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In the context of ongoing global urbanization, the disparity in urban development, marked by the dual phenomena of urban sprawl and urban shrinkage at the regional level, has become increasingly evident. In this vein, two land-related governance strategies—smart growth (SG) and smart shrinkage (SS)—emerge as potential remedies to these challenges, targeting urban expansion and shrinkage, respectively. This study bridges the gap in the fragmented discourse surrounding SG and SS by conducting a comprehensive comparative review on the respective literatures. Utilizing the Scopus database, our research employs trend analysis, text and topic mining, time node analysis, and regional analysis, augmented by qualitative reviews of seminal papers. The findings reveal a notable shift in research focus, with interest in SS surging around 2010 (the number of SS-related papers published after 2010 accounts for 92.3% of the total number of the entire study period) as attention to SG waned, suggesting an impending paradigm shift in urban sustainability. The analysis indicates that SS research lacks the disciplinary diversity, thematic breadth, and empirical depth of SG studies, underscoring a need for a more robust theoretical foundation to support urban sustainability. Furthermore, while both SG and SS derive from environmental science foundations, SG predominantly addresses the physical and landscape attributes of urban areas, whereas SS focuses more on socio-economic dimensions. Our findings point to an intrinsic link between SG and SS, which could lay the groundwork for their integration into a unified theoretical framework to better advance urban sustainability. [ABSTRACT FROM AUTHOR]

The development of smart cities has led to transforming modern city operations by applying emerging technologies from the fourth industrial revolution such as the Internet of Things, BIM and machine learning. To prepare for the future development of cities, it is necessary to investigate the current status of city development, research topics and the direction toward future cities. In this study, a systematic literature review was conducted following the combination of literature review guides by Kitchenham and the PRISMA statement. The review identified 141 peer-reviewed academic papers from web-based archives, such as Web of Science and SCOPUS, that were categorized into five topics related to smart cities and urban areas. The technologies applied in the research were analyzed to determine the direction future cities should take based on current smart cities and emerging technologies that will shape individuals' daily lives. However, it was discovered that research papers on critical areas, such as mobility and management, were lacking compared to those on building design and urban planning. This paper concludes with an example of a future urban area that has been transformed due to adoption of future mobility technology to address the shortcomings of the reviewed literature on building and urban environments. [ABSTRACT FROM AUTHOR]

Since 1971, remote sensing techniques have been used to map and monitor phenomena and parameters of the coastal zone. However, updated reviews have only considered one phenomenon, parameter, remote data source, platform, or geographic region. No review has offered an updated overview of coastal phenomena and parameters that can be accurately mapped and monitored with remote data. This systematic review was performed to achieve this purpose. A total of 15,141 papers published from January 2021 to June 2023 were identified. The 1475 most cited papers were screened, and 502 eligible papers were included. The Web of Science and Scopus databases were searched using all possible combinations between two groups of keywords: all geographical names in coastal areas and all remote data and platforms. The systematic review demonstrated that, to date, many coastal phenomena (103) and parameters (39) can be mapped and monitored using remote data (e.g., coastline and land use and land cover changes, climate change, and coastal urban sprawl). Moreover, the authors validated 91% of the retrieved parameters, retrieved from remote data 39 parameters that were mapped or monitored 1158 times (88% of the parameters were combined together with other parameters), monitored 75% of the parameters over time, and retrieved 69% of the parameters from several remote data and compared the results with each other and with available products. They obtained 48% of the parameters using different methods, and their results were compared with each other and with available products. They combined 17% of the parameters that were retrieved with GIS and model techniques. In conclusion, the authors addressed the requirements needed to more effectively analyze coastal phenomena and parameters employing integrated approaches: they retrieved the parameters from different remote data, merged different data and parameters, compared different methods, and combined different techniques. [ABSTRACT FROM AUTHOR]

Promoting sustainable communities aims at creating both environmentally and socially responsible living environments. This paper explores the role of affordable housing in promoting the long-term sustainability of a community within healthy living conditions by closely examining the relationship between affordable housing, urban development policies, and sustainability, with the capital of Lebanon, Beirut, serving as a case study. The first part of the paper focuses on the current building laws issued in the official newspaper in 2004 using a content analysis methodology to demonstrate the impact of the changes in the laws on the new morphology and social fabric of the city through the creation of a favorable environment for big developers, wealthy property owners, and real estate agencies and, at the expense of old city residents and low-income families. The second part of the paper uses the qualitative analysis methodology to justify the presence of large unused stock of residential units in Beirut, referring to information from multiple data sources selected based on their applicability to sustainable development, affordable housing, and urban planning in areas related to the case study, Beirut. This part then investigates the potential presented by this stock of residential units in Beirut to increase the supply of affordable housing and foster a sustainable community. This paper argues that the promoted vertical expansion of the city weighs heavily on the environment and fails to provide a diverse mix of housing units, excluding a significant portion of the community from the city. Alternative development models aligning with principles of sustainable development and challenging the current building laws can promote social inclusivity, reduce urban sprawl, and minimize environmental impacts associated with new constructions, thus preserving the city's physical and social fabric. [ABSTRACT FROM AUTHOR]

Continuous enhancement of sustainable development capacity is one of the goals of building a well-off society. In order to understand the development of each region, it is necessary to make a comprehensive evaluation of their sustainable development capacity. This paper presents a study of the 11 regions of Hebei Province, China. Considering the influence of time on urban development, this paper comprehensively evaluates the sustainable development ability of each region in Hebei Province from three dimensions of society, economy and environment based on panel data. The evaluation results show that Shijiazhuang has the strongest sustainable development capacity. On this basis, the promoting factors and restricting factors of sustainable development in each region are found by using grey correlation analysis method. This study provides a reference for the future sustainable development of each district. [ABSTRACT FROM AUTHOR]

Phase models of gentrification play a prominent role in German-language urban geography textbooks and in shaping discussions on urban gentrification. Their empiric validity however, remains a topic for debate. To contribute to this debate, we conduct a comprehensive literature review of English- and German-language gentrification research over the past 40 years, with a specific focus on phase models. We examined 4,262 papers on gentrification, employing keyword searches and forward citation to pinpoint those that reference the phase models. Out of these, 223 papers mentioned the phase models or relevant key terms, but upon closer examination, only 56 directly addressed the model, forming the basis for our qualitative content analysis. We then assess the evolution of scientific discourse on phase models and their empirical validation. Despite their widespread reference, our study reveals that only a small fraction of gentrification research explicitly engages with these models, with limited empirical evidence to support their comprehensive validity. We argue that, although these models offer a framework for understanding gentrification, they are not universally applicable and neglect important elements such as, amongst others, supply-side factors and the diversity of gentrification trajectories. We advocate for a more nuanced approach to gentrification studies, calling for empirical research that encompasses a wider array of socio-ecological factors and recognizes the heterogeneity of gentrification patterns. Furthermore, there is a need for improved integration of urban research findings into educational materials, proposing a more critical presentation of gentrification models in school textbooks to reflect their limitations and the complex realities of urban development. [ABSTRACT FROM AUTHOR]

