Development Of Cities Research Articles

Developing an evaluation model for urban tourism competitiveness: combining community construction and community service to foster sustainable development of cities.

This study aims to develop a comprehensive evaluation model for urban tourism competitiveness in China. Given China's transition into a mature tourist destination, there is a pressing need for a framework that can assess the effectiveness of its urban tourism strategies. The model presented in this study is designed to provide a holistic understanding of the factors influencing urban tourism competitiveness in the Chinese context. The methodology employed in this study combines both qualitative and quantitative approaches. A modified version of Porter's Diamond Model serves as the primary framework, augmented by the IMD World Competitiveness Center: International Institute for Management Development (IMD) framework to incorporate social governance and environmental dimensions. To derive comprehensive scores for sustainable development, a linear weighted evaluation method was used, incorporating the coefficient of variation entropy weight method. This approach allows for a quantitative assessment of urban tourism competitiveness from 2008 to 2019. The key findings of the study reveal significant challenges within the current urban tourism landscape in China. These challenges include homogeneous competition, a lack of strategic management, and insufficient service quality. Furthermore, the study identifies the need for greater emphasis on sustainable tourism development, balancing economic benefits with the preservation of cultural and natural assets. Based on the findings, the study proposes several solutions to address the identified challenges. These solutions include creating boutique inland tourism routes, developing unique urban tourism brands, and enhancing regional cooperation and management practices. Additionally, the study emphasizes the importance of integrating community development and services into the evaluation model to foster sustainable tourism development. The proposed solutions offer actionable insights for policymakers and planners seeking to improve the competitiveness and sustainability of urban tourism in China.

Evaluating coupling coordination between urban smart performance and low-carbon level in China’s pilot cities with mixed methods

The construction models of smart cities and low-carbon cities are crucial for advancing global urbanization, enhancing urban governance, and addressing major urban challenges. Despite significant advancements in smart and low-carbon city research, a consensus on their coupling coordination remains elusive. This study employs mixed-method research, combining qualitative and quantitative analyses, to investigate the coupling coordination between urban smart performance (SCP) and low-carbon level (LCL) across 52 typical smart and low-carbon pilot cities in China. Independent evaluation models for SCP and LCL qualitatively assess the current state of smart and low-carbon city construction. Additionally, an Entropy–TOPSIS–Pearson correlation–Coupling coordination degree (ETPC) analysis model quantitatively examines their relationship. The results reveal that smart city initiatives in China significantly outperform low-carbon city development, with notable disparities in SCP and LCL between eastern, non-resource-based, and central cities versus western, resource-dependent, and peripheral cities. A strong positive correlation exists between urban SCP and overall LCL, with significant correlations in management, society, and economy, and moderate to weak correlations in environmental quality and culture. As SCP levels improve, the coupling coordination degree between the urban SCP and LCL systems also increases, driven primarily by economic, management, and societal factors. Conversely, the subsystems of low-carbon culture and environmental quality show poorer integration. Based on these findings, this study proposes an evaluation system for smart and low-carbon coupling coordination development, outlining pathways for future development from the perspective of urban complex systems.

Review of Slum Management Policies in Urban Areas

Urban slum areas in Indonesia began to feel very disruptive to city mechanisms and dynamics in the late 70s, so the government launched Village Improvement programs such as the Moh Slum Improvement Program. Husni Thamrin in Jakarta, Dewi Sartika Village Improvement Program in Bandung, and other village improvements carried out in big cities in Indonesia. While these programs have not been able to solve existing problems, city dynamics are running so fast, especially after reform. The development of cities with very high population pressure is beyond the government's ability to control them. On the other hand, the need for employment and business is very large due to the financial crisis and the phenomenon of job cuts (PHK), because many companies are going bankrupt. This problem must be borne by the city ecosystem which has many limitations. People in every city, because they are pressured by the necessities of life, can do business in urban areas wherever they think there is a chance to live. In this situation, the growth of slum areas in urban areas not only occurs in residential areas, but also occurs in business areas and along road routes which are still possible to use as places of business and residence. Of course, this cannot be tolerated, and the government needs to respond through appropriate policies now and in the future, considering that slum areas are now evenly distributed to all cities in Indonesia and not only in big cities.

