Hasil untuk "Urbanization. City and country"

Ulysse Marquis, Marc Barthelemy

Urban scaling laws describe how an urban quantity $Y$ varies with city population $P$, typically as $Y \sim P^β$. These relations are usually obtained from cross-sectional comparisons across cities at a given time (transversal scaling), but their link to the temporal evolution of individual cities (longitudinal scaling) remains unclear. Here we derive explicit expressions for the transversal exponent from the longitudinal dynamics of cities. We show that the measured exponent does not directly reflect individual city dynamics, but instead arises from a snapshot of a heterogeneous ensemble of cities with distinct growth trajectories. As a result, transversal scaling combines intrinsic dynamics with statistical effects due to the distribution of city sizes and correlations between population and city-specific parameters. Consequently, cross-sectional scaling laws cannot, in general, be used to infer the dynamics of individual cities. In particular, apparent sub- or superlinear scaling can emerge even when all cities follow linear longitudinal dynamics, as we demonstrate for the area-population relation. Strikingly, the behavior associated with the transversal exponent is in general not observed in the trajectory of any individual city, underscoring its collective, rather than dynamical, nature. More broadly, the transversal exponent has a clear dynamical meaning only under restrictive conditions-when cities behave as scaled versions of one another and path dependence is weak. Outside of these limits, it is not a law of urban growth, but a statistical artefact of heterogeneity.

Chonghua Han, Yuan Yuan, Yukun Liu et al.

Human mobility prediction is vital for urban planning, transportation optimization, and personalized services. However, the inherent randomness, non-uniform time intervals, and complex patterns of human mobility, compounded by the heterogeneity introduced by varying city structures, infrastructure, and population densities, present significant challenges in modeling. Existing solutions often require training separate models for each city due to distinct spatial representations and geographic coverage. In this paper, we propose UniMove, a unified model for multi-city human mobility prediction, addressing two challenges: (1) constructing universal spatial representations for effective token sharing across cities, and (2) modeling heterogeneous mobility patterns from varying city characteristics. We propose a trajectory-location dual-tower architecture, with a location tower for universal spatial encoding and a trajectory tower for sequential mobility modeling. We also design MoE Transformer blocks to adaptively select experts to handle diverse movement patterns. Extensive experiments across multiple datasets from diverse cities demonstrate that UniMove truly embodies the essence of a unified model. By enabling joint training on multi-city data with mutual data enhancement, it significantly improves mobility prediction accuracy by over 10.2\%. UniMove represents a key advancement toward realizing a true foundational model with a unified architecture for human mobility. We release the implementation at https://github.com/tsinghua-fib-lab/UniMove/.

Zongqi Wang, Lufeng Zhang

Abstract In the context of China’s ongoing territorial spatial planning reform, establishing a scientifically sound and practically effective marine spatial planning (MSP) system is essential for advancing land–sea integration. Anchored in systematic policy research, this study reviews the development trajectory of China’s MSP system since the 1980s, identifies the structural conflicts embedded within its framework, and proposes forward-looking perspectives derived from the evolution of China’s coastal spatial governance. The study traces the institutional establishment and implementation of six major types of marine plans that constitute the core of China’s MSP framework and provides a diachronic account of their development trajectories. The underpinning institutional reforms reflect the distinct developmental phases of MSP, demonstrating an evolution toward coordinated governance. A comparative analysis of the plans in terms of planning hierarchy, duration, spatial scope, zoning units, and classification systems identifies three persistent challenges: fragmented and administration-centered zoning standards, insufficient integration between marine and terrestrial planning systems, and incomplete technical standards. Drawing on the evolution of China’s coastal spatial governance, the paper concludes with policy insights emphasizing three strategic pathways—technical enhancement, legislative consolidation, and institutional innovation—to strengthen the coherence and adaptability of China’s marine spatial governance system.

