterns. This mixed-method approach helps to comprehend the complexities of coastal Bangladesh’s climate change, water security, and livelihood changes. Research findings indicate a significant increase in salinity level in the study area which affects water consumption patterns and leads to livelihood diversification of the South-eastern coastal community in Bangladesh.