Multi-Source Data-Based Investigation of Spatiotemporal Heterogeneity and Driving Mechanisms of Coupling and Coordination in Human Settlements in Urban Agglomeration in the Middle Reaches of the Yangtze River

In the information age, the new wave of the information technology revolution has profoundly changed our mode of production and way of life. Pseudo human settlements (PHS), consisting of digits and information, have become increasingly important in human settlements (HS) systems, and become a strong support for the high-quality development of global HS. Against this background, clarifying the spatiotemporal heterogeneity and driving mechanisms of the coupling and coordination between the PHS and real human settlements (RHS) is of great significance to the high-quality development of HS and providing a reasonable explanation of today’s man–land relationship. Therefore, we developed a theoretical framework system for describing PHS–RHS coupling and coordination based on multi-source data such as internet socialization, public utility, and remote sensing images, etc. Taking the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), which is the key region consolidating China’s “two horizontal and three vertical” urbanization strategy, as a case study area, we have comprehensively analyzed the spatiotemporal heterogeneity of the coupling and coordination of PHS and RHS and its driving mechanism in UAMRYR during the period of 2011–2021, by comprehensively applying the modified coupling coordination degree (CCD) and other models. The results show are as follows: (1) Temporal process—The CCD exhibited a reverse L-shaped increasing trend. The CCD class varied significantly, with the extremely uncoordinated and severely uncoordinated classes present at the beginning of the study period and disappearing toward the end of the study period, while the well coordinated and highly coordinated classes were absent at the beginning of the study period and appeared toward the end of the study period. (2) Spatial pattern—The CCD exhibited an equilateral triangle-shaped, core–margin spatial pattern and a characteristic of core polarization. Overall, the spatial distribution of the CCD exhibited a characteristic of “high in the central region, low in the eastern and western regions, and balanced in the south–north direction”. (3) Dynamic evolution—The CCD increased more rapidly in the north-eastern direction than in the south-western direction; the CCD exhibited north-eastward migration and dispersion, and the spatial variability decreased. (4) Driving mechanisms—The primary factors affecting the CCD varied significantly over time. The living system was dominant in the PHS, whereas the human system was dominant in the RHS. The PHS had a greater effect than the RHS on the CCD. The study broadens the research scope of human settlements geography, establishes a scientific foundation for advancing urban HS construction in the UAMRYR, and offers theoretical support for the high-quality development of cities in the UAMRYR.

Constructing a standard system of city sustainable development assessment technology based on the SDGs

Given the rapid development of China’s new urbanization, cities with different locations and varying functional positioning, resource endowments, and development stages have insufficient scientific and applicable technical tools for implementing the United Nations Sustainable Development Goals (SDGs). City managers and policymakers must urgently establish SDG benchmarks to diagnose city development. Moreover, successful experiences from similar cities regarding sustainable development and self-improvement must be learned from to promote diversified, sustainable development across the country. Furthermore, emerging technologies such as artificial intelligence, the Internet of Things, big data and 5G are widely used in smart cities. Therefore, there is a growing need for “knowledge-based, personalized and intelligent” technologies to support monitoring, evaluation, and decision-making processes facilitating sustainable development in cities. This paper uses standardization as the theoretical support and technical basis. This approach can help clarify the sustainable development processes in China and clarify the evaluation results of and provide data on horizontal city comparisons, which can be used to develop evaluation technology for sustainable development in cities and construct a standardized system. The results provide a standard framework for intelligent assessment and decision-making regarding cities’ sustainable development capabilities in China. Evaluating major international standardization institutions reveals that the practices of Chinese national standards should be fully absorbed and integrated to guide the evaluation of smart, resilient, and low-carbon cities. To this end, an indicator library of city sustainable development is proposed to provide standard evaluation technology methods. Finally, analyzing the response relationship of the indicator library to SDGs reveals the need for a standardized knowledge map of sustainable development assessment techniques and methods from the perspective of integrated management for sustainable development in cities.

