Urban Structure Research Articles

Wide area maps of building differential deformations

Abstract. The European Ground Motion Service (EGMS) uses Sentinel-1 data to monitor and measure land displacement across Europe, delivering information on ground motion phenomena. The EGMS service includes three types of products, enabling the analysis of annually updated ground motion data. The authors are working on a project aimed at computing the spatial gradient of land deformation and generating wide-area differential deformation maps. This type of maps can help identifying potentially vulnerable buildings and urban structures. The project involves developing a software pipeline to compute and convert original deformation data and creating a customized web viewer to display the results. Given the large volume of the processed datasets, with several millions of measurement points an accurate algorithm implementation is needed. The resulting information will aid in monitoring anthropogenic phenomena and their impact on building and infrastructures. This will be essential for urban management and risk mitigation planning.

Prediction and Scenario Simulation of Carbon Emissions Peak of Resource-Based Urban Agglomeration with Industrial Clusters—Case of Hubaoe Urban Agglomeration Inner Mongolia Autonomous Region, China

China has implemented a “dual-carbon” policy in response to the Paris Agreement’s global climate change objectives. Hohhot, Baotou, and Ordos (HBO-UA) is a resource-based urban agglomeration that is noteworthy for having significant heavy industry in China. Based on the extended STRIPAT model, which broadens the study indicators into six aspects—population, economics, technology, urbanization, industrial energy, and industrial structure—this paper develops a research framework of “Driving–Predicting–Simulating” for carbon emissions. According to the “one formula for one city” principle, driver models were constructed for Hohhot, Baotou, and Ordos, respectively. The following conclusions were drawn: (1) Population and urbanization are the dominant factors of carbon emissions in HBO-UA, following the economy and industrial energy. (2) Carbon emissions are multifactor-driven in Hohhot, double-factor-driven in Baotou, and single-factor-driven in Ordos. (3) Hohhot can achieve its carbon emissions peak under more efficient and lower policy costs, while Ordo is under great pressure to reduce carbon emissions. (4) We suggest multiple strategies to accomplish the “dual-carbon” goals for resource-based urban agglomeration with industrial clusters. These strategies include fostering diversified consumption by continuously enhancing urban functions, directing the transformation of the industrial structure, and fostering the growth of emerging industries.

A longitudinal study of evolving polycentric pattern in Shanghai

In the context of technological progress and economic transition, the urban spatial structure has consistently undergone dynamic evolution. However, the trajectories of polycentric patterns display significant national and regional variations. It is crucial to examine the dynamic evolution of spatial structures within Chinese metropolitan areas amidst economic transitions. Focusing on the Shanghai Metropolitan Area (SMA), this study investigates the temporal dynamics of job distribution and employment centres and considers industry differentiation to understand the evolution of polycentric patterns. Additionally, spatial regression models are utilized to probe the intrinsic mechanisms through which adjustments in industrial structure influence spatial evolution. The findings indicate that both the service and manufacturing sectors have the potential to concentrate employment and form subcentres in the SMA. Nevertheless, within the economic transition context, the downtown area, dominated by the service sector, underwent specialized development, fostering continuous prosperity and the emergence of employment subcentres in the periphery. In contrast, employment centres in suburban areas, dominated by the manufacturing sector, experienced a declining trend. Consequently, the locations of employment clusters in the SMA shifted, concurrently reshaping the relationships between the main centre and subcentres and leading to a transformation from a weaker separated polycentric pattern to a stronger continuous polycentric pattern. This paper elucidates the underlying mechanisms through which industrial transition influences urban spatial structure, offering insights into the evolution of polycentric patterns in the postindustrial era from a local Chinese perspective.