Jennifer Gerend, Marina Beck

The perspectives of municipal representatives and property owners in three rural communities in Bavaria are the subject of this paper on property and infill development. The results of a survey were assigned to four spatially coded settlement types: historic town centres, post-World-War II settlement types, settlements from the 1980s and 1990s, and new developments after 2000. There were considerable differences between these settlement types in many of the responses: The responses from the newer settlements showed a more individualistic attitude than the respondents in the town centres. For example, vacant lots between buildings are often reserved as plots for grandchildren, others serve as green spaces. Little interest in selling is reported. This paper therefore recommends providing tailored support and incentives that take into account the social aspects of land ownership (including long-term lease options, land swaps, or swaps for units in a new building on the site). The results also show that many vacant lots are perceived in the neighbourhood as welcome green spaces. Therefore, administrations should focus more on planning green spaces in small rural communities and re-evaluating existing properties as potential public green spaces.

Emmanuel Brobbey, Ebenezer Boateng, Bernice Nkrumah Boadu et al.

Emerging nations have faced significant external shocks in recent years, resulting in increased economic policy uncertainty and geopolitical risk to their growth trajectories. Similarly, emerging economies in Europe are susceptible to global shocks; however, these shocks tend to have a more pronounced impact on prices and output which may vary across time and frequency. This underscores the need for a deeper analysis through time and frequency of the growth-inflation nexus in response to global shocks highlighting the study’s unique contribution. Hence, we examined the dynamic conditional impact of two global risk factors as uncertainty indices amid inflation (CPI) and economic growth (GDP) in the context of four selected emerging European nations. These countries included Czech Republic, Greece, Hungary, and Russia. Two uncertainty indicators − Global Economic Policy Uncertainty (GEPU) and Geopolitical Risk (GPR) were utilized. The bi-wavelet approach was employed to examine the nexus between CPI and GDP, whereas the partial wavelet technique was used to decipher the co-movement between CPI and GDP relative to the global risk factors. We found low positive co-movements between inflation and economic growth in the short-term. Conversely, we observed no lead-lag nexus in the long-term confirming the natural rate hypothesis. The results of the partial wavelet divulged the protracted and substantial influence of GEPU on the co-movements between GDP and CPI except for Russia. The time-varying perspective was confirmed by the DCC-GARCH time-varying connectedness approach as robustness. The country-specific variables as well as the global risk factors are highly connected in crisis episodes implying contagion effects. The economic growth indicator revealed a consistent net receiving role whereas GEPU and GPR were significant net transmitters. This explicates that the economic growth of these emerging economies is responsive to GEPU and GPR shocks.

Tonia Stiuso

Starting from the relationship between urban planning and mobility management, TeMA has gradually expanded the view of the covered topics, always remaining in the groove of rigorous scientific in-depth analysis. This section of the Journal, Review Notes, is the expression of continuously updating emerging topics concerning relationships between urban planning, mobility, and environment, through a collection of short scientific papers written by young researchers. The Review Notes are made of five parts. Each section examines a specific aspect of the broader information storage within the main interests of TeMA Journal. In particular, the Urban planning literature review section presents recent books and journals on selected topics and issues within the global scientific panorama. For the second issue of TeMA Journal volume no. 18, this section provides a comprehensive overview of the challenges and solutions related to the role of open and green spaces in climate change adaptation, with particular attention to the urban flooding risks. Using a variety of scientific sources and practical resources, this contribution aims to identify the key characteristics of these spaces that can influence adaptation strategies, examining the solutions proposed in the scientific literature, specifically in books, journals, and reports.

