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This study examines the impact of urbanization on growth and the role of international financial flows in the urbanization-growth nexus.

The study applies the panel least square estimation to examine the impact of urbanization on growth using panel data from 50 developing countries from 1980 to 2016. Further, addressing the endogeneity issues in panel estimations, the study applies the dynamic System-GMM approach to investigate the role of financial flows in urbanization and their impact on economic growth in developing countries.

Contrary to the conventional literature, we found a non-linear (U-shaped) relationship between urbanization and growth. Our findings demonstrate that growth is reduced at a lower level of urbanization due to less availability, concentration, and synchronization of production factors. The concentration of physical and human capital and technological advancement in urban areas help developing countries achieve economic growth at a higher level of urbanization. Robust estimations divulged that foreign aid spent on infrastructure development and expanding urban regions helps promote economic growth. Nevertheless, as a resilient factor, remittances buffer the rapid pace of urbanization and reduce growth by resisting the migration of labor and capital from rural to urban areas.

The paper's findings suggest policymakers promote urban infrastructure and development using local and international funds since its increased level spurs economic growth. Further, the results advise policymakers to reduce aid dependency, attract FDI, and facilitate the easy and low-cost transfer of money to promote remittance inflows since both FDI and remittances positively contribute to economic growth.

The paper contributes significantly to the literature by determining the U-shaped relationship between urbanization and growth and highlighting the role of international flows in the urbanization-growth nexus.

This study examines the contribution of urban development to Vietnam's economic progress over the period 1986–2020. The study uses an augmented Solow framework, where urbanization is included as a shift variable in addition to capital per worker and accounts for structural breaks. It examines the cointegration and the long-run and short-run effects of urban development from four different cases of cointegration (constant, restricted constant, restricted trend and trend options), with each case accounting for the effect of a significant structural break. Also, the study provides causality nexus to check the presence of urbanization-led growth hypothesis. From the results, we note a long-run positive effect of urbanization on economic growth, but no short-run effects. In all cases, a 1% increase in population results in 0.8–0.9 increase of output, hence supporting a positive and momentous effect of urbanization over the long-term. We note a significant positive effect of a single structural break period (1991), which is a period of major shift towards economic progress. We note bidirectional causality between capital and output and a unidirectional causality from output and capital to urbanization. The former suggests a mutually reinforcing effect of capital accumulation and economic growth, and the latter indicates that urban development necessitates economic growth and capital accumulation. The findings derived from this study provide further impetus for urban development and urban policies and consider urbanization as a critical source of economic growth for Vietnam.

This paper aims to assess the current and future dynamics of land cover transitions and analyze the vegetation conditions in Abuja city since its establishment as the capital of Nigeria in 1991.

A random forest classifier embedded in the Google Earth Engine platform was used to classify Landsat imagery for the years 1990, 2001, 2014 and 2020. A post-classification comparison was used to detect the dynamics of land cover transitions. A hybrid simulation model that comprised cellular automata and Markovian was used to model the probable scenario of land cover changes for 2050. The trend of Normalized Difference Vegetation Index was examined using Mann–Kendall and Theil Sen’s from 2014 to 2022. Nighttime band data from the National Oceanic and Atmospheric Administration were obtained to analyze the trend of urbanization from 2014 to 2022.

The findings show that built-up areas increased by 40%, while vegetation, bare land and agricultural land decreased by 27%, 7% and 8%, respectively. Vegetation had the highest declining rate at 3.15% per annum. Built-up areas are expected to increase by 17.1% between 2020 and 2050 in contrast with other land cover. The proportion of areas with moderate vegetation improvement is estimated to be 15.10%, while the proportion of areas with no significant change was 38.10%. The overall proportion of degraded areas stands at 46.8% due to urbanization.

The findings provide a comprehensive insight into the dynamics of land cover transitions and vegetation variability induced by rapid urbanization in Abuja city, Nigeria. In addition, the findings provide valuable insights for policymakers and urban planners to develop a sustainable land use policy that promotes inclusivity, safety and resilience.

