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Cities are being restructured as a result of globalization, information flows, and changing economic processes. Global cities become command and control centers for subordinate production centers, resulting in the transformation of the mega-metropolitan system from monocentric to polycentric. The purpose of this paper is to analyze the urban transformation of the Dhaka region, Bangladesh. We estimated urban areas using remote sensing techniques and nighttime light data analysis. The urban areas were extracted from VIIRS nightlight datasets using ISODATA clustering algorithm. Urban areas were examined for two periods, from 2012 to 2017 and from 2017 to 2022. Apart from visual examination, the extracted urban areas were validated through the use of random sample points. Urban transformation was determined using hotspot analysis and the differentiation index for urban expansion. The finding is that Dhaka has continued to grow due to the continuous population growth and industrial centers’ proximity. Secondly, the majority of physical expansion of the Dhaka region occurs along major arterial highways and shows a functional intra-regional decentralization of industrial agglomeration.

Urban density not only represents the intensity of travel demand, but also serves as a useful tool for quantifying the elements that influence travel behavior and demand. In this study, Khulna City of Bangladesh has been selected as a case study to explore the impacts of urban density on travel behavior in a city of a developing country. The average characteristics of urban density, as well as their impacts on travel behavior and demand, have been studied using geospatial analysis techniques. Urban densities have been categorized into Single Density (Population Density, Employment Density, and Building Density) and Composite Density (Household to Work trip Density, Household to School trip Density and Household to Shop trip Density) based on characteristics of travel behavior and demand. Descriptive statistics have been used to explore the impacts of urban densities on the various trip characteristics such as trip production, trip distance, trip cost, trip time, and trip mode. Diversity of trips and overall trip attraction areas have been identified using the Shannon diversity index and other spatial analyses. Trip production, trip distance, trip time, trip cost, and mode choice all show a positive linear relationship with urban single-density, according to this study. The everyday activities of residents are closely related to urban composite densities, and trip production increase in tandem with composite densities. It has been concluded that different urban densities have significant impacts on travel demand and travel behavior.

Rapid urbanization, human demands with dynamic hydrology, and land resources impact the carbon cycle and ecosystem resilience at the city level. The expansion of urban areas is continuously replacing the vegetative cover (VC), which accelerates carbon emissions (CE), raises land surface temperature (LST), and contributes to global warming. This study aimed to assess the CE dynamics in Penang City, Malaysia, resulting from land use and land cover (LULC) changes during 1996–2021 and to identify the impacts of CE dynamics on LST change and urban heat island (UHI) effects. In this regard, remote sensing and geospatial methods were applied to monitor the LULC changes and used the biomass carbon stock assessment techniques to quantify carbon storage. The findings of the study illustrate a 17% decrease in forest cover and an excessive increase in urban areas (22%), average LST (8 °C) and UHI (38%) in the last 25 years. The carbon stock (CS) concentration reveals a 24% decrease in high CS areas with more than 1% yearly decline from 1996 to 2021. In addition, due to the massive VC loss, carbon attracted the sun rays, which led to lower CS in built-up and no VC areas. The strong positive correlations between CE and LST and CE and UHI (R2 > 0.7961) at a significant level (p-value < 0.001) suggest that CE is highly responsible for the LST increase and UHI effects. This study proposes effective strategies, including afforestation, reforestation and urban greening practices through rooftop gardening, which can significantly improve the CS capacity and reduce climate change and global warming impacts in the fastest-growing cities.

A mega-industrial region is frequently the result of purposeful regional development policies. Mega-region development is a new form of rapid urbanization and economic growth that is stimulated by government infrastructure projects. The objective of this research is to examine how the core built-up area and population growth of Khulna city, Bangladesh are slowing relative to the periphery as a result of mega-regionalization. We describe the spatial transformation of the city using GIS and remote sensing for built-up area identification and two urban expansion indices–expansion intensity index and urban expansion differentiation index–for quantitative measurements. The findings indicate that the city's periphery is seeing a higher rate of land use change and population agglomeration than the core. Secondly, the development hotspots are located in the peripheral regions. This change is largely fuelled by conventional speculative land and housing development similar to most cities with growing economies, and not the result of becoming a mega-industrial region. The land use transformation at the regional level and the city’s periphery has catastrophic repercussions because of massive resettlement and depeasantization.

Central Business Districts (CBDs) are impeccable areas of traffic attractions exacerbated by the increase of rapid population density, enormous urbanization, and increasing economic and commercial activities. Traffic congestion in the CBD areas is a perpetual problem for sustainable urban development. This study detailed the traffic congestion states and the factors influencing traffic congestion in the CBD areas of Khulna City. In this regard, spot speed, journey speed, running speed, and volume of all types of vehicles in the four CBD areas during peak and off-peak hours on both weekends and weekdays have been measured through manual counting and video recording methods. The traffic congestion state in the study area has been assessed through Level of Service, Speed Performance Index, Road Segment Congestion Index. The outcome of these indices revealed the worst congestion state in all CBD areas with breakdown flow. The Active Road Performance Index explained that inadequate parking facilities, illegal road occupancy by roadside vendors, and on-street parking decreased the road efficiency by 32 to 82% in different areas. The regular road users believed that congestion occurs mostly between 6.00 PM and 9.00 PM. This study found that rapid increase in vehicle population, poor public transport, pedestrians’ behavior, illegal road occupancy, and fragile enforcement of laws are leading the traffic condition of Khulna towards an unsustainable future. The outcome of this study will provide useful information for urban planners, policymakers, and practitioners to devise appropriate strategies for reducing congestion that would help to ensure a sustainable urban transport system.