Wenjing Han, Xiaoling Zhang, Xian Zheng

Land use regulation has always been regarded as one of the most crucial means of macro-control of urban growth, which can affect a city’s land values directly and further determine related urban economic well-being. Since the New Type Urbanization Strategy proposed by the government in 2014, China’s mode of urban growth has been transformed from addressing “quantity” to “quality" in the urbanization process. In this case, the regulation of land use by the Chinese government plays a more important role in urban growth. With their planned land regulatory scheme, the various instruments employed by Chinese governments have quite different mechanisms influencing land prices. However, there are no rigorous studies focusing on the land use regulation system and its impact on land values to date, particular in China. This study seeks to explore how land use regulation affects urban land values through the systematic lens. We summarize the main land use regulatory instruments based on the analysis of China’s planned land use system and urban land banking system, including the construction land quota, constraints on the allowed floor area ratio (FAR) of each land transaction parcel, and land supply restrictions. A new dataset based on land transaction data from 2007 to 2016 that covers 286 prefectural cities from the country’s coastal, central, and western regions is used in the empirical analysis. The results show that the effects of the floor area ratio (FAR) on land values are significant and positive, with the residential and commercial land supply ratio being a key factor. Moreover, the results imply that the effects of constraints on FAR and commercial land supply vary between regions. These findings indicate that the Chinese land market is considerably distorted by excessive administrative interventions by local governments, in the stage of urban transition guided, the capable regulatory instruments could play an important role in adjusting urban land prices and hence impact on urban growth.

Mohamed R. Ibrahim, Terry Lyons

Air pollution in cities, especially NO\textsubscript{2}, is linked to numerous health problems, ranging from mortality to mental health challenges and attention deficits in children. While cities globally have initiated policies to curtail emissions, real-time monitoring remains challenging due to limited environmental sensors and their inconsistent distribution. This gap hinders the creation of adaptive urban policies that respond to the sequence of events and daily activities affecting pollution in cities. Here, we demonstrate how city CCTV cameras can act as a pseudo-NO\textsubscript{2} sensors. Using a predictive graph deep model, we utilised traffic flow from London's cameras in addition to environmental and spatial factors, generating NO\textsubscript{2} predictions from over 133 million frames. Our analysis of London's mobility patterns unveiled critical spatiotemporal connections, showing how specific traffic patterns affect NO\textsubscript{2} levels, sometimes with temporal lags of up to 6 hours. For instance, if trucks only drive at night, their effects on NO\textsubscript{2} levels are most likely to be seen in the morning when people commute. These findings cast doubt on the efficacy of some of the urban policies currently being implemented to reduce pollution. By leveraging existing camera infrastructure and our introduced methods, city planners and policymakers could cost-effectively monitor and mitigate the impact of NO\textsubscript{2} and other pollutants.

Li Yang, Zhipeng Luo, Shiming Zhang et al.

With the digitization of modern cities, large data volumes and powerful computational resources facilitate the rapid update of intelligent models deployed in smart cities. Continual learning (CL) is a novel machine learning paradigm that constantly updates models to adapt to changing environments, where the learning tasks, data, and distributions can vary over time. Our survey provides a comprehensive review of continual learning methods that are widely used in smart city development. The content consists of three parts: 1) Methodology-wise. We categorize a large number of basic CL methods and advanced CL frameworks in combination with other learning paradigms including graph learning, spatial-temporal learning, multi-modal learning, and federated learning. 2) Application-wise. We present numerous CL applications covering transportation, environment, public health, safety, networks, and associated datasets related to urban computing. 3) Challenges. We discuss current problems and challenges and envision several promising research directions. We believe this survey can help relevant researchers quickly familiarize themselves with the current state of continual learning research used in smart city development and direct them to future research trends.