This chapter aims to comprehend the challenges of urban mobility in smart cities and the measures to mitigate these challenges. This chapter also tries to study how sustainable mobility can be achieved to improve the quality of life in smart cities. In this direction, this chapter reviews various newspapers, academic reports, travel reports, government portals, government websites and research papers. Results and discussions are then carried out based on such data. So, the sources of data are secondary in nature. This chapter presented an overall comprehensive discussion on urban mobility, its challenges and the measures to combat these challenges. Further, this chapter confirmed that sustainable mobility helps in improving the quality of life. Practically, this chapter offers many implications to urban transport companies, providers, government and policymakers. Urban transport companies, providers, government and policymakers may be able to understand that the path to leading a quality life in today's smart cities lies in sustainable mobility. This chapter is original in the sense that the researchers, to their limited knowledge, could not find a chapter that discusses the challenges posed by smart cities in the form of urban mobility, and that sustainable mobility is the only path to enhance the quality of life by making the environment sustainable.

This paper aimed to develop a participatory methodology to analyze the disaster risk creation in coastal cities, based on an approach that combines social, urban, environmental and disaster risk elements.

The methodology uses some aspects of three theoretical approaches in a complementary way: i) the Pressure and Release (PAR) framework for the identification of dynamic pressures that contribute to disaster risk creation; ii) the application of Drivers, Pressure, State, Impact, Response (DPSIR) framework to analyze environmental dimensions; and iii) urban analysis, applying the Strengths, Weaknesses, Opportunities and Threats (SWOT) tool to classify urban processes. The methodology combined the use of satellite remote sensing data to analyze the urban sprawl and citizen science methods to collect social and environmental data, using the case study of the watershed of the Juqueriquerê River in the coastal city of Caraguatatuba, Brazil. The pilot project was part of a local university extension project of the undergraduate course on Architecture and Urban Planning and also engaged residents and city hall representatives.

The satellite remote sense data analysis indicated a continuous urban sprawl between 1985 and 2020, especially in the south of the Juqueriquerê watershed, reducing urban drainage and increasing the extension and water depth of urban flooding and riverine floods. Using citizen science methods, undergraduates identified settlements with limited economic resources to elevate houses and a lack of infrastructure to promote a resilient coastal city. After identifying the dynamic pressures that contribute to disaster risk creation and the weaknesses and strengths of a resilient city, undergraduate students proposed urban planning interventions and gray and green infrastructure projects to mitigate disaster risks.

The paper identifies urban sprawl in disaster-prone areas as one of the risk factors contributing to disaster. It also comprehensively analyzes differences between different zones in the Juqueriqere River, which will be useful for policy-making.

The method presented an interdisciplinary approach that used satellite remote sensing data and citizen science techniques to analyze disaster risks in coastal cities. The multidimensional approach used to evaluate risks is useful and can be replicated in other similar studies to gain a more comprehensive understanding of disaster risks.

As more and more cities adopt resilient, inclusive and sustainable principles, circular economy (CE) emerges as a critical ally in developing smart cities. The technology-driven environment of smart cities and CE's resource-efficient principles are perfectly compatible, overcoming challenges and highlighting benefits like increased resource efficiency. The integration of CE in smart cities is thoroughly analyzed in this chapter using VOSviewer and RStudio, tracing its history and pointing urban innovators towards a circular future. The categorization of obstacles to CE implementation in smart cities, the provision of knowledge about barriers and the facilitation of methodical solutions constitute a critical focus of research. Additionally, by analyzing pertinent literature, this investigation highlights the importance of integrating the concepts of the CE and the smart cities, illuminating the interdisciplinary nature of this field. This synthesis provides policymakers and planners with the knowledge they can use to advance sustainable urbanization effectively.