In the process of global urban development, there are urgent ecological security and environmental pollution problems, green development is the fundamental way for urban sustainable development, economic transformation and mitigation of ecological and environmental problems. Based on the panel data of 283 cities at prefecture level and above in China from 2003 to 2017, this paper analyzes spatial–temporal evolution characteristics of urban green development efficiency (UGDE) and the peer effects of UGDE between cities of different grades. It is found that during the study period, in terms of temporal evolution, the average UGDE in China increased from 0.47 in 2003 to 0.61 in 2017, with a cumulative growth rate of 29.79%, showing a rising trend in general. In terms of spatial evolution, the number of low-efficiency cities and medium-efficiency cities continued to decrease. The eastern region has always been the main distribution area of higher-efficiency cities and high-efficiency cities; in the central region, UGDE in most cities improved significantly; in the western region, UGDE has always lagged behind that in the eastern and central regions. In addition, the center of gravity of UGDE presented a trend of northwest migration in general, with a total displacement of 100.07 km, and UGDE showed a spatial dispersion trend. The empirical results indicate that the improvement of UGDE in large cities has a driving effect on that in neighboring medium cities and small cities through the positive peer effect, and the growth of UGDE in medium cities has a promoting effect on that in neighboring small cities through the positive peer effect; the increase of UGDE in medium cities has a positive peer effect on that in neighboring large cities, and the growth of UGDE in small cities has a positive peer effect on that in neighboring medium cities; UGDE promotes each other between large cities through the positive peer effect. [ABSTRACT FROM AUTHOR]

With the rapid development of the world city network, the traditional location theory has gradually been disproven, and the advantages of the flow space over the traditional vertical organizational structure are gradually being revealed. Therefore, from corporate branch networks and corporate investment networks, 21 cities in urban agglomerations of Guangdong are taken as case studies for this paper. Furthermore, in this paper, 5 representative types of corporate contact data (catering service, financial service, life service, sports and leisure and accommodation service) are selected, the social network analysis (SNA) method is used to quantitatively analyze the network structure characteristics of urban agglomerations, and a spatial interaction model is constructed to explore the factors influencing. The results indicate that secondary networks have developed in Guangdong. The financial service network is the most complex, followed by the life services, sports and leisure and catering networks. The accommodation service network structure is the simplest. Among all kinds of networks, Guangzhou and Shenzhen have the highest status. The catering and accommodation corporations in Yangjiang in the west have a relatively major external development. Shantou in the east has many branches of various types, while most of the capital exchange in the region is concentrated in Heyuan and Qingyuan in the north. The coefficients of geographical proximity and the urban development level play a significant role in promoting the development of networks. However, administrative capacity limits the attractiveness of origin cities to a certain extent. [ABSTRACT FROM AUTHOR]

With the continuous development of the global economy, carbon dioxide and other greenhouse gas emissions are persistently increasing, making global warming an indisputable fact. As a high-energy consuming industry, the building industry has gradually emerged as the primary source of greenhouse gas emissions during urban expansion. Consequently, countries are exploring sustainable development pathways for low-carbon buildings to minimize the detrimental impact caused by the construction industry. This paper summarizes the current status of low-carbon building development and, through literature analysis concerning carbon standard systems and carbon emission accountings, discusses the challenges and possible improvements for the future. Establishing a quantitative evaluation tool for carbon emissions and elucidating accounting methods in the construction field is fundamental and a prerequisite for comprehensively studying low-carbon buildings throughout their life cycle. The challenges of low-carbon building development are as follows: (1) lack of a set of carbon emission measurement standards that can be commonly used internationally, (2) lack of a deep and systematic study of the theory of carbon emission accountings and (3) difficulty in recognizing carbon emission boundaries and related data for existing carbon emission accounting methods. This paper provides a comprehensive analysis of the current progress in low-carbon building development, along with an examination and optimization of the application of carbon emission accounting methodologies within construction to address the challenges. [ABSTRACT FROM AUTHOR]

Introduction: The Yellow River Basin is an important national energy base and ecological protection area, and it is of great significance to promote the coordinated development of high-quality development and eco-environmental carrying capacity in the region. Methods: Taking the 73 prefecture-level cities along the Yellow River as the study unit, this paper measures the changes of high-quality development level and eco-environmental carrying capacity of municipalities from 2005 to 2020, using the coupling coordination degree model and fuzzy logic algorithm. Results and discussion: 1) The capital city and its surrounding cities have a high level of high-quality development, with the lower and middle reaches of the Yellow River having higher levels than the upper reaches. From 2005 to 2020, the level of high-quality development showed an upward trend. 2) The eco-environmental carrying capacity of cities in the lower reaches is higher than that in the upper reaches. From 2005 to 2020, the eco-environmental carrying capacity of cities in the lower reaches of the Yellow River increased first and then decreased. 3) The provincial capital cities have a high degree of coupling coordination, with cities in the lower reaches having a higher level than those in the middle and upper reaches. A high degree of coupling coordination reduces spatial differences, but dominated by primary coordination. 4) From 2005 to 2020, the eco-environmental carrying capacity tended to be coordinated with the high-quality development, close to a high level and system optimization. In the end, we conclude with policy recommendations to promote high-quality urban development and harmony between people and nature in the region. [ABSTRACT FROM AUTHOR]

Research currently focuses on immersive technologies like virtual reality (VR), augmented reality (AR), and mixed reality (MR). However, there is limited exploration of their application in sustainable smart cities with Building Information Modeling (BIM), and there remains a lack of interdisciplinary integration within this domain aimed at fostering sustainable smart city development. Therefore, this paper aims to explore the development status of immersive technology and BIM in sustainable smart cities, identifying trends and research hotspots by employing a triangulation research method mixed with a quantitative method via bibliometric analysis and a qualitative method via content analysis to investigate the relationship between immersive technologies and BIM in sustainable smart cities. The results reveal a fragmented nature in the research on immersive technology and BIM in sustainable smart cities, with rapidly changing hotspots and new technologies following a cyclical pattern every 3 to 5 years. Two distinct cycles of growth were observed in the field over the last 10 years (2014–2023). The first cycle, from 2014 to 2017, represented modest growth, while the second cycle, from 2018 to 2022, showed rapid expansion, with the keywords AR, VR, MR, BIM, smart city, and smart city concept indicating the research hotspots. Immersive technologies and BIM, developed since 2017, have contributed to sustainable smart city construction. The emerging keywords AR, MR, and 360-degree VR have become research hotspots since 2021, particularly in collaborative construction. Future research trends include artificial intelligence, digitalization, AR, and MR, while building sustainability and intelligent construction have emerged as real-world applications. Additionally, this paper employs software tools to generate multidimensional knowledge maps to form a knowledge universe map at a "macro-knowledge" level followed by a "micro-knowledge" level comprising a standard knowledge system, such as lifecycle analysis, enhancing the objectivity and organization of the results and providing innovative references for future research. [ABSTRACT FROM AUTHOR]