M. Marzouk, A. A. Othman

Abstract Rapid urbanization is one of the present characteristics in both developed and developing countries. It is projected that by 2050 around 68 % of the world’s population shall live in urban areas. As a result, many city development initiatives are proposed by various research centers or through academia to aid in managing the process. One of the most evolving concepts through the past two decades is Smart Cities. The concept of smart cities has been defined and formulated by many research efforts and organizations. However, most of these definitions and initiatives focus on the operation stage of the city. This paper proposes an inclusive framework for integrating Building Information Modeling (BIM) and Geographical Information System (GIS) to plan and forecast the utility infrastructure needs for expanding and emerging cities to highlight the concept of “smartness” during the planning stage. The considered infrastructure needs are freshwater consumption, sewage capacity and electrical energy requirements. Firstly, the city is broken down into several districts, lands and plots. Afterwards, through the assignment of relevant land use, building type information and various other information, an interactive tool is originated to allow for the formulation of different city development schemes and the representation of their respective resulting infrastructure needs. The framework is targeted to be flexible enough in order to be applied to any city, not just a single case as smart city solutions need to adopt to diverse cities’ needs. The proposed framework is advocated to enforce the concept of both smart and sustainable cities by taking a closer look at the city’s planning and development stages and infrastructure requirements which shape a sizable part of the city’s performance throughout its expansion and development. It can also serve as a decision support tool for better planning and management of smart city infrastructure requirements. Finally, a case study is represented to demonstrate the practical features of the proposed framework.

A. Janik, Adam Ryszko, Marek Szafraniec

The smart sustainable city (SSC) is a concept created in response to problems and challenges arising from rapid urbanization. This is a relatively new term that is developing dynamically, which is confirmed by the growing number of publications over recent years. For this reason, this article presented an up-to-date comprehensive bibliometric analysis to describe and assess the scientific landscape of smart and sustainable cities literature. The analysis was based on two bibliographic sources—the Web of Science Core Collection and the Scopus database. It covers publications on the SSC, as well as documents describing the smart city (SC) and the sustainable city (SuC) concepts separately. VOSviewer and Biblioshiny were selected as software tools for the bibliometric analysis. Based on the descriptive bibliometric analysis, quantity and quality indicators were determined separately for the SC, SuC, and SSC concepts, while the network analysis mapped and covered the level of multi-faceted scientific cooperation in the field of the SSC research. The analysis results were intended to familiarize scholars and practitioners with the most prolific authors, sources, institutions, and countries in the analyzed scientific field, to identify the most influential research channels and impact from authors, sources, countries, and research topics, to determine major clusters of the SSC research and also to provide valuable information for further investigation.

Guangdong Li, Feng Li

China's unprecedented urbanization has resulted in accelerating urban sprawl, which is threatening the country's eco-environmental quality and socioeconomic sustainability. In this study, we integrated urban land census data and urban district population data to examine the pattern of urban sprawl and identify differences, and to investigate the socioeconomic drivers of urban sprawl in China between 2006 and 2014. The results revealed that China has experienced drastic urban sprawl over almost all of the last decade with an average urban sprawl index (USI) of 3.16%. However, the rate of urban sprawl has decreased since 2010. In addition, regional distribution, urban size, and hierarchy have different effects on urban sprawl. In particular, cities with severe urban sprawl should be noted, such as large and medium cities in eastern China, large cities in central China, small-A and large-B cities in western China, and large-A cities in northeast China. We also found that urban sprawl was significantly associated with urban population density, gross domestic product (GDP) per capita, and industrial structure. Further, when the spatial heterogeneity was considered, the driving forces of urban sprawl exhibited different magnitudes and directions. Our results indicate that to formulate effective urban planning and land use policies, decision-makers should seriously consider the differences in urban sprawl depending on region, urban size, and hierarchy.

Qinglong Ding, Yang Chen, L. Bu et al.

