This is a foundational text in urban geography, now updated to include the essay 'The Right to the City'. Throughout his distinguished and influential career, David Harvey has defined and redefined the relationship among politics, capitalism, and the social aspects of geographical theory. Laying out Harvey's position that geography could not remain objective in the face of urban poverty and associated ills, "Social Justice and the City" is perhaps the most widely cited work in the field. Harvey analyzes core issues in city planning and policy - employment and housing location, zoning, transport costs, concentrations of poverty - asking in each case about the relationship between social justice and space. How, for example, do built-in assumptions about planning reinforce existing distributions of income? Rather than leading him to liberal, technocratic solutions, Harvey's line of inquiry pushes him in the direction of a 'revolutionary geography', one that transcends the structural limitations of existing approaches to space. Harvey's emphasis on rigorous thought and theoretical innovation gives the volume an enduring appeal. This is a book that raises big questions, and for that reason geographers and other social scientists regularly return to it.
Broadband access in the home is a necessity, especially since the COVID-19 pandemic. Increasingly, connectivity is of vital importance for school, work, family, and friends. Existing international research on the implementation of broadband has studied its adoption patterns with a focus on the rural/urban digital divide. This paper explores the digital divide in a case study of the seventh largest city, by population, in the United States; San Antonio is a majority-minority city where over half of the people are Hispanic. This paper focuses on the five key affordability factors that drive broadband adoption. Researchers test social exclusion theory, the structural facets of poverty and social marginality to ascertain its potential impact on broadband access. The authors conducted a survey in both English and Spanish to learn more about the affordability factors that influence the broadband digital divide. Through our analysis, we found evidence that four of the factors (geographical disparities, profit-based discrimination, technology deployment cost, and socio-economic factors) played a role in the digital divide in this case study. The results of this study demonstrate that the digital divide is not exclusively a rural/urban digital divide, but can also occur in an intra-city context. This is especially evident in low-income areas within the city because they have substantially lower broadband adoption rates. The results of this study demonstrate the importance of looking closely at issues of social exclusion of marginalized groups and the affordability of broadband access intra-city.
Across the globe, from established tourist destinations such as Venice or Prague to less traditional destinations in both the global North and South, there is mounting evidence that points to an increasing politicization of the topic of urban tourism. In some cities, residents and other stakeholders take issue with the growth of tourism as such, as well as the negative impacts it has on their cities; while in others, particular forms and effects of tourism are contested or deplored. In numerous settings, contestations revolve less around tourism itself than around broader processes, policies and forces of urban change perceived to threaten the right to ‘stay put’, the quality of life or identity of existing urban populations. This book for the first time looks at urban tourism as a source of contention and dispute and analyses what type of conflicts and contestations have emerged around urban tourism in 16 cities across Europe, North America, South America and Asia. It explores the various ways in which community groups, residents and other actors have responded to – and challenged – tourism development in an international and multi-disciplinary perspective. The title links the largely discrete yet interconnected disciplines of ‘urban studies’ and ‘tourism studies’ and draws on approaches and debates from urban sociology; urban policy and politics; urban geography; urban anthropology; cultural studies; urban design and planning; tourism studies and tourism management. This ground breaking volume offers new insight into the conflicts and struggles generated by urban tourism and will be of interest to students, researchers and academics from the fields of tourism, geography, planning, urban studies, development studies, anthropology, politics and sociology.
There has been a large increase in the number of days per year with numerous EF1-EF5 tornadoes. Given the significant damage incurred by tornadoes upon communities, community resilience analyses for tornado-stricken communities have been gaining momentum. As the community resilience analysis aims to guide how to lay out effective hazard mitigation strategies to decrease damage and improve recovery, a comprehensive and accurate approach is necessary. Agent-based modeling, an analysis approach in which different types of agents are created with their properties and behavior clearly defined to simulate the processes of those agents in an external environment, is the most comprehensive and accurate approach so far to conducting community resilience simulations and investigating the decision-making for mitigation and recovery under natural hazards. In this paper, agent-based models (ABMs) are created to simulate the recovery process of a virtual testbed based on the real-world community in Joplin City, MO. The tornado path associated with the real-world tornado event that occurred in May 2011 is adopted in the tornado hazard modeling for the Joplin testbed. In addition, agent-based models are created for another virtual community in the Midwest United States named Centerville using an assumed tornado scenario of the same EF-scale as that in Joplin. The effects of hazard mitigation strategies on the two communities are also explored. A comparison between the analysis results of these two testbeds can indicate the influence of the characteristics of a tornado-prone community on the resilience of the community as well as on the effects of hazard mitigation strategies. It is observed that a community's level of development significantly impacts the tornado resilience. In addition, the effects of a specific type of hazard mitigation strategy on the recovery process are contingent upon testbed characteristics.