Exploring the influence of linear infrastructure projects 4.0 technologies to promote sustainable development in smart cities

Industry 4.0 technologies have a high potential to improve the planning and execution of linear projects such as roads, bridges and railroads. These technologies can help reduce emissions, enhance operations' efficiency, and improve users' quality of life. Despite their potential to promote sustainability in smart cities, there is a lack of research focused on analysing their impact. Therefore, this paper aims to identify 4.0 technologies related to linear projects and examine their influence on smart cities' sustainable development. The research method involved four main stages: identification of 4.0 technologies in linear projects, questionnaire design and application, influence analysis, and factor analysis. A systematic literature review identified a set of 4.0 technologies that favour smart cities' sustainable development. Subsequently, 66 experts were consulted to determine which of these technologies have the most significant influence on smart cities' sustainable development, highlighting data analysis and management, intelligent traffic control systems, and artificial intelligence. This study makes three main contributions: (1) it identifies thirty-seven 4.0 technologies associated with linear projects that promote sustainable development in smart cities; (2) it characterises the 4.0 technologies with the most significant influence on the sustainability of smart cities; and (3) it proposes nine principal components into which interrelated 4.0 technologies that promote sustainable development can be grouped. This study provides valuable evidence for smart city managers and offers guidance for the efficient adoption of 4.0 technologies in linear projects.

Integrating Real Estate Investment Environment Indicators with Sustainable Urban Development: An Evaluation Framework for Egyptian new cities

Abstract The decision-making process in real estate investment is strongly linked with economic development and the real estate market, exerting a significant influence on the construction industry. In Egypt, decision-makers often prioritize responding to investment pressures to attract investors and establish projects, neglecting the alignment of investments with the principles of sustainable urban development. This study aims to identify the indicators of real estate investment environment according to the sustainable urban development, enhancing the decision-making process in the urban development of new Egyptian cities. Additionally, the research seeks to show best practices and successful global initiatives that effectively integrate real estate investment environment with sustainable urban development, emphasizing on innovative strategies and policies. The study will conclude indicators that harmonize economic progress with spatial, environmental, and social sustainability to enhance decision-making processes in urban development by adopting a more holistic and inclusive approach.

Spatial–Temporal Similarity Fusion Graph Adversarial Convolutional Networks for traffic flow forecasting

Traffic flow forecasting is integral to the advancement of intelligent transportation systems and the development of smart cities. This paper introduces a novel model, the Spatial–Temporal Similarity Fusion Graphs Adversarial Convolutional Networks (STSF-GACN), which leverages advanced data preprocessing techniques to enhance the predictive accuracy and efficiency of traffic flow forecasting.The innovation of our approach lies in the meticulous construction of the spatial–temporal similarity matrix through the precise calculation of temporal and spatial similarities. This matrix forms the backbone of our model, serving as the generator in the integrated Generative Adversarial Network (GAN) architecture. The Spatial–Temporal Similarity Fusion Adaptive Graph Convolutional Network, developed as part of our GAN’s generator, utilizes cutting-edge techniques such as the Wasserstein distance and Dynamic Time Warping to optimize the adaptive adjacency matrix, enabling the model to capture latent spatial–temporal correlations with unprecedented depth and precision.The discriminator of the GAN further refines the model by evaluating the accuracy of the traffic predictions, ensuring that the generative model produces results that are not only accurate but also robust against varying traffic conditions. This cohesive integration of GAN into the model architecture allows for a significant improvement in prediction accuracy and convergence speed, moving beyond traditional forecasting methods.

Environmental Decentralization, Digital Financial Inclusion, and the Green Transformation of Industries in Resource-Based Cities in China

In the digital era, digital financial inclusion plays a pivotal role in facilitating green industrial transformation and green development in resource-based cities. In this study, we conduct an in-depth analysis of environmental decentralization and digital financial inclusion and their mechanism of influence on the industrial green transformation of resource-based cities, utilizing panel data from resource-based cities in China between 2011 and 2022, in order to perform empirical tests using fixed effects and threshold models. The results indicate that environmental decentralization can advance the green transformation of industries, and that, under the influence of digital financial inclusion, environmental decentralization has a significant reverse impact on the green transformation of industries of resource-based cities in China. Furthermore, different levels of digital financial inclusion contribute to varying effects of environmental decentralization on the green transformation of industries. Additionally, the impact of environmental decentralization on the green transformation of industries differs among various types of resource-based cities in China. Therefore, we should continuously optimize the management system of environmental decentralization, improve the digital financial inclusion service system, fully leverage the advantages of digital financial inclusion, accurately grasp and scientifically utilize the driving principles of environmental decentralization, and implement measures in different cities according to the situation, in order to advance the green transformation of industries in resource-based cities in China.

