Guo-Shiuan Lin, Denise Hertwig, Megan McGrory
et al.
Cities host most of the world population with diverse services and activities. One key challenge in urban modelling is the quantification of intra- and inter-city mobility patterns and the associated space-time dynamics of population density and anthropogenic activities. To address this, we apply the novel agent-based urban model DAVE (Dynamic Anthropogenic actiVities and feedback to Emissions) to simulate population behaviour and mobility in the Vaud and Geneva Cantons, a system of small- to medium-size cities in Switzerland. Simulation results provide detailed temporal (10 min) and spatial (500 m) population dynamics for different age groups and day types. DAVE further models the time-varying population distribution in 11 different microenvironments (e.g., home, work, leisure, outdoor) and the travel flows by different modes. Simulation results align with observations, confirming the possibility of driving urban system modelling with statistical information on residents' behaviour. Sustainability and health indicators like daily driving distance and walking time for each neighbourhood are also reflected by the model with urban-rural gradients displayed. This work serves as a foundation for future applications of DAVE to study bottom-up human-built environment interactions, from anthropogenic emissions and building energy to urban climate, exposure, and health in cities around the world.
César Vega Zárate, Iris Adriana Landa Torres, Diana Donají Del Callejo Canal
et al.
El Programa Pueblos Mágicos en México busca detonar el desarrollo local. Este artículo busca identificar si existe relación entre los presupuestos asignados a 89 pueblos mágicos en el periodo 2013-2016 y la promoción del crecimiento de espacios turísticos, aplicando un método de panel balanceado, un modelo de pooling y uno de efectos fijos. Los resultados explican que 72% de los pueblos mágicos tuvieron un incremento de hoteles construidos; sin embargo, los modelos de pooling y de efectos fijos establecieron que el presupuesto solo explica 13% del incremento, lo que implica que también influyen otros componentes de la capacidad institucional.
Cities. Urban geography, Urban groups. The city. Urban sociology
Berdiansk is a Ukrainian city on the Azov Sea shore in Zaporizhzhia Oblast. With almost 200 years of colonial history, this city currently living under Russian occupation is an excellent fit for analysing the memory transformation process in the communities of southeastern Ukraine. This paper examines the memory politics background in the southeast of Ukraine as exemplified by the changes in symbolism across Berdiansk’s city space on the back of post-Maidan politics. In addition, it describes and discusses the transformation of memory sites under occupation and imagines potential commemoration frameworks for the liberated Berdiansk. The considerations for symbolical transformations in Berdiansk draw on the Content Analysis method. Some data comes from the interview with the Research Institute of Urban History Director, Prof. Victoria Konstantinova, who helped implement decommunisation laws. While analysing the relations between Ukrainian memory politics and Russian colonial policy, the author used de/postcolonial optics.
Cities. Urban geography, Economic history and conditions
The evolution of urban landscapes is rapidly altering the surface of our planet. Yet, our understanding of the urbanisation phenomenon remains far from complete. A fundamental challenge is to describe spatiotemporal changes in the built environment. A dynamic theory of urban evolution should account for both vertical and horizontal city expansion, analogous to the dynamical behaviour of surface growth in physical and biological systems. Here we show that building-height dynamics in cities around the world are well described by a zero-dimensional geometric Brownian motion (GBM), where multiplicative noise drives stochastic fluctuations around a deterministic drift associated with economic growth. To account for intra-city correlations, we extend the GBM with spatial coupling, revealing how local interactions effectively mitigate noise-driven fluctuations and shape urban morphology. The continuum limit of this spatial model can be recasted into the Kardar-Parisi-Zhang (KPZ) equation and we find that empirical estimates of the roughness exponent are in the range of the KPZ prediction for most cities. Together, these results show that multiplicative noise, moderated by local interactions, governs the evolution of urban roughness, anchoring spatiotemporal city dynamics in a well-established statistical physics framework.