Disasters and engineering, Cities. Urban geography
Mohammed A. Alharthi, Sanda Lenzholzer, João Cortesão
Abstract Cities in hot arid climates are particularly vulnerable to extreme heat, especially during summer. Climate responsive design strategies can support spatial designers (i.e., landscape architects and urban designers) in shaping urban open spaces in hot arid climate regions to ameliorate urban heat, reduce thermal discomfort, and to be more resilient to the impacts of climate change. To gather the necessary knowledge to develop suitable design strategies, a systematic literature review on the topic of climate responsive design in hot arid climates was conducted with this study. This review was carried out using the protocol of the Preferred Reporting Items for Systematic Review Recommendations (PRISMA). From the 2815 studies screened and assessed for eligibility, only 35 were suitable and were analyzed in depth. Among the design strategies found, urban form has been the most investigated while less attention has been given to shading devices, vegetation, water elements and materials. In hot arid climate cities, however, it is essential to provide shade during noon and afternoon hours, allow heat release at night, and allow proper ventilation during day and night. Many design strategies can be also found in vernacular spatial design, but they have been insufficiently (re)discovered. All these design strategies, also in relation to other aspects of climate action, require further research.
Cities. Urban geography, Urban groups. The city. Urban sociology
There are many benefits and costs that come from people and firms clustering together in space. Agglomeration economies, in particular, are the manifestation of centripetal forces that make larger cities disproportionately more wealthy than smaller cities, pulling together individuals and firms in close physical proximity. Measuring agglomeration economies, however, is not easy, and the identification of its causes is still debated. Such association of productivity with size can arise from interactions that are facilitated by cities ("positive externalities"), but also from more productive individuals moving in and sorting into large cities ("self-sorting"). Under certain circumstances, even pure randomness can generate increasing returns to scale. In this chapter, we discuss some of the empirical observations, models, measurement challenges, and open question associated with the phenomenon of agglomeration economies. Furthermore, we discuss the implications of urban complexity theory, and in particular urban scaling, for the literature in agglomeration economies.
Cities worldwide are rapidly adopting smart technologies, transforming urban life. Despite this trend, a universally accepted definition of 'smart city' remains elusive. Past efforts to define it have not yielded a consensus, as evidenced by the numerous definitions in use. In this paper, we endeavored to create a new 'compromise' definition that should resonate with most experts previously involved in defining this concept and aimed to validate one of the existing definitions. We reviewed 60 definitions of smart cities from industry, academia, and various relevant organizations, employing transformer architecture-based generative AI and semantic text analysis to reach this compromise. We proposed a semantic similarity measure as an evaluation technique, which could generally be used to compare different smart city definitions, assessing their uniqueness or resemblance. Our methodology employed generative AI to analyze various existing definitions of smart cities, generating a list of potential new composite definitions. Each of these new definitions was then tested against the pre-existing individual definitions we have gathered, using cosine similarity as our metric. This process identified smart city definitions with the highest average cosine similarity, semantically positioning them as the closest on average to all the 60 individual definitions selected.
Understanding factors driving the recreational utilization of ecological space in urban agglomerations is crucial for the sustainable management of regional systems. However, existing literature focuses on the provision, distribution, and accessibility of urban green space at small scales, lacking explorations into ecological recreational spaces at an urban agglomeration scale. The current study explores the recreational utilization of ecological space in the Pearl River Delta Urban Agglomeration in China by using panel data regression and field investigations from the perspective of urban political ecology. The results show that the forest area proportion, natural reserve area proportion, fiscal revenue, and tourist numbers all have a positive effect on the recreational utilization rate of ecological space; the fixed assets investment exerts unstable prohibitive impacts on the RUoES rate, and the wetland area proportion presents a negative effect on the RUoES rate; land use rights and regional governance structure exacerbate the imbalanced distribution of the rate across different cities. The research contributes to the existing literature by researching urban ecological space from a recreational perspective and at a broader spatial scale, thereby promoting the theoretical integration of recreational geography and political ecology.