With the world's rapid urban development, it has been observed that space for sociability has decreased. To overcome the impact of the same, streets should develop as an urban space along transit corridors. These spaces encourage meaning and identity creation by offering visual quality to everyone. This paper focuses on assessing parameters through which an urban streetscape along transit corridor can be analyzed to enhance visual quality. The authors suggest nine essential parameters based on literature review and expert interviews. [ABSTRACT FROM AUTHOR]

In order to explore the causal relationship between the level of urban digital construction and urban economic growth, this paper takes 280 cities in China as the research object and constructs a comprehensive indicator evaluation system covering digital infrastructure, overall economic level, innovation development level, digital industry development status, and ecological environment conditions. Using the entropy method to weigh various indicators, this paper has obtained the evaluation results of the digital construction level of each city from 2011 to 2021. Furthermore, a panel data regression model is used to empirically analyze the impact of urban digital construction level on urban economic growth. The results show that for every 1% increase in the level of urban digital construction, the GDP will increase by 0.974. Through the above research, we hope to further enrich the theoretical and empirical research in the field of the digital economy, provide a scientific and reasonable method for quantitatively evaluating the level of urban digital construction, and provide decision-making references for improving the level of urban digital construction and promoting sustainable urban development. [ABSTRACT FROM AUTHOR]

Scholars have done a lot of research on urban settlement, but it is difficult to give consideration to the temporal and spatial attributes of settlement at the same time in its display and analysis. Most of them focused on the analysis of regional settlement, single point settlement curve and settlement rate map at a certain time, but few combined time and space for collaborative analysis. Therefore, in this paper, 32 scenes Sentinel-1B SAR data are used to obtain settlement data of Beijing via PS-InSAR method. Secondly, combined with the temporal and spatial attributes of settlement results, the subsidence law revealed by using spatio-temporal cube slicing and attribute filtering. Finally, subsidence development trend and the detection of abnormal subsidence are explored by emerging hot spots (ESH) analysis. The experimental results show that the settlement funnel center in Beijing is mainly concentrated near the junction of Chaoyang district and Tongzhou district. The settlement range tends to expand. There are several local continuous subsidence areas in the settlement oscillating area. Spatio-temporal analysis makes the development trend of urban settlement more intuitive. Emerging hotspot analysis combined with Getis-Ord Gi* statistics and Mann-Kendall trend test could more effectively analyze the settlement trend of the study area and detect new potential settlement centers, so that to provide auxiliary decision-making for urban safety early warning and city development. [ABSTRACT FROM AUTHOR]

This paper is situated within the discussion of mega-urbanization, a particular urbanization process that entails a large-scale agglomeration. In this paper, our focus is on urbanization in Java, Indonesia's most dynamic region. We add to the literature by investigating the change and prediction of the land use/land cover (LULC) of mega-urbanization in Java. This research uses a vector machine approach to support the classification of land cover change dynamics, cellular automata-Markov (CA Markov), and the Klassen typology technique. This paper indicates that major metropolitan areas are still expanding in terms of built-up areas, generating a larger urban agglomeration. However, attention should be also given to the urbanization process outside existing metropolis' boundaries given that more than half of the built-up land coverage in Java is located in non-metropolitan areas. In terms of future direction, the projection results for 2032 show that the Conservative scenario can reduce and slow down the increase in built-up land on the island of Java. On the other hand, the Spatial Plan (RTRW) scenario facilitates a rapid increase in the LULC of built-up land from 2019. The urban spatial dynamics in Java raises challenges for urban and regional planning as the process is taking place across multiple administrative authorities. [ABSTRACT FROM AUTHOR]

Public sentiment can effectively evaluate the public's feelings of well-being in the urban environment and reflect the quality of the spatial environment to a certain extent. Previous studies on the relationship between public sentiment and urban built environmental factors have yielded meaningful results. However, few studies have focused on the effect of micro-built environment on public sentiment at the street level, which directly shapes people's perceptions. In addition, the nonlinear relationship and synergistic effect among urban built environmental factors have been commonly disregarded in previous studies, resulting in an incomplete understanding of the impact of urban built environment on public emotions. Therefore, this paper takes San Francisco as a study case to explore the complex relationship between urban built environmental factors and public emotions. Specifically, this paper measures the polarity of public emotions through sentiment analysis on Twitter data, establishes a comprehensive built environment index system from both macro- and micro- perspectives, and subsequently explores the complex relationship between the urban built environment and public sentiment through the OLS model and Shapley Additive Explanation algorithm. Results show that: (1) micro-built environmental factors have a significant influence on public emotion, although they have been frequently ignored. (2) Public sentiment tends to be more positive in areas with recreation facilities, mixed land use, rich street view visual environment, suitable thermal and acoustic environment, balanced income, and a suitable degree of high population density. (3) A nonlinear relationship and threshold effect exist between the built environmental variables and the semantic orientations of public emotion. Environment improvement strategies based on the synergic effect between variables can effectively promote the generation of positive emotions. Our empirical findings can offer valuable insights to promote feelings of well-being and foster an urban development approach through strategic interventions within the urban built environment. [ABSTRACT FROM AUTHOR]

The connotation and measurement standard of "fairness" in parkland planning is closely related to the level of urban development and residents' needs, with solid realism and dynamics, and it is still a complex problem to control accurately in planning. Therefore, to conduct a more comprehensive study, taking the main urban area of Harbin as an example, this paper combined urban development background and practical problems at different stages and, based on POI and AOI data, divided the connotation of "equity" in park green space planning into two levels: "spatial equity" and "social equity". Based on these two levels of fairness, the research framework of urban park green space layout is constructed. Kernel density estimation and GIS-based network analysis were used to study the spatial layout and accessibility of urban parkland. The ability to match supply and demand for parkland in the study area as a whole was analyzed using a gridded two-step moving search method, as well as the degree of equity in the enjoyment of urban parkland by vulnerable groups including the elderly and children using the Lorenz curve with the Gini coefficient, the share index, and the entropy of the locality. The results show that: (1) the parkland is concentrated in the seven main urban areas of the two–two junctions, and the cohesion distribution trend is outside the distribution. (2) Motorized vehicles have the best 15-min accessibility for travel, but it still does not cover all the parkland. (3) Supply and demand within the region are unsatisfactory, with the area with the strongest supply and demand capacity for parkland accounting for only 3.19% of the total area. (4) The Gini coefficient of parkland enjoyed by the residents of Harbin city center is 0.407, with a massive gap in the overall distribution. In addition, the share index of vulnerable groups of the elderly and children all have share indices below 1, and the results of the analysis of locational entropy indicate that the level of street park green space resources enjoyed by these two groups belongs to the low socio-spatial equity pattern, which is not balanced. This study investigates the spatial layout of urban parkland from two equity levels, which can provide new ideas for the equity study of urban green space planning. [ABSTRACT FROM AUTHOR]