Joanderson Fernandes Simões, Larícia Gomes Soares, Daniel Carlos Alves Santos
No desenvolvimento histórico da geografia física, diferentes autores contribuíram para o avanço metodológico de apreensão da realidade nesse campo científico. No contexto brasileiro, um dos principais expoentes foi Tricart (1977) através de sua classificação em unidades ecodinâmicas: meios estáveis, intergrades e fortemente instáveis. A partir disso, objetiva-se com esse artigo compreender as contribuições desse autor para a geografia física brasileira, a partir de sua obra Ecodinâmica. A partir da classificação morfodinâmica de Tricart (1977), verifica-se que as contribuições deste são deveras significativas e influentes para os estudos em Geografia Física, sobretudo no tocante às pesquisas abordando sistemas como meios físicos apresentando relações integradas, onde a paisagem é caracterizada por seu dinamismo e influências mútuas entre os elementos.
Md. Shahinoor Rahman, Kamal Chandra Paul, Md. Mokhlesur Rahman
et al.
Cities become mission-critical zones during pandemics and it is vital to develop a better understanding of the factors that are associated with infection levels. The COVID-19 pandemic has impacted many cities severely; however, there is significant variance in its impact across cities. Pandemic infection levels are associated with inherent features of cities (e.g., population size, density, mobility patterns, socioeconomic condition, and health environment), which need to be better understood. Intuitively, the infection levels are expected to be higher in big urban agglomerations, but the measurable influence of a specific urban feature is unclear. The present study examines 41 variables and their potential influence on COVID-19 cases and fatalities. The study uses a multi-method approach to study the influence of variables, classified as demographic, socioeconomic, mobility and connectivity, urban form and density, and health and environment dimensions. This study develops an index dubbed the PVI-CI for classifying the pandemic vulnerability levels of cities, grouping them into five vulnerability classes, from very high to very low. Furthermore, clustering and outlier analysis provides insights on the spatial clustering of cities with high and low vulnerability scores. This study provides strategic insights into levels of influence of key variables upon the spread of infections as well as fatalities, along with an objective ranking for the vulnerability of cities. Thus it provides critical wisdom needed for urban healthcare policy and resource management. The pandemic vulnerability index calculation method and the process present a blueprint for the development of similar indices for cities in other countries, leading to a better understanding and improved pandemic management for urban areas and post-pandemic urban planning across the world.
Städte sind Zentren der sozialen, kulturellen, wirtschaftlichen und materiellen Vielfalt, in denen Menschen in unterschiedlichsten Lebenslagen im dicht besiedelten Raum aufeinandertreffen und sich soziale Ungleichheiten bzw. Disparitäten durch die räumliche Konzentration von Bevölkerungsgruppen
manifestieren und verstärken können. Durch die Zunahme innerstädtischer Disparitäten haben zahlreiche deutschsprachige (Groß-)Städte begonnen, kleinräumige Sozialraumberichterstattungen aufzubauen, um der räumlichen Konzentration von sozialen Problemlagen frühzeitig entgegenwirken zu können. In diesem Beitrag werden die unterschiedlichen
methodisch-konzeptionellen Herangehensweisen bei quantitativen Sozialraumanalysen in 25 deutschsprachigen (Groß-)Städten mit vergleichbarem Datenmaterial systematisch analysiert und diskutiert. Dabei sind für diese Metaanalyse die systematische Gegenüberstellung der Motivationen, Ziele und inhaltlichen Fragestellungen sowie die dafür verwendeten Indikatoren, räumlichen Analyseebenen und methodischen Herangehensweisen von Interesse. Der Erkenntnisgewinn kann für Stadt- und Regionalverwaltungen von Relevanz bei der (Neu-)Konzeption und Durchführung eigener Sozialraumanalysen sein.
Cities. Urban geography, Urbanization. City and country
This research builds a dynamic model of the global economy and climate with three endogenous knowledge stocks. We confirm that the contribution of induced R&D in global climate change is shown to be very sensitive to the elasticity of substitution between energy and other factors of production since growth patterns of all types of research depend on whether inputs are gross complements or gross substitutes. The second, the duplication externality. Induced R&D generates a lower abatement cost reduction if we externalize duplication in the business as usual scenario. Third, the initial level of research expenditure. Higher initial levels of energy-related R&D shares would create a market size effect, leading to an increased contribution of induced R&D. Fourth, the inter-firm knowledge spillovers. Firms are not successful in capturing all the benefits they create, as many benefits flow out into other firms free of charge. These benefits are called inter-firm knowledge spillovers. Fifth, first-best and second-best policies. The first-best policy fully internalizes the inter-firm knowledge spillovers, which leads to increases in the levels of all types of research, whereas the second-best policy does not internalize it, which leads to induced changes in research resulting from the carbon tax affecting pre-existing market distortions. Sixth, a research dividend effect and tax burden effect. The tax may induce an increase in research expenditure, which would increase the welfare and consumption levels. Finally, the results demonstrated that induced R&D has a limited role in the abatement cost reduction of carbon emissions overall.