Roman Schotten, Evelyn Mühlhofer, Georgios-Alexandros Chatzistefanou
et al.
Natural hazards impact interdependent infrastructure networks that keep modern society functional. While a variety of modelling approaches are available to represent critical infrastructure networks (CINs) on different scales and analyse the impacts of natural hazards, a recurring challenge for all modelling approaches is the availability and accessibility of sufficiently high-quality input and validation data. The resulting data gaps often require modellers to assume specific technical parameters, functional relationships, and system behaviours. In other cases, expert knowledge from one sector is extrapolated to other sectoral structures or even cross-sectorally applied to fill data gaps. The uncertainties introduced by these assumptions and extrapolations and their influence on the quality of modelling outcomes are often poorly understood and difficult to capture, thereby eroding the reliability of these models to guide resilience enhancements. Additionally, ways of overcoming the data availability challenges in CIN modelling, with respect to each modelling purpose, remain an open question. To address these challenges, a generic modelling workflow is derived from existing modelling approaches to examine model definition and validations, as well as the six CIN modelling stages, including mapping of infrastructure assets, quantification of dependencies, assessment of natural hazard impacts, response & recovery, quantification of CI services, and adaptation measures. The data requirements of each stage were systematically defined, and the literature on potential sources was reviewed to enhance data collection and raise awareness of potential pitfalls. The application of the derived workflow funnels into a framework to assess data availability challenges. This is shown through three case studies, taking into account their different modelling purposes: hazard hotspot assessments, hazard risk management, and sectoral adaptation. Based on the three model purpose types provided, a framework is suggested to explore the implications of data scarcity for certain data types, as well as their reasons and consequences for CIN model reliability. Finally, a discussion on overcoming the challenges of data scarcity is presented.
Disasters and engineering, Cities. Urban geography
Simon Scheider, Harm Bartholomeus, Judith Verstegen
The recent success of large language models and AI chatbots such as ChatGPT in various knowledge domains has a severe impact on teaching and learning Geography and GIScience. The underlying revolution is often compared to the introduction of pocket calculators, suggesting analogous adaptations that prioritize higher-level skills over other learning content. However, using ChatGPT can be fraudulent because it threatens the validity of assessments. The success of such a strategy therefore rests on the assumption that lower-level learning goals are substitutable by AI, and supervision and assessments can be refocused on higher-level goals. Based on a preliminary survey on ChatGPT's quality in answering questions in Geography and GIScience, we demonstrate that this assumption might be fairly naive, and effective control in assessments and supervision is required.
Uche Abamba Osakede, Victor Olufemi Aramide, Aderonke Esther Adesipo
et al.
Gender inequality is high in Africa compared to other regions of the world. This disparity jeopardises the efforts targeted at improving human development and economic growth in the continent. This study provides empirical evidence on the drivers of human development in Africa across gender and country income groups, covering 54 countries over the period 1990 to 2019. It employed the Mean Group estimator for analysis to accommodate slope heterogeneity and cross-sectional dependence. The paper used Human Development Index (HDI) to proxy human development, while HDI across gender was employed to capture gender differences in human development. Country income grouping followed the World Bank country classification into low, lower-middle and upper-middle-income economies. The findings showed more determinants of HDI when disaggregated across gender than otherwise. The drivers of HDI are similar across gender for each country income group, with infrastructure, particularly ICT shown to have a positive effect in the long run for all country groups. For lower-middle and upper-middle income countries, fertility rate induced a significant negative effect on HDI and gender human development but only in the long run. However, the effect was insignificant for male and female HDI in low-income countries. Moreover, an increase in real Gross Domestic Product (GDP) promotes human development regardless of a country's income classification. A larger positive effect of GDP was observed on the HDI for low-income countries. Therefore, in the bid to improve human development in Africa, efforts should continually be intensified towards promoting GDP growth regardless of the level of growth in macroeconomic income. Policies targeted at reducing fertility rates and increasing ICT are also encouraged as these will improve HDI and close the gap in HDI across gender.
Cities. Urban geography, Urbanization. City and country