Against the backdrop of an urban-rural dual structure, governance structure significantly influences the fairness and sharing of land value increment profits from land consolidation in various regions. This paper develops a spatial-institutional analytical framework, reflects on the traditional government-led land quota planning management mechanism and advocates optimizing governance structures in land consolidation to facilitate urban-rural element flows and the sharing of land value increment profits. This paper selects two comprehensive land consolidation cases in the Fenghua District and Cixi City of Ningbo, representing government-led and village collective self-organized governance structures. The research shows that the Fenghua case adopts a government-led state-owned enterprise coordinated governance structure, which state-owned enterprises bear operational risks and the majority of profit sharing, while village collectives, as landowners, are insufficiently protected in benefit sharing. The Cixi case employs a government-embedded village-town governance structure, with the village collectives as the main operating body, allowing collective construction land to enter the market to ensure the sharing of community profits. Both governance structures promote the bidirectional flow of urban-rural land resource elements; the former significantly drives urban development, while the latter ensures better benefit sharing for village collectives. The research proposes that optimizing governance structures and improving land quota allocation mechanisms can further stimulate various entities' participation in land consolidation and land value activation. [ABSTRACT FROM AUTHOR]

In the study of urban development, it is very important to evaluate the influence of production factors reasonably and efficiently for the region to achieve efficient development. The principal aim of this investigation is to amalgamate the conventional measurement model characterized by robust interpretability with the non-parametric model characterized by limited interpretability, thereby enhancing the precision of research outcomes. Towards this objective, the study employs an optimized directional distance function integrated with a global Malmquist–Luenberger index to formulate a comprehensive total factor productivity measurement framework. In elucidating the homogeneous attributes of regions, departing from prior methodologies reliant on manual or direct algorithmic partitioning, this paper employs the K-means clustering algorithm for index discernment, abstracting the concept of K-means clustering centroids to encapsulate regional homogeneity, thereby delineating results through the visualization of regional development potential maps and the evolution of centroid-based clustering trend maps. The findings of the investigation illuminate common patterns of change across disparate regions, proposing a strategy for leveraging regional resource endowments towards a cohesive framework, thereby transcending constraints imposed by production efficiency limitations. Amidst the backdrop of the COVID-19 pandemic, this study draws upon provincial-level data spanning from 2000 to 2018 in China. The conclusive analytical outcomes underscore the pivotal role of energy factors in regional development efficiency, particularly within high-potential development regions, followed by the capital and labor factors. Concurrently, the study discerns a discernible hierarchical pattern among areas of development potential, which exhibits correlation with factor mobility dynamics. [ABSTRACT FROM AUTHOR]

As an efficient, environmentally friendly, and economical urban public transportation tool, the subway has significant advantages compared to other urban public transportation tools and plays an irreplaceable role in the urban rail transit system. While the subway brings many conveniences to people, its operation has also brought a series of problems to urban development and residents’ lives, especially the vibration and noise problems generated by the subway have become unavoidable and urgent problems to be solved. The traditional wave barriers have a certain effect on attenuating and suppressing the vibration generated by the subway, but it has shortcomings in terms of the width and quantity of elastic wave bandgap (BG), so its application in low-frequency vibration reduction and isolation of subway systems is greatly limited. In order to broaden the elastic BG width and quantity of the wave barrier, this paper designs a novel phononic-like crystal subway wave barrier (PLCSWB) for subway vibration isolation based on locally resonant theory. Firstly, the dispersion curves of the novel PLCSWB are calculated using the improved plane wave expansion method and finite element method (FEM), and compared with the dispersion curves of traditional phononic crystal (PC) wave barriers. Secondly, the frequency response function of the novel PLCSWB is calculated using FEM to evaluate its attenuation effect on vibration, and the energy distribution characteristics at its BG boundary are analyzed. Then, the main factors affecting the BG of the novel PLCSWB are analyzed, and a spring–mass system equivalent model of the novel PLCSWB is established to theoretically estimate its BG range. Finally, the vibration data of the tunnel wall monitored on site are used to analyze and verify the vibration isolation effect of the novel PLCSWB. The results show that the novel PLCSWB opens five low-frequency BGs in the 200Hz frequency band, which increased the total width of the opened BGs by 49% compared to traditional PC wave barriers. In the frequency range of the BG, the attenuation value of the novel PLCSWB to vibration is mostly above 30dB, and the energy distribution inside the structure is mainly concentrated in the primitive cell that controls the BG, indicating good attenuation and control effects on vibration. The main factors affecting the BG of the novel PLCSWB are the density of the scatterer material, the elastic modulus, and the thickness of the wrapping layer material. Moreover, during subway operation, the novel PLCSWB has a good attenuation effect on the vibration transmitted from the tunnel wall to the soil. Among them, the maximum vibration acceleration amplitude of the novel PLCSWB with nine rows is reduced by 47%, and the vibration isolation performance is remarkable. The relevant research results of this paper provide a novel approach and method for the study of subway vibration reduction and isolation, and can also provide specific references for the design and development of wave barriers. [ABSTRACT FROM AUTHOR]

As urban development accelerates and natural disasters occur more frequently, the urgency of developing effective emergency shelter planning strategies intensifies. The shelter location selection method under the traditional multi-criteria decision-making framework suffers from issues such as strong subjectivity and insufficient data support. Artificial intelligence offers a robust data-driven approach for site selection; however, many methods neglect the spatial relationships of site selection targets within geographical space. This paper introduces an emergency shelter site selection model that combines a variational graph autoencoder (VGAE) with a random forest (RF), namely VGAE-RF. In the constructed urban spatial topological graph, based on network geographic information, this model captures both the latent features of geographic unit coupling and integrates explicit and latent features to forecast the likelihood of emergency shelters in the construction area. This study takes Beijing, China, as the experimental area and evaluates the reliability of different model methods using a confusion matrix, Receiver Operating Characteristic (ROC) curve, and Imbalance Index of spatial distribution as evaluation indicators. The experimental results indicate that the proposed VGAE-RF model method, which considers spatial semantic associations, displays the best reliability. [ABSTRACT FROM AUTHOR]

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Measuring the impact of land use regulation on the land market involves identifying and classifying relevant impact factors related to the land market. The objective of this study was to identify land market impact factors in the context of the introduction of land use regulation in Nepal. Through a combination of desktop review and the incorporation of stakeholder perspectives, the paper presents a new approach for determining land market impact factors due to land use regulation where both generic and country issues are considered. A desktop review was carried out to identify a preliminary set of impact factors, which were reclassified through intuitive analysis based on the degree of thematic closeness. Perspective-based impact factors were identified through the qualitative analysis of primary data collected through semi-structured interviews with the Nepalese land market stakeholders. These independently derived impact factors were compared with the desktop literature review impact factors, resulting in 14 land market impact factors across four dimensions, including transaction cost, valuation, mortgage availability, taxation, and compensation across the economic dimension; lot size, subdivision restrictions, and coordination across the institutional dimension; awareness, expectation, and proximity across the social dimension; and risk reduction, quality of residential land, and suitability of zoning classification across the environmental dimension. There was significant overlap and commonality across factors identified from both the literature review and semi-structured interviews. The land market impact factors determined in this study may be adapted and generalized across other countries and could be utilized to better understand the impacts of land policy decisions on urban planning and development. Further research is recommended on the process to operationalize the use of these factors to quantify the impact of land use regulation on different land markets. [ABSTRACT FROM AUTHOR]