Green siphon or green spillover: Analyzing the spatial implications of industrial relocation on green development

Industry relocation has a profound impact on the green development of recipient cities and their neighboring areas, driven by various factors such as investment and technological progress. This study investigates the impact of industrial relocation on the green development efficiency (GDE) of recipient cities and its spatial spillover effect using national city-level data and the establishment of national-level Industrial Relocation Demonstration Zones (IRDZ) as a policy shock, employing spatial difference-in-differences models. Both theoretical analysis and empirical tests show that industrial outflow increases the GDE of recipient cities, but reducing the GDE of neighboring cities. This effect decays with spatial distance and only affects non-resource cities. In addition, regional integration and the influence of large cities can significantly mitigate the adverse effects of industrial relocation. Industrial agglomeration, environmental regulation, green innovation, and energy intensity are the main direct and indirect pathways through which industrial relocation affects GDE in recipient and neighboring cities. The findings of this study are significant for promoting industrial relocation, energy conservation, and emission reduction in developing regions, as well as enhancing green cooperation among governments.

Data autonomy: beyond personal data abuse, sphere transgression, and datafied gentrification in smart cities

The ‘smart city’ has been driven by advances in information and communication technologies, with the aim of integrating these technologies with urban infrastructures for improved optimisation, automation and control. Smart cities have emerged as a response to the challenges faced by megacities and are likely to manifest the ‘datafying’ society in the public space. However, the pervasive nature of data collection, continuous analysis and inference, and long-term data storage result in a potentially problematic reconfiguration of society that undermines individual and collective autonomy. This article proposes the concept of ‘data autonomy’ as a guiding principle for the development of smart cities, addressing challenges related to the potential misuse of personal data, sphere transgression, and datafied gentrification. Section II. explores concerns related to data protection law, which can be understood as a proxy for the relationship between the individual and society, highlighting power dynamics and the autonomy of individuals and communities. Section III. discusses the concept of sphere transgression, where tech giants expand their influence in society without adequate expertise or accountability. Section IV. examines the potential impact of datafied gentrification on individual and collective autonomy. Building on the challenges identified throughout these sections, this paper proposes ‘data autonomy’ as a guiding principle for smart city development in section V., promoting a value-based approach centred on human dignity. To make it practicable, increased interdisciplinary collaboration in the development of smart cities is needed, with a particular focus on improved design and impact assessment methodologies.

City identity in existing city future planning or development

City identity in existing city future planning or development

Improved Variable Scale Optimisation Algorithm in Water Saving Landscape Design and Its Application

Abstract With the acceleration of urbanisation, the problem of water resource shortage is becoming increasingly serious. Currently, the water use situation in Chinese cities is severe and the contradiction between the supply and demand of water resources is prominent, which has become one of the main factors restricting sustainable development of cities. Traditional research on water-saving landscape design focuses mainly on the analysis of the efficiency of water resource utilisation within a single area or city. The scope of the research is limited and the research methods are individual, which cannot fully meet the current needs of sustainable urban water-saving landscape design. The improved variable scale optimisation algorithm has become an indispensable tool in modern landscape design and would play a more important role in landscape design and ecological environment protection in the future. In response to the shortcomings of traditional variable-scale optimisation algorithms in solving the optimisation problem of water-saving landscape design for ecological sustainable development, this article would use an improved variable-scale optimisation algorithm to study the water-saving landscape design for ecological sustainable development in Community X, City B, Province A. The research results indicated that there were three experts who rated the effect of the water saving landscape design of the first group of designers as good or above, accounting for 37.5 %. The number of people who rated the effectiveness of water-saving landscape design in the second group as good or higher was 8, representing 100 %. The improved variable-scale optimisation algorithm could effectively improve the application of water-saving landscape design in ecological sustainable development.