Cities. Urban geography, Urbanization. City and country
Erich Wolff, Matthew French, Noor Ilhamsyah
et al.
Concerns regarding the impacts of climate change on marginalised communities in the Global South have led to calls for affected communities to be more active as agents in the process of planning for climate change. While the value of involving communities in risk management is increasingly accepted, the development of appropriate tools to support community engagement in flood risk management projects remains nascent. Using the Revitalising Informal Settlements and their Environment (RISE) Program as a case study, the article interrogates the potential of citizen science to include disadvantaged urban communities in project-level flood risk reduction planning processes. This project collected more than 5000 photos taken by 26 community members living in 13 informal settlements in Fiji and Indonesia between 2018 and 2020. The case study documents the method used as well as the results achieved within this 2-year project. It discusses the method developed and implemented, outlines the main results, and provides lessons learned for others embarking on citizen science environmental monitoring projects. The case study indicates that the engagement model and the technology used were key to the success of the flood-monitoring project. The experiences with the practice of monitoring floods in collaboration with communities in Fiji and Indonesia provide insights into how similar projects could advance more participatory risk management practices. The article identifies how this kind of approach can collect valuable flood data while also promoting opportunities for local communities to be heard in the arena of risk reduction and climate change adaptation.
We propose hypotheses describing the empirical finding of an association between the exponents of urban GDP scaling and Zipf's law for cities. These hypotheses represent various combinations of directional or reciprocal causal links between the two phenomena and include inter- and intra-city processes. Future theories and models can be motivated with and categorized according to these hypotheses. This paper intends to stimulate the discussion around the processes behind these phenomena and pave the way to a Unified Urban Theory.
This paper evaluates the significant factors contributing to environmental awareness among individuals living in the urban area of Sylhet, Bangladesh. Ordered Probit(OPM) estimation is applied on the value of ten measures of individual environmental concern. The estimated results of OPM reveal the dominance of higher education, higher income, and full-employment status on environmental concern and environmentally responsible behavior. Younger and more educated respondents tended to be more knowledgeable and concerned than older and less educated respondents. The marginal effect of household size, middle-income level income, and part-time employment status of the survey respondents played a less significant role in the degree of environmental awareness. Findings also validate the "age hypothesis" proposed by Van Liere and Dunlap (1980), and the gender effect reveals an insignificant role in determining the degree of environmental concern. Environmental awareness among urban individuals with higher income increased linearly with environmental awareness programs which may have significant policy importance, such as environmental awareness programs for old-aged and less-educated individuals, and may lead to increased taxation on higher income groups to mitigate city areas' pollution problems.
Urban morphology and socioeconomic aspects of cities have been explored by analysing urban street network. To analyse the network, several variations of the centrality indices are often used. However, its nature has not yet been widely studied, thus leading to an absence of robust visualisation method of urban road network characteristics. To fill this gap, we propose to use a set of local betweenness centrality and a new simple and robust visualisation method. By analysing 30 European cities, we found that our method illustrates common structures of the cities: road segments important for long-distance transportations are concentrated along larger streets while those for short range transportations form clusters around CBD, historical, or residential districts. Quantitative analysis has corroborated these findings. Our findings are useful for urban planners and decision-makers to understand the current situation of the city and make informed decisions.
Seen from a satellite, observing land use in the daytime or at night, most cities have circular shapes, organised around a city centre. A radial analysis of artificial land use growth is conducted in order to understand what the recent changes in urbanisation are across Europe and how it relates to city size. We focus on the most fundamental differentiation regarding urban land use: has it been artificialised for human uses (residence or roads for instance) or is it natural, or at least undeveloped? Using spatially detailed data from the EU Copernicus Urban Atlas, profiles of artificial land use (ALU) are calculated and compared between two years, 2006 and 2012. Based on the homothety of urban forms found by Lemoy and Caruso (2018), a simple scaling law is used to compare the internal structure of cities after controlling for population size. We firstly show that when using the FUA definition of cities, a kind of Gibrat's law for land use appears to hold. However, when we examine cities internally, this is no longer clear as there are differences on average between city size categories. We also look at further city groupings using regions and topography to show that artificial land use growth across European cities is not homogeneous. Our findings have important implications relative to the sustainability of cities as this evidence is pointing towards increasing urban sprawl and stagnant growth in urban centres across cities of all sizes. It also has theoretical implications on the nature of sprawl and its scaling with city size.