Urban areas are places associated with the transformation of ideas into practices, social initiatives, and spatial economics. The study aims to assess the triad interaction between education, science, and business as a multiplier on the socio-economic development in the region. The study built a conceptual model of socio-economic space in the context of innovative urban development: the unity of education, science, and business. The statistical analysis allowed the author to substantiate the peculiarities of the local triad. The study revealed correlations in the influence of education, science, and business on changes in the regional system. The paper suggests that the triad of education, science, and business rests on territorial specifics. This feature is the determining factor of innovative development in the field of resort towns. The presented research uses the quantitatively measured influence of the triad as a multiplier by combining values of the unity of education, science, and business. The study found that the mentioned indicator reflects the wellbeing and quality of the labor resources in the region. On the one hand, the multiplicative influence of the triad is a guarantee of an increase in the wellbeing level within the borders of the region. On the other hand, it requires adaptation of the innovative development of resort towns to the current growth of the workforce and a decrease in innovative advantages on a local scale. The findings provide policymakers with significant indicators on the way to stabilizing the regional economy and effective decision making. The study of the interaction between education, science, and business in the context of socioeconomic development can become a crucial tool for formulating policies aimed at stabilizing the region’s economy and improving the quality of life of its residents, particularly in resort cities. The obtained results can provide guidelines for the development of innovation support programs and the planning of investment strategies, taking into account the specifics of territorial conditions. [ABSTRACT FROM AUTHOR]

Increased urbanization and population lead to increased consumption of manufactured goods. This ultimately results in increased production of waste. Identifying its composition is crucial for planning an effective solid waste management strategy. This study assesses the characteristics and composition of the waste generated within the Uyo Capital City Development Area of Akwa Ibom State, Nigeria. This is to aid in developing a scientifically supported waste management pilot system for the state. Direct waste sorting and characterization were conducted on the municipal solid waste arriving at the landfill during the study period. Over 50% of the generated wastes are recyclables and composed of plastics, metals, and paper, while the fraction of organic waste is over 30%. Similarly, the waste generation per capita is 1.34 kg/person/day, while the generation forecast over the next ten years is estimated to increase by approximately 40%. Furthermore, over 9,000 surveys were completed by residents to establish a problem statement about the existing waste collection and disposal system, and possible solutions. Importantly, a majority of survey respondents were willing to source-separate their wastes and supported paying a fee for adequate waste collection. This strongly indicates that an integrated waste management system could be established to generate value from the collected waste. Supplementary revenue can be generated through composting, recycling, and land reclamation. [ABSTRACT FROM AUTHOR]

Technological implementation and innovation represent essential pillars of contemporary society and are fundamental to its progress and evolution. In the urban development field, the concept of "smart city" rethinks the way of planning and managing cities by integrating emergent digital technologies that bring improvements in citizens’ way of life, while also increasing their efficiency, sustainability, and resilience. This paper aims to review a brief history of cities from ancient times until today, and the significant developments that determined the need for smart approach integration. For recent period, international and national trends and initiatives that impact smart city developments in Romania will be investigated. In addition, the innovative solutions promoted at the level of public administration will be highlighted by following the strategies and implementations in the phase of pilot projects, started or already used as prototypes, and private initiatives, as well as the impact of these smart approaches. For this purpose, an exploratory analysis is used at the level of multiple sources—town halls, county councils, various publications, specialized articles, magazines, companies, and non-governmental associations—following the mode in which the projects are framed on the thematics globally applied—people, economy, environment, governance, living, and mobility. Following the study, 1001 smart projects at the public level were identified in recent statistics, carried out by small, medium, and large cities in different stages of implementation. In addition, up-to-date private initiatives that led to urban transformation through the implementation of innovative solutions were pursued. [ABSTRACT FROM AUTHOR]

Urban regeneration is a sound, sustainable urban development strategy globally. In China, promoting urban regeneration has become the national sustainable urban strategy. Under the resource constraint, it is necessary to understand what benefits different types of urban regeneration projects can contribute to urban development. Much research has contributed to evaluating the benefits of urban regeneration on the project scale. The systematic investigation of their effects on surrounding economic vitality, especially the comparison between different types of projects, is relatively downplayed. This paper aims to evaluate and compare the effects of urban regeneration projects on surrounding economic vitality by calculating the change in housing prices. Chongqing is selected as the case city. Based on the housing transaction data from 2015 to 2021, a staggered difference-in-difference method is employed to capture the results. The finding shows that the overall effects are significantly negative, especially within a 400–800 m radius. Higher investment or better project location relates to stronger negative effects. Moreover, the differences in effects among the three types of urban regeneration projects are clearly revealed from diverse perspectives. It provides a valuable reference for policymakers and urban planners to make urban regeneration planning better by considering comprehensive benefits. [ABSTRACT FROM AUTHOR]

As one of the four major bay areas in the world, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a highly integrated mega urban agglomeration and its unparalleled urbanization has induced prominent land contradictions between humans and nature, which hinders its sustainability and has become the primary concern in this region. In this paper, we probed the historical characteristics of land use and land cover change (LUCC) in the GBA from 2005 to 2015, and forecasted its future land use pattern for 2030, 2050, and 2070, using a cellular automata–Markov (CA–Markov) model, under three typical tailored scenarios, i.e., urban development (UD), cropland protection (CP), and ecology security (ES), for land use optimization. The major findings are as follows: (1) The encroachments of build-up land on the other land uses under rapid urbanization accounted for the leading forces of LUCCs in the past decade. Accordingly, the urban sprawl was up to 1441.73 km2 (23.47%), with cropland, forest land, and water areas reduced by 570.77 km2 (4.38%), 526.05 km2 (1.76%), and 429.89 km2 (10.88%), respectively. (2) Based on the validated CA–Markov model, significant differences are found in future land use patterns under multiple scenarios, with the discrepancy magnified over time and driven by different orientations. (3) Through comprehensive comparisons and tradeoffs, the ES scenario mode seems optimal for the GBA in the next decades, which optimizes the balance between socio-economic development and ecological protection. These results serve as an early warning for future land problems and can be applied to land use management and policy formulation to promote the sustainable development of the GBA. [ABSTRACT FROM AUTHOR]