Magnetic Gradiometry Survey at the Urban Centre of Türkmen‐Karahöyük (Turkey)

ABSTRACTThe understanding of urban centres in the ancient Near East, one of the main regions for investigating the development of cities, has been transformed in recent years through investigations using archaeological geophysical prospection tools. This paper presents results of our recent magnetic gradiometry survey at the large urban site of Türkmen‐Karahöyük (Konya Plain, Turkey) conducted using a SENSYS Magneto MXPDA cart‐based system. Results of the survey have successfully identified and characterized numerous areas of ancient settlement, industrial activity and burials across the massive site, offering new insights into the history of occupation at Türkmen‐Karahöyük. Our findings are thereby helping to shape future investigations at the site and, more broadly, demonstrate the opportunities and challenges presented by cart‐based geophysical survey instruments for archaeological investigations of mounded urban sites with extensive lower towns.

Identificação de manifestações patológicas através da elaboração de mapas de danos de fachadas de um prédio histórico da cidade do Recife, PE: Estudo de caso do Bloco A da Escola Politécnica de Pernambuco

The city of Recife has numerous historic buildings that have existed for over 100 years and are part of the rich culture of this region. Over the years, these buildings get damaged due to the action of external weather and, in some cases, human action, which ends up generating numerous pathological manifestations that require correction. Therefore, this research's main objective is to study and identify the pathological manifestations present on the facades of block A of the Polytechnic School of the University of Pernambuco, aiming to assist in future, more sustainable restoration works in this building. As a methodological basis, a photographic inspection of the study object was carried out, followed by the identification of the pathological manifestations present on each facade, analysis of the photos and the development of damage maps using AutoCAD software. As a result, several pathological manifestations were found on the four facades of the building and from the preparation of damage maps it was possible to identify the areas that needed the most urgent repairs, due to the high degree of incidence of anomalies. The results demonstrated the importance of conserving historical heritage, since these buildings are living memories of a people's culture, in addition to being important instruments for the economic, social and environmental development of cities.

Decoupling Analysis between Socio-Economic Growth and Air Pollution in Key Regions of China

The coordinated development of atmospheric pollution and socio-economic growth plays a core role in the sustainable development of cities and regions. The relationship between socio-economic growth and air pollution can be described using decoupling analysis. The seven key regions of China (168 cities), including Beijing–Tianjin–Hebei and its surrounding areas (BTHSR), the Yangtze River Delta region (YRDR), the Fen-Wei Plain (FWP), the Chengdu–Chongqing region (CCR), the urban agglomeration of the middle reaches of the Yangtze River (MLRYR), the Pearl River Delta region (PRDR), and other provincial capitals and municipalities with specialized plans (OPCCSP) were taken as targets to investigate the spatiotemporal evolution characteristics of AQI values and PM2.5 concentrations from 2014 to 2022. Then, the decoupling relationship between the AQI/PM2.5 and the socio-economic growth index (SEGI) in these key regions was deeply researched by the Tapio decoupling model. The main results were as follows: (1) Although the continuous improvement in air quality was observed in these seven key regions in China, the PM2.5 concentration in the BTHSR and FWP was still higher than 35 μg·m−3. The AQI showed a spatial pattern of high in the north and low in the south, and the distribution of PM2.5 in China was high in the east and low in the west. (2) The decoupling degree between air pollution and socio-economic growth was relatively high in the PRDR and YRDR. In contrast, the degree of decoupling was poor in the FWP and OPCCSP. The decoupling states were primarily influenced by industrial structure, energy consumption, and urbanization. (3) The decoupling of air pollution from socio-economic growth was in a strong decoupling state throughout the majority of the study period, achieving a comparatively ideal decoupling state in 2018. However, the overall decoupling states of the seven regions were not sustainable, and the decoupling stability was relatively poor. During the research period, the decoupling state between socio-economic growth and air pollution changed and was unstable.