Research on Multi-Scenario Simulation of Urban Expansion for Beijing–Tianjin–Hebei Region Considering Multilevel Urban Flows

With the development of urban agglomerations in China, the study of the interactions between cities has become a popular and difficult issue. Exploring the interactions between cities can help decision-makers optimize regional resource allocation and improve regional spatial patterns. Combining the urban flow model and the patch-generating land use simulation (PLUS) model, this study simulates and analyzes the process of urban expansion in the Beijing–Tianjin–Hebei (BTH) region, and investigates the impact of urban hierarchical structure differences on urban expansion. In this study, the role and influence of inter-city economy flow, transportation flow, population flow, and information flow on the development of urban agglomerations are comprehensively considered, and a multilevel urban interaction model is constructed based on a hierarchical generalized linear model (HGLM). Based on the national BTH cooperation and development strategy, a multi-scenario simulation study of urban expansion is carried out using the HGLM-PLUS model. The results indicate the following: (1) compared to the traditional PLUS model, the coupled HGLM-PLUS model, which considers multilevel urban flows, improved the overall accuracy by 0.047, the Kappa coefficient by 0.207, and the figure of merit (FoM) index by 0.051; (2) under different simulation scenarios, the development trend under the cooperation and development policy in the BTH region is more stable, demonstrating a relatively smooth urbanization expansion trend; and (3) under the BTH cooperation and development background, the total area of construction land in the BTH region is expected to be maintained at around 1,164,500 km2 by 2040. The spatial expansion pattern will present a networked expansion with the core driving development, axes and belts connecting, and clusters breaking through.

The Axial City: disjunctioning radical pluralities from an urban galaxy

ABSTRACT In 1999, the City Council of Brescia (Northern Italy) approved the construction of the city’s inaugural subway line, which began operating in 2013. Since its inception, the subway has been reshaping Brescia’s urban structure. Its aim was to spatially integrate essentials urban services into a seemingly cohesive and post-industrial socio-spatial system, a process that have been termed as urban wholing. However, wholing dynamics have simultaneously solidified and splintered the city’s urban structure. Over the last decades, Brescia has evolved into an “Axial City” socio-spatially governed through the regimented mobilities emanating from the subway. This configuration is spatially marked by the presence of “hierarchized centralities” that disproportionately catalyze investments and development policies. Furthermore, the subway system establishes distinct patterns of socio-spatial (dis)junction, defining different areas as “(dis)integrated ecologies” from the city-as-a-wholed. Via this approach, the processes of wholing generate mobilities according to normative class, racial, gendered, and age-related urban relations, transforming the Axial City into a comprehensive system fueling unprecedent conditions of selective (dis)integration and “kinetic segregation.” This contribution explores the governmentality expressed by the Brescia’s infrastructure, emphasizing how the socio-spatial processes of splintering radical pluralities, intrinsic to the efforts towards wholing, are crucial conditions of injustice permeating the contemporary city’s political project.

Elite poems and mass proverbs: exploring the historic landscape in Nanchang City, China

The rapid process of urbanisation has led to the erosion of the preservation of features of urban landscape. Research on historical landscapes in ancient urban planning has predominantly concentrated on the elite class, neglecting the broader population. Nanchang, a city with a history spanning over two millennia of urban development, is the focus of this study. The study integrates elite poems and mass proverbs through GIS spatial matching and KH Coder word frequency analysis to research the historic landscape in Nanchang City. The research uncovers that the elite class focuses on the historical, literary, and aesthetic aspects of Nanchang, while the masses emphasise urban structure, functionality, and aspirations. These dual perspectives underscore Nanchang’s evolution from inception to formalisation, highlighting its ability to cater to diverse societal needs. The efforts on the distribution of landscape spots and strict modulus reflect the adaptability and sustainability of Nanchang City.