Urban carbon emissions are an important area for addressing climate change, and it is necessary to establish scientific and effective carbon emission prediction models to formulate reasonable emission reduction policies and measures. In this paper, a novel model based on Lasso regression, an ARIMA model, and a BPNN is proposed. Lasso regression is used to screen the key factors affecting carbon emissions, and the ARIMA model is used to extract the linear components of the carbon emission sequences, while the BPNN is used to predict the residuals of the ARIMA model. The final result is the sum of that from the ARIMA model and the BPNN. The carbon peak, carbon neutralization time, and emissions were analyzed under different scenarios. Taking Suzhou City as an example, the results show that the electricity consumption of the whole population is one of the key drivers of carbon emissions; the carbon emission prediction accuracy and stability of the ARIMA-BPNN combined model are better than those of the single model, which improves the reliability as well as the accuracy of the model's prediction. However, under the constraints of the current policies, the goal of achieving carbon peaking by 2030 in Suzhou City may not be realized as scheduled. This novel carbon emission prediction model built was validated to provide a scientific basis for low-carbon urban development. This study presents an important reference value for predicting carbon emissions and formulating emission reduction measures in other cities. [ABSTRACT FROM AUTHOR]

This study explores the architectural and demographic dynamics of Jerusalem, examining public discourse to determine the presence of neo-colonial ethnic segregation and socio-spatial divisions. Furthermore, it aims to discern the underlying motivations influencing urban architecture and to identify challenges within Jerusalem's demographic and architectural frameworks. Approach of the study encompasses an extensive review of academic publications, news articles, and both qualitative and quantitative data. The study includes documentation and archival research published in both international and national journals. Significant focus is placed on studies from global and regional organizations such as UNESCO, ICOMOS, the UN, IPCC, the EU, Friedrich Ebert Stiftung (FES), UNICEF in the State of Palestine, and various urban delineation and conservation projects by TİKA across the Jerusalem (al-Quds) metropolitan region. The paper critically assesses the city's evolution into a space characterized by ethnonational divisions, heightened militarization, and increasing violence, which suggest a shift from an 'ethnocracy' to an 'urban apartheid.' Finally, this paper proposes transitioning from 'ethnocracy' to 'democracy' as a solution for achieving a truly modern and democratic Jerusalem metropolis. [ABSTRACT FROM AUTHOR]

Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an 'Urban Laboratory' as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project 'El Campo de Cebada' in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities. [ABSTRACT FROM AUTHOR]

The significance of air quality monitoring for analyzing impact on public health is growing worldwide. A crucial part of smart city development includes deployment of suitable air pollution sensors at critical locations. Note that there are various air quality measurement instruments, ranging from expensive reference stations that provide accurate data to low-cost sensors that provide less accurate air quality measurements. In this research, we use a combination of sensors and monitors, which we call hybrid instruments, and focus on optimal placement of such instruments across a region. The objective of the problem is to maximize a satisfaction function that quantifies the weighted closeness of different regions to the places where such hybrid instruments are placed (here weights for different regions are quantified in terms of the relative population density and relative PM 2.5 concentration). Note that there can be several constraints such as those on budget, the minimum number of reference stations to be placed, or the set of important regions where at least one sensor should be placed. We develop two algorithms to solve this problem. The first one is a genetic algorithm that is a metaheuristic and that works on the principles of evolution. The second one is a greedy algorithm that selects the locally best choice in each iteration. We test these algorithms on different regions from India with varying sizes and other characteristics such as population distribution, PM 2.5 emissions, or available budget. The insights obtained from this paper can be used to quantitatively place reference stations and sensors in large cities rather than using ad hoc procedures or rules of thumb. [ABSTRACT FROM AUTHOR]

Wind comfort is an important factor when new buildings in existing urban areas are planned. It is common practice to use computational fluid dynamics (CFD) simulations to model wind comfort. These simulations are usually time-consuming, making it impossible to explore a high number of different design choices for a new urban development with wind simulations. Data-driven approaches based on simulations have shown great promise, and have recently been used to predict wind comfort in urban areas. These surrogate models could be used in generative design software and would enable the planner to explore a large number of options for a new design. In this paper, we propose a novel machine learning workflow (MLW) for direct wind comfort prediction. The MLW incorporates a regression and a classification U-Net, trained based on CFD simulations. Furthermore, we present an augmentation strategy focusing on generating more training data independent of the underlying wind statistics needed to calculate the wind comfort criterion. We train the models based on different sets of training data and compare the results. All trained models (regression and classification) yield an F 1 -score greater than 80% and can be combined with any wind rose statistic. [ABSTRACT FROM AUTHOR]

This paper applies Fuzzy Cognitive Maps (FCMs) to understand the diverse behavior of municipal governments in Ecuador to find common elements that influence the well-being of citizens in the short and long term. Information gathering was conducted in two stages: in the first one, a group of 16 national experts was consulted to develop the initial FCM; in the second stage, local experts from 220 municipalities were interviewed to collect information on the general validity of initial FCMs and specific values given to concepts and relationships in their municipalities. Results show the importance of certain concepts for long-term municipal performance, such as the need for a competitive entrepreneurial sector, improving human resources in the municipality, and, particularly, having a competent mayor with leadership skills and a forward-looking vision that enables the development of municipal projects required to reach an efficient and equitable coverage of goods and services throughout the city. Through the application of genetic algorithms, the FCM was calibrated to ascertain the long-term dynamics of municipal development and the optimal values of the concepts that would optimize the attainment of the set objectives. The derived outcomes suggest the desirability of the maintenance of, in principle, unwanted structures like financial transfers from the central government and the need to exploit natural resources to attain urban development. [ABSTRACT FROM AUTHOR]

China has experienced significant urbanization during the past 40 years, which exerts impacts on regional climates through changing land surface properties. Previous studies mainly focused on the Pearl River Delta, the Yangtze River Delta, and the Beijing-Tianjin-Hebei areas, while less attention has been paid to central China. In this paper, the regional climate effects of urbanization around the greater Wuhan area were investigated using the WRF model. High resolution, satellite-derived, impervious datasets were used to generate two realistic scenarios representing urban surface states of the years 1986 and 2018. By comparing the simulation results of two sensitivity experiments from 1 July 2015 to 12 July 2015, the spatial and diurnal changes in surface air temperature, surface skin temperature, and surface energy budget were analyzed. Our results reveal that urban expansion leads to 2 m air temperature and surface skin temperature increases by approximate 0.63 °C and 0.83 °C, respectively. Surface sensible heat flux increases, while latent heat flux decreases, with much greater effects in daytime than nighttime. The planetary boundary layer height (PBLH) increases with its maximum value over 100 m, and a 2 m water vapor mixing ratio decreases with a peak value around −2 g/kg. These findings provide knowledge to improve the understanding of land–atmospheric interactions and pave the way to studying urban expansion effects under future climate change scenarios. [ABSTRACT FROM AUTHOR]