Entropy is one of physical bases for fractal dimension definition, and the generalized fractal dimension was defined by Renyi entropy. Using fractal dimension, we can describe urban growth and form and characterize spatial complexity. A number of fractal models and measurements have been proposed for urban studies. However, the precondition for fractal dimension application is to find scaling relations in cities. In absence of scaling property, we can make use of entropy function and measurements. This paper is devoted to researching how to describe urban growth by using spatial entropy. By analogy with fractal dimension growth models of cities, a pair of entropy increase models can be derived and a set of entropy-based measurements can be constructed to describe urban growing process and patterns. First, logistic function and Boltzmann equation are utilized to model the entropy increase curves of urban growth. Second, a series of indexes based on spatial entropy are used to characterize urban form. Further, multifractal dimension spectrums are generalized to spatial entropy spectrums. Conclusions are drawn as follows. Entropy and fractal dimension have both intersection and different spheres of application to urban research. Thus, for a given spatial measurement scale, fractal dimension can often be replaced by spatial entropy for simplicity. The models and measurements presented in this work are significant for integrating entropy and fractal dimension into the same framework of urban spatial analysis and understanding spatial complexity of cities.
Daniel Rhoads, Albert Solé-Ribalta, Marta C. González
et al.
In the wake of the pandemic, the inadequacy of urban sidewalks to comply with social distancing remains untackled in academy. Beyond isolated efforts (from sidewalk widenings to car-free Open Streets), there is a need for a large-scale and quantitative strategy for cities to handle the challenges that COVID-19 poses in the use of public space. The main obstacle is a generalized lack of publicly available data on sidewalk infrastructure worldwide, and thus city governments have not yet benefited from a complex systems approach of treating urban sidewalks as networks. Here, we leverage sidewalk geometries from ten cities in three continents, to first analyze sidewalk and roadbed geometries, and find that cities most often present an arrogant distribution of public space: imbalanced and unfair with respect to pedestrians. Then, we connect these geometries to build a sidewalk network --adjacent, but not assimilable to road networks, so fertile in urban science. In a no-intervention scenario, we apply percolation theory to examine whether the sidewalk infrastructure in cities can withstand the tight pandemic social distancing imposed on our streets. The resulting collapse of sidewalk networks, often at widths below three meters, calls for a cautious strategy, taking into account the interdependencies between a city's sidewalk and road networks, as any improvement for pedestrians comes at a cost for motor transport. With notable success, we propose a shared-effort heuristic that delays the sidewalk connectivity breakdown, while preserving the road network's functionality.
Kerry A. Nice, Jason Thompson, Jasper S. Wijnands
et al.
The confluence of recent advances in availability of geospatial information, computing power, and artificial intelligence offers new opportunities to understand how and where our cities differ or are alike. Departing from a traditional `top-down' analysis of urban design features, this project analyses millions of images of urban form (consisting of street view, satellite imagery, and street maps) to find shared characteristics. A (novel) neural network-based framework is trained with imagery from the largest 1692 cities in the world and the resulting models are used to compare within-city locations from Melbourne and Sydney to determine the closest connections between these areas and their international comparators. This work demonstrates a new, consistent, and objective method to begin to understand the relationship between cities and their health, transport, and environmental consequences of their design. The results show specific advantages and disadvantages using each type of imagery. Neural networks trained with map imagery will be highly influenced by the mix of roads, public transport, and green and blue space as well as the structure of these elements. The colours of natural and built features stand out as dominant characteristics in satellite imagery. The use of street view imagery will emphasise the features of a human scaled visual geography of streetscapes. Finally, and perhaps most importantly, this research also answers the age-old question, ``Is there really a `Paris-end' to your city?''.