The past decades were witnessing unprecedented habitat degradation across the globe. It thus is of great significance to investigate the impacts of land use change on habitat quality in the context of rapid urbanization, particularly in developing countries. However, rare studies were conducted to predict the spatiotemporal distribution of habitat quality under multiple future land use scenarios. In this paper, we established a framework by coupling the future land use simulation (FLUS) model with the Intergrated Valuation of Environmental Services and Tradeoffs (InVEST) model. We then analyzed the habitat quality change in Dongying City in 2030 under four scenarios: business as usual (BAU), fast cultivated land expansion scenario (FCLE), ecological security scenario (ES) and sustainable development scenario (SD). We found that the land use change in Dongying City, driven by urbanization and agricultural reclamation, was mainly characterized by the transfer of cultivated land, construction land and unused land; the area of unused land was significantly reduced. While the habitat quality in Dongying City showed a degradative trend from 2009 to 2017, it will be improved from 2017 to 2030 under four scenarios. The high-quality habitat will be mainly distributed in the Yellow River Estuary and coastal areas, and the areas with low-quality habitat will be concentrated in the central and southern regions. Multi-scenario analysis shows that the SD will have the highest habitat quality, while the BAU scenario will have the lowest. It is interesting that the ES scenario fails to have the highest capacity to protect habitat quality, which may be related to the excessive saline alkali land. Appropriate reclamation of the unused land is conducive to cultivated land protection and food security, but also improving the habitat quality and giving play to the versatility and multidimensional value of the agricultural landscape. This shows that the SD of comprehensive coordination of urban development, agricultural development and ecological protection is an effective way to maintain the habitat quality and biodiversity.

Guru Chythanya Guptha, Sabyasachi Swain, N. Al‐Ansari et al.

Abstract: The increasing number of pluvial floods due to extreme climatic events or poor maintenance of the drainage networks urge for assessing the performance of the urban drainage system (UDS). This paper presents a comprehensive evaluation of the UDS of Gurugram City, India. While the limited availability of sub-hourly precipitation and finer resolution geospatial data pose major challenges in the detailed analyses through Storm Water Management Model (SWMM), it was circumvented by utilizing the high-resolution remotely sensed datasets viz., IMERG (half-hourly precipitation data from 2000 to 2019), ALOS PALSAR (Digital Elevation Model) and Sentinel-2 (land use/land cover). Functional failure scenarios (i.e., the combinations of climate change and urbanization) were simulated to assess the impacts on the resilience of the UDS. The modelling results showed that individually, climate change would impose a more serious threat than urbanization, whereas their combinations would significantly hamper the resilience of the UDS. The structural failure (only single link-failure) scenarios were analyzed, and 11 out of 25 conduits were identified to be non-resilient. The study highlights the importance of the readily available remote sensing datasets, which fill the gap of non-availability of ground-based datasets at desirable resolutions, especially in developing countries.

Ángela Abascal, Natalie Rothwell, Adenike Shonowo et al.

The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, statistics and data (e.g., local monitoring of Sustainable Development Goals - SDGs) are hindered by the unavailability of spatial data at metropolitan, city and sub-city scales. Deprivation is a complex and multidimensional concept, which has been captured in existing literature with a strong focus on household-level deprivation while giving limited attention to area-level deprivation. Within this scoping review, we build on existing literature on household- as well as area-level deprivation frameworks to arrive at a combined understanding of how urban deprivation is defined with a focus on LMIC cities. The scoping review was enriched with local stakeholder workshops in LMIC cities to arrive at our framework of Domains of Deprivations, splitting deprivation into three different scales and nine domains. (1) Socio-Economic Status and (2) Housing Domains (Household scale); (3) Social Hazards & Assets, (4) Physical Hazards & Assets, (5) Unplanned Urbanization and (6) Contamination (Within Area scale); and (7) Infrastructure, (8) Facilities & Services and (9) city Governance (Area Connect scale). The Domains of Deprivation framework provides a clear guidance for collecting data on various aspects of deprivation, while providing the flexibility to decide at city level which indicators are most relevant to explain individual domains. The framework provides a conceptual and operational base for the Integrated Deprived Area Mapping System (IDEAMAPS) Project for the creation of a data ecosystem, which facilitates the production of routine, accurate maps of deprived “slum” areas at scale across cities in LMICs. The Domains of Deprivation Framework is designed to support diverse health, poverty, and development initiatives globally to characterize and address deprivation in LMIC cities.

Wenhui Peng, Shaoxiang Qin, Senwen Yang et al.