The advent of the 21st century marks a pivotal era where rapid urbanization intersects with technological advancements, giving rise to the concept of smart cities. These urban environments harness information and communication technologies to improve service efficiency and enhance the quality of life. Parallel to this development is the emergence of circular economy (CE) models, recognized globally as an essential response to environmental challenges. This chapter delves into the integration of CE principles in smart cities, emphasizing a shift from traditional linear models towards sustainable, resource-efficient urban landscapes. Exploring the evolution of smart cities and CEs, this chapter highlights synergies and potential benefits of this integration while acknowledging significant challenges. These include technological, infrastructural, financial, policy-related and social–cultural barriers. Through a comprehensive analysis of literature, case studies and best practices, effective strategies to overcome these challenges are presented. This chapter emphasizes the roles of technological innovation, policy reform, stakeholder engagement and community involvement in driving this transformation. This chapter identifies future research areas and emerging trends, underscoring the profound impact of integrating CE principles in smart cities. This integration is pivotal for shaping sustainable and resilient urban futures, thereby redefining the paradigm of urban development in the modern era.

In the context of modern urbanization, optimizing resources such as energy, materials, water and labour is no longer solely an environmental concern but a strategic economic necessity. This chapter underscores the vital connection between smart cities and resource efficiency, highlighting sustainable practices as crucial amidst the ever-expanding urban landscape. This chapter commences by demystifying key terms like ‘smart city,’ ‘data analytics,’ ‘artificial intelligence’ and ‘resource efficiency.’ It illuminates how these concepts intertwine and emphasizes their pivotal roles in shaping urban sustainability. Furthermore, this chapter unravels the multifaceted components of smart cities, showcasing their real-world use cases and the techniques of data analytics and artificial intelligence (AI) driving transformative changes. It draws from an extensive body of research, exemplifying how various data analytics techniques have been leveraged in the realm of smart cities. Towards its conclusion, this chapter provides a comprehensive overview of these techniques and their applications, shedding light on their potential to revolutionize resource management in urban environments. In essence, this chapter serves as a valuable compendium of knowledge, offering insights into the critical synergy between smart cities, data analytics, AI and resource efficiency. It underscores the imperative for cities to harness data-driven insights and technological advancements to achieve sustainable and prosperous urban futures.

The circular economy (CE) is a sustainable economic model that has the potential to create new opportunities, reduce environmental impact and enhance social well-being. Ho Chi Minh City (HCMC), the largest city in Vietnam, has experienced rapid economic growth in recent years, but at the cost of the environment and public health. The city could reduce waste, conserve resources and promote sustainable production and consumption by adopting CE principles. Employing qualitative research, including content analysis, we construct a SWOT analysis to assess HCMC's strengths, weaknesses, opportunities and threats in the CE context. The city possesses several strengths, such as a vast potential for a CE and a robust economic foundation. However, it also faces multiple weaknesses, including insufficient infrastructure, inadequate citizen and business awareness and participation, ineffective policy enforcement and a deficiency of standards for recycled products. This chapter will conclude that the CE presents an opportunity for HCMC to reduce its dependence on imported raw materials, increase local value creation and create new jobs in the CE sector.

The presence of green spaces plays a vital role in promoting urban sustainability. Urban green parks (UGPs) help create sustainable cities while providing fundamental ecological functions. However, rapid urbanization has destroyed crucial green areas in Ranchi City, endangering inhabitants’ health. This study aims to locate current UGPs and predict future UGP sites in Ranchi City, Jharkhand.

It uses geographic information system (GIS) and analytical hierarchical process (AHP) to evaluate potential UGP sites. It involves the active participation of urban communities to ensure that the UGPs are designed to meet dweller’s needs. The site suitability assessment is based on several parameters, including the normalized difference vegetation index (NDVI), land use and land cover (LULC), population distribution, PM 2.5 levels and the Urban Heat Island (UHI) effect. The integration of these factors enables an evaluation of potential UGP’s sites.

The findings of this research reveal that 54.39% of the evaluated areas are unsuitable, 15.55% are less suitable, 12.76% are moderately suitable, 11.52% are highly suitable and 5.78% are very highly suitable for UGPs site selection. These results emphasize that the middle and outer regions of Ranchi City are the most favorable locations for establishing UGPs. The NDVI is the most important element in UGP site appropriateness, followed by LULC, population distribution, PM 2.5 levels and the UHI effect.

This study improves the process of integrating AHP and GIS, and UGPs site selection maps help urban planners and decision-makers make better choices for Ranchi City’s sustainability and greenness.