This paper explores the integration of 3D documentation within a living lab framework for the renovation of the Gunsan Civic Cultural Center. The study emphasizes the importance of architectural renovation in contemporary sustainability and social resilience, highlighting the unique challenges of adapting existing structures. Our approach combines advanced 3D scanning techniques, such as drone filming, photogrammetry, LiDAR scanning, and hybrid modeling, with the living lab methodology, enabling real-world experimentation and stakeholder engagement. Our showcase on the Gunsan Civic Cultural Center illustrates the practical application of these techniques in material reuse and cultural performance planning, emphasizing community participation and collaborative decision-making. The living lab approach, central to our methodology, fosters dynamic interaction among architects, builders, community members, and local authorities, enhancing communication and project outcomes. This study contributes to the field by showcasing how concurrent 3D documentation in a living lab setting can revitalize heritage sites, ensuring their sustainable future while actively involving the community. The lessons and discussions drawn from this project highlight the potential of this approach in broader architectural and urban development contexts. [ABSTRACT FROM AUTHOR]

Change Detection (CD) provides a research basis for environmental monitoring, urban expansion and reconstruction as well as disaster assessment, by identifying the changes of ground objects in different time periods. Traditional CD focused on the Binary Change Detection (BCD), focusing solely on the change and no-change regions. Due to the dynamic progress of earth observation satellite techniques, the spatial resolution of remote sensing images continues to increase, Multi-class Change Detection (MCD) which can reflect more detailed land change has become a hot research direction in the field of CD. Although many scholars have reviewed change detection at present, most of the work still focuses on BCD. This paper focuses on the recent progress in MCD, which includes five major aspects: challenges, datasets, methods, applications and future research direction. Specifically, the background of MCD is first introduced. Then, the major difficulties and challenges in MCD are discussed and delineated. The benchmark datasets for MCD are described, and the available open datasets are listed. Moreover, MCD is further divided into three categories and the specific techniques are described, respectively. Subsequently, the common applications of MCD are described. Finally, the relevant literature in the main journals of remote sensing in the past five years are analyzed and the development and future research direction of MCD are discussed. This review will help researchers understand this field and provide a reference for the subsequent development of MCD. Our collections of MCD benchmark datasets are available at: [ABSTRACT FROM AUTHOR]

This paper introduces a deep learning (DL) tool capable of classifying cities and revealing the features that characterize each city from a visual perspective. The study utilizes city view data captured from satellites and employs a methodology involving DL-based classification for city identification, along with an Explainable Artificial Intelligence (AI) tool to unveil definitive features of each city considered in this study. The city identification model implemented using the ResNet architecture yielded an overall accuracy of 84%, featuring 45 cities worldwide with varied geographic locations, Human Development Index (HDI), and population sizes. The portraying attributes of urban locations have been investigated using an explanatory visualization tool named Relevance Class Activation Maps (CAM). The methodology and findings presented by the current study enable decision makers, city managers, and policymakers to identify similar cities through satellite data, understand the salient features of the cities, and make decisions based on similarity patterns that can lead to effective solutions in a wide range of objectives such as urban planning, crisis management, and economic policies. Analyzing city similarities is crucial for urban development, transportation strategies, zoning, improvement of living conditions, fostering economic success, shaping social justice policies, and providing data for indices and concepts such as sustainability and smart cities for urban zones sharing similar patterns. [ABSTRACT FROM AUTHOR]

The coexistence of urban expansion and shrinkage in China has become increasingly apparent; therefore, the current strategic model of growth-oriented urban planning as the top-level design needs to be adjusted. This paper focuses on the city of Baishan, which is a typical shrinking city in China, and explores the feasibility of implementing the concept of smart shrinkage planning in shrinking cities in China by constructing a coupled PLUS-SD model. The results demonstrate the following conclusions: (1) The overall simulation of the coupled PLUS-SD model is superior to that of the PLUS model. In Baishan, the areas with the most changes in construction land will be located at the edges of the landforms by 2030. (2) Using the traditional planning scenario would only exacerbate the rate of construction land expansion in Baishan, deepening the incongruity between the city's population and construction land. (3) The smart shrinkage scenario will require strict control of the scale of construction land and optimization of the structure of the urban construction land, which would push the city in the direction of healthy and sustainable development. (4) The concept of smart shrinkage planning is a scientific and feasible plan for realizing the efficient and sustainable use of construction land in shrinking cities. [ABSTRACT FROM AUTHOR]

In recent decades, the analysis of different geographic scales for studying the spatial patterning of crime has profoundly deepened our theoretical grasp of crime dynamics. However, a similar investigation is lacking when it comes to the patterning of offender residences, despite there being clear theoretical and empirical reasons for doing so, among them, the close relationship between where offenders live and where their corresponding crimes are committed. This paper delves into the concentration and variance of offender residences across different levels of spatial aggregation. The data used contains the locations of residence for known offenders in Birmingham between the years 2006 and 2016. Resident locations are aggregated to Output Areas (OA), nested within Lower Super Output Areas (LSOA), further nested within Middle Super Output Areas (MSOA). Descriptive and model-based statistics are deployed to quantify concentration and variation at each spatial scale. Results suggest that most variance (48%) in offender residence concentrations is attributable to the largest spatial scale (MSOA level). Output Areas capture approximately 38% of the variance. Findings open up discussions on the role of urban development in determining the appropriateness of spatial scale. [ABSTRACT FROM AUTHOR]

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As a unit hydrograph method widely used in engineering practice, the synthetic unit hydrograph of Guangdong is obtained from the analysis and synthesis of rain and flood data before 1983, which reflects the production-confluence relationship before urbanization in Guangdong Province. However, there are few studies on the evaluation and modification of its applicability in urbanized areas. Taking Jing-tian Watershed of Shenzhen City, Guangdong Province as an example, based on the rainstorm and flood records of Jingtian Hydrology Station from 2011 to 2019, this paper evaluates the applicability of the comprehensive unit line in Guangdong Province by using evaluation indexes such as Nash efficiency coefficient, identification index and correlation coefficient, and conducts a sensitivity analysis of important parameters by Spearman rank correlation coefficient method. Based on Latin hypercube sampling method and constrained least square method, the comprehensive unit line method of Guangdong Province is modified. The results show that the Jingtian Basin has experienced rapid urban expansion since the 1980s, and the proportion of impervious surface has exceeded 90%. The comprehensive unit line method in Guangdong Province has obvious shortcomings in describing the storm-flood process in this basin. The two schemes proposed in this paper can improve the simulation effect of the model by determining important parameters and modifying the unit line. Among them, the cross-validation parameter optimization method based on grid search and the unit line correction method based on constrained least square method proposed for small samples show a good simulation performance, and the indexes such as Nash efficiency coefficient, identification index and correlation coefficient are significantly improved, which better reflects the characteristics of production and convergence in Jingtian Basin. Compared with the recommended unit line of the integrated unit line method in Guangdong Province, the modified unit hydrograph method shows the characteristics of larger peak discharge, earlier peak time and smaller total duration, which is more in line with the law of production and confluence of urbanization. [ABSTRACT FROM AUTHOR]