Global urbanization has underscored the significance of urban microclimates for human comfort, health, and building/urban energy efficiency. They profoundly influence building design and urban planning as major environmental impacts. Understanding local microclimates is essential for cities to prepare for climate change and effectively implement resilience measures. However, analyzing urban microclimates requires considering a complex array of outdoor parameters within computational domains at the city scale over a longer period than indoors. As a result, numerical methods like Computational Fluid Dynamics (CFD) become computationally expensive when evaluating the impact of urban microclimates. The rise of deep learning techniques has opened new opportunities for accelerating the modeling of complex non-linear interactions and system dynamics. Recently, the Fourier Neural Operator (FNO) has been shown to be very promising in accelerating solving the Partial Differential Equations (PDEs) and modeling fluid dynamic systems. In this work, we apply the FNO network for real-time three-dimensional (3D) urban wind field simulation. The training and testing data are generated from CFD simulation of the urban area, based on the semi-Lagrangian approach and fractional stepping method to simulate urban microclimate features for modeling large-scale urban problems. Numerical experiments show that the FNO model can accurately reconstruct the instantaneous spatial velocity field. We further evaluate the trained FNO model on unseen data with different wind directions, and the results show that the FNO model can generalize well on different wind directions. More importantly, the FNO approach can make predictions within milliseconds on the graphics processing unit, making real-time simulation of 3D dynamic urban microclimate possible.

Nurlia, Dwi Susilowati, Dahniyar et al.

This study provides a comprehensive analysis of the global impact of COVID-19 on energy sector companies, taking into account company characteristics, market distinctions (developed and emerging markets), and sector differentiations (fossil fuels and alternative fuels). By examining financial report data from 1252 companies across 64 countries during the period 2018–2022, the study reveals a negative influence of COVID-19 on the performance of energy sector companies across all market and sector categories. Importantly, the findings highlight the significant role of company characteristics, including firm size, liquidity, and capital structure, in shaping the performance outcomes of energy sector companies.

Sergio Reyes-Corredera, Paulo Silva

Train stops on the Portuguese state network are a reference to the country's heritage. Their architecture is an invitation in many cities and towns not only to make a journey, but also to understand the territory and the cities where they are located. Many of these spaces can be the first stop of a tourist visit and a space of reflection to understand the evolution of the nearby geographical space and of the one further away. This methodological proposal offers a reading where the landscapes and cultural elements represented in their tile panels are identified, catalogued and interpreted from the perspective and understanding of railway architecture and the designs and forms of artistic expression used for the representation of Portuguese landscapes. For this research, the urban train network of the city of Porto (Portugal) was used due to its quantity and variety of elements for its study.

Athanasios Batakis, Thi-Thuy-Nga Nguyen, Michel Zinsmeister

In the first part of this paper we propose a new theoretical model of city growth based on percolation. The second half oh the paper is devoted to a concrete application of the model, namely to the city of Montargis. It appears that the embedded algorithm is quite efficient in terms of computational time and allows to exploit big data type ressources such as individual land lots.

Helena Blazun Vosner, Peter Kokol, Danica Zeleznik et al.

The development of modern nursing and consequently nursing research in Ex- Yugoslavia is about a century old. To profile the development, volume, and content of nursing research we completed a performance and spatial bibliometric analysis combined with synthetic content analysis to identify the most productive countries and institutions, most prolific source titles, country cooperation, publication production trends, the content of research and hot topics. The corpus was harvested from the Web of Science All databases and contained 1380 papers. Slovenia was the most productive country, followed by Croatia and Serbia. The synthetic content analysis demonstrated that nursing research in ex-Yugoslavian countries is growing both in scope and number of publications, notwithstanding the fact that research content differs between countries and it seems that each country is focused on their local health problems. A substantial part of the research is published in national journals in national languages however, it is noteworthy to note that some ex-Yugoslavian authors have succeeded in publishing their research in top nursing journals. The study also revealed substantial international cooperation especially among ex-Yugoslavian countries and European Union.