Non-linear relationship between built environment and active travel: A hybrid model considering spatial heterogeneity

Exploring the mechanisms between the built environment and active travel is crucial for promoting green transportation and fostering the sustainable development of cities. Existing literature focuses on the correlation between the built environment and active travel in urban centers, with limited studies on suburban environments, ignoring the implications of spatial heterogeneity. This paper conducts a comprehensive spatio-temporal analysis of suburban residents’ active travel behavior and explores the nonlinear relationship between suburban built environment and active travel. A novel hybrid modeling framework that combines eXtreme Gradient Boosting and Multi-scale Geographic Weighted Regression is introduced to forecast suburban active travel demand with the consideration of the nonlinearity and spatial heterogeneity in parameter estimates. Shapley additive explanation is used to elucidate the non-linear relationship between built environment variables and active travel. The results indicate that the proposed hybrid model performs the best with high predictive power and interpretability. The density of tourist attractions, transportation facilities, and household properties emerges as the three most influential factors affecting residents’ active travel behavior. Social-economic attributes contribute 15.70% to the prediction, while three categories of built environment variables (accessibility, transportation facilities, and land use) contribute 7.31%, 5.13%, and 71.87%, respectively. The hybrid model appears to be effective in identifying the nonlinear relationship and threshold effects between built environment variables and active travel. Besides, the model provides actionable insights into designing sustainable and efficient suburban environments, supporting targeted planning and policy-making efforts.

Analyzing urban footprints over four coastal cities of India and the association with rainfall and temperature using deep learning models

Capabilities of deep-learning models CNN and ConvLSTM are explored for analyzing and projecting future urban growth in four Indian coastal cities, viz., Mumbai, Chennai, Kochi, and Vishakhapatnam. ConvLSTM performed better with higher overall accuracy, Cohen's kappa, macro F1-score (> 95 %), and R2 and NSE values (> 0.87). The urbanization trends indicate a higher growth in Kochi (∼90.5 %), and greater projected rate for Mumbai (∼42.5 %). The monthly accumulated rainfall and mean temperature are analyzed and forecasted through the ConvLSTM model. The Mann-Kendall test-based analysis (with p-value <0.05), suggest no significant rainfall pattern for the cities except Mumbai, which exhibits an increasing trend. The projected rainfall trend is unaltered except for Vishakhapatnam, which is expected to increase in the coming years. The mean temperature over all the cities, shows an increasing trend (slope ∼ 0.02). However, in the coming years, the ‘increasing trend’ is expected to change into a ‘no significant trend’ for Mumbai and Vishakhapatnam. The forecasted results indicate a continuous urban expansion, which is expected to have a significant impact on rainfall and temperature trends. The outcome could assist urban planners in defining the timeline for improving drainage and include green spaces in the city development plans.

How does urban industrial structure upgrading affect green productivity? The moderating role of smart city development

The concept of the smart city, which has recently gained prominence as a new urbanization model, represents a practical approach to achieving a balance between economic development and environmental protection. This article analyzes the effect of upgrading urban industrial structures on green total factor productivity (GTFP) and addresses a gap in evaluating the mediating role of smart city development. Utilizing panel data from Chinese prefecture-level cities, the study finds that internal advancements and diversification in industrial structures significantly enhance GTFP, while industrial structure rationalization displays a complex, non-linear correlation with GTFP. Moreover, smart city development is found to positively moderate the relationship between industrial structure and productivity, particularly in terms of outer-advancement, diversification, and rationalization. The moderating effect is evident in green technical efficiency rather than green technological innovation. Cluster analysis reveals significant effects in regions characterized by irrational, diversified, and naturally rational industrial structures. Additionally, the study identifies five impact mechanisms facilitated by smart cities, namely ICT, finance development, digitalization, smart governance, and social trust. These conclusions are of material significance to promote high-quality urban development.

DEVELOPMENT OF CITIES

The development of cities is a complex and multifaceted subject that intertwines urban planning, geography, economics, and architecture. Cities are shaped by a variety of factors, including their historical contexts, geographical settings, economic activities, and cultural influences. This research paper delves into the evolution of cities by examining their growth patterns, shapes, and structures throughout history. From the ancient cities that emerged around 3500 BCE to the contemporary urban environments of today, the study highlights the interplay between natural features, human activities, and technological advancements in shaping urban landscapes. Modern city planning principles are also explored through the research paper, emphasizing sustainability, smart technologies, and inclusivity in the face of growing urbanization and globalization. This paper aims to provide a comprehensive understanding of how cities have developed over time and the factors that continue to influence their form and function in the 21st century. Key Words: city form, urban planning, shape, pattern.