Coastal spaces are shaped by human activity. Approaching their urban spaces allows us to analyse the concepts of structure, growth, and management. Highlighting the problems associated with these concepts can lead to intensive scientific analysis and provide solid research methods. This paper focuses on the study of how the process of territorial occupation takes place and the urban forms it generates on the Spanish Mediterranean coast. It is based on the consideration that the process of territorial occupation is deficient in its territorial adequacy. To analyse this, a methodology is proposed that addresses processes of analysis at different scales: dynamics of changes in land use, the study of the morphologies of urban development with spatial analysis tools, and the adaptation of urban processes to the characteristics of the spaces that support them with multi-criteria evaluation techniques and GIS (Geographical Information Systems). The results are specified in five degrees of suitability of the occupation of the territory. Two conclusions can be observed: first, urban planning gives rise to forms of occupation that follow a similar pattern in the twenty areas studied, and second, the suitability of the urban process is not governed by planning based on precepts of suitability and environmental logic but by a weakness of the adapted planning methods. [ABSTRACT FROM AUTHOR]

New territorial units resulting from urban sprawl processes constitute a major challenge for territorial planning. The aim of this paper is to analyze periurban spaces, focusing on the delimitation and characterization of the urban units arising from urban sprawl processes. The delimitation derives from fractal analysis, where urbanized space is used to detect the limits of the units. The characterization starts with the calculation of eight different indicators, using Geographic Information Systems tools. PCA is used to obtain different dimensions of the urban sprawl phenomenon. Finally, a cluster analysis has been applied to establish a typology of territorial units and facilitate the comparative analysis. The methodology is applied to a case study, the metropolitan area of Valencia. Results show six groups of urbanized spaces, which present different types of urban sprawl structures with different necessities. This applied research can be useful for the spatial planning of the periurban spaces, insofar as it allows the identification of supra-municipal or infra-municipal areas, where it will be possible to improve infrastructures, facilities, or green infrastructure, to empower secondary urban nuclei and to create new inter-municipal cooperation and governance formulas. In addition, the results can constitute a non-administrative territorial basis for the calculation of land occupation indicators that are often used as thresholds for the creation of new residential spaces in regulatory planning documents. [ABSTRACT FROM AUTHOR]

With the development of information technology, such as cloud computing and 5G technologies, the construction of smart cities has been an essential part of the city's long-term development strategy for the 14th five-year plans in China. After a few years of development, the research problem of the dynamic performance assessment of smart cities has been a hot and urgent issue. This paper constructed the dimensions of smart productivity, smart livability, smart governance, and eco-community based on the connotations of smart cities. Then, an indicator system including 35 indicators was built based on the four dimensions. To enlarge the overall differences of the final assessment values, we used the vertical and horizontal deviation maximization (VH-DM) method to measure the performances of 31 smart cities in China from the year 2014–2018. Two essential findings and driving indicators were identified from the assessment results. Firstly, the development among the smart cities was unbalanced and more than half of the smart cities (accounting for 64.52%) were below the average level. The local authorities considered the urban agglomeration strategies to alleviate the problem of unbalanced urban development. Secondly, some smart cities (such as Chongqing) with large scale of population and total resources showed a low level after the total resources were allocated to per capita, which provided a warning for the smart cities to pay more attention to individual development. The local authorities have proposed the high-quality development strategies to deal with such problems. [ABSTRACT FROM AUTHOR]

Land use modelling is essential to understanding future land use and change dynamics. Analyses of land use and change using Cellular Automata (CA) have been frequent in the literature since the latter were introduced to geography in the 1970s. In this paper, the statistical subsections – city blocks – of a previous analysis of Lisbon's commercial structure are used as the cells of a CA. A multi-layer perceptron (MLP) models the transition potential of those cells between 1995 and 2020, considering the impact of street centrality, subway development and other proxies of urban growth. The results confirm that commercial growth and change can be simulated as a function of street centrality and that using Local integration and Choice as drivers of a CA may help improve predictions of commercial growth and change. Moreover, the CA results reinforce that street centrality positively affects street commerce, especially when combined with access to transit and amenities. While these results can already inform planning practice and policymaking, the framework presented in this paper may be replicated to simulate ​future commercial land use, thus helping planners and policymakers prepare for change.

Driven by the goal of achieving sustainable development and carbon neutrality. Addressing environmental pollution and remediating land damage have become critical challenges in resource-based cities and regions with low land use efficiency. As a response, this study focuses on the 23 provinces where China's coal resource-based cities are situated. Utilizing data from 2014 to 2020, this research employs the SBM-Undesirable model, which considers undesirable outputs in efficiency calculations, and the Tobit regression test. It aims to explore the spatio-temporal variations in industrial transformation within resource-based cities and its impact on the efficiency of green space utilization. Furthermore, it analyzes the characteristics and the extent of the influence of factors such as industrial structure adjustments on urban land use efficiency, maximizing the output of land as a factor of production. The results show that: (1) Over the 7-year period studied, China consistently made nationwide adjustments to land area and land use structure to meet the needs of urban development (2) The regression test results show that the industrial transformation of resource-based cities can promote the improvement of green space utilization efficiency. The positive influence coefficient is 0.064 and is significant at a 1% level. (3) Environmental regulation, government expenditure, international trade, and green cover play a positive role in promoting green land use. The study provides valuable insights for policymakers and urban planners seeking to foster sustainable development in resource-based cities. [ABSTRACT FROM AUTHOR]

The aim of this study was to create a dataset of building locations in Poland from the 1970s–1980s. The source information was the historical 1:10 000 Polish topographic map. Building footprints were detected and extracted from approximately 8,500 scanned map sheets using the Mask R-CNN model implemented in Esri ArcGIS Pro software, and converted to point building locations. The dataset of building locations covers the entire country and contains approximately 11 million points representing buildings. The accuracy of the dataset was assessed manually on randomly selected map sheets. The overall accuracy is 95% (F1 = 0.98). The dataset may be used in conjunction with various contemporary land use, land cover and cadastral datasets in a broad range of applications related to long-term changes in rural and urban areas, including urban sprawl and its environmental and social consequences. It can also serve as a highly reliable reference dataset for regional or global settlement products derived, e.g., from early Landsat data. [ABSTRACT FROM AUTHOR]

This paper, set against the backdrop of expanding urban rail networks and dynamic urban development, focuses on the distribution and evolution of commercial Points of Interests (POIs) within the central urban rail transit areas of Beijing. The study examines data from four different years—2008, 2013, 2017, and 2020—to observe the temporal evolution of commercial entities. It identifies stable explanatory variables affecting the distribution and evolution of commercial POIs, which include rail transit accessibility, characteristics of the working and residential population distribution around stations, and the construction intensity in the vicinity of station areas. Through statistical analysis and model building, relatively stable linear regression equations were established, with R 2 values generally maintained above 0.5 (except for 2017). The study advances our understanding of the influence of rail transit on urban commercial spaces and how this influence shifts with temporal and urban developmental changes. It elucidates the correlation between changes in the number of businesses and spatial configuration, offering insights and information for urban planners and policy makers. This research also serves as a model for exploring the interplay between urban rail transit and commercial spaces in other major cities. [ABSTRACT FROM AUTHOR]