Towards urban LCA: examining densification alternatives for a residential neighbourhood

This paper explores the environmental impacts of retaining or replacing buildings by extending the consequential replacement framework (CRF) for life-cycle assessment (LCA) from individual buildings towards the urban scale. It addresses a gap in previous studies by examining the broader consequences of building-level retention or replacement decisions in the built environment, namely greenhouse gas (GHG) emissions from associated infrastructure construction. The case study, which is located in Finland, investigates alternative ways to densify a growing city, some of which can be achieved within the urban structure, while others require greenfield construction elsewhere in the city. The results reveal that refurbishing and extending already existing buildings is worthwhile in terms of GHG emissions, even if some of the additional floor area targeted in densification were to be built on a greenfield site. After 50 years, the accumulated GHG emissions of scenarios that develop existing buildings are 0.2–12% less than those from replacement scenarios, depending on whether the targeted densification is minor or major and the amount of infrastructure construction involved. This is primarily due to the 11–35% smaller upfront embodied GHG emissions of refurbishment compared with new construction—which 50 years do not offset. Policy relevance This paper reinforces the notion from previous research that developing the existing building stock holds major emission-savings potential, even more so than replacement with energy-efficient new build. It highlights the potential contribution of existing building stocks in low-emission city development, even in growing city contexts. The case study results challenge the common belief in urban planning that if replacement involves densification, it must be a more low-emission alternative than retention, and conversely, if retention leads to greenfield construction, it must be higher in emissions than replacement. Low-emission urban planning should base its conclusions on urban LCA. This paper introduces an infrastructure-extended CRF that accounts for building retention and replacement scenarios, ensuring methodological robustness. The approach is essential for policymakers to base their decisions on evidence and prioritise low-emission development alternatives. Which policymakers hold power over such decisions and which instruments are suitable to pursue these goals depend on the context.

Alleviating the resolution limit problem in spatial community detection: a local network structure-based method

Spatial community detection plays a crucial role in the analysis of spatially embedded networks. However, most existing methods adopt modularity as an objective function, which may fail to detect small spatial communities (i.e. the well-known resolution-limit problem). To alleviate this problem, a local network structure-based spatially constrained Leiden method was developed. First, the weights of the edges were reset based on the local network structure, which facilitated a clearer delineation between distinct communities. Second, we extended Leiden, an effective community detection method, to spatial community detection content by adding spatial constraints. Experiments on simulated datasets demonstrated that the proposed method is superior to four state-of-the-art methods for detecting spatial communities of different sizes. A case study conducted using the Shenzhen taxi dataset demonstrated that the proposed method outperformed four state-of-the-art methods in revealing urban spatial structures. Notably, the modularity of the spatial communities detected using the proposed method exhibited a marked improvement, nearly doubling that of the four comparative methods in the case study. This study presents a novel and promising framework for detecting spatial communities using modularity.

The Impact of Urban Industrial Structure on Citizen Income: Evidence from China

Technology advancements and the rise of new sectors have caused a steady shift in the urban industrial structure of cities. It is crucial to adopt effective policies to ensure that the industrial structure is conducive to economic development. This study aims to investigate the specific impact of urban industrial structure on residents’ income and how it promotes economic development from the individual level to the city level. Based on data from 5900 prefecture-level cities from 2003 to 2022, the empirical results show the following: (1) Urban industrial structure can significantly benefit both urban and rural residents’ income positively, albeit with a larger marginal effect for urban residents. (2) Enhancing urban industrial structures, rationalizing industrial structures, and upgrading industrial structures can considerably close the economic disparity between urban and rural areas in the corresponding locations. In light of these findings, policymakers should prioritize optimizing urban industrial structures for broader income growth. Balancing industrial reforms between urban and rural areas is crucial for sustainable economic development.

Non-locality and spillover effects of residential flood damage on community recovery: Insights from high-resolution flood claim and mobility data

Examining the relationship between vulnerability of the built environment and community recovery is crucial for understanding disaster resilience. Yet, this relationship is rather neglected in the existing literature due to limitations in the availability of empirical datasets needed for such analysis. In this study, we combined fine-resolution flood damage claim data (composed of both insured and uninsured losses) and human mobility data (composed of millions of movement trajectories) during the 2017 Hurricane Harvey in Harris County, Texas, to specify the extent to which vulnerability of the built environment (i.e., residential flood damage) affects community recovery (based on the speed of human mobility recovery) locally and regionally. We examined such relationship using spatial lag, spatial reach, and spatial decay models to measure the extent of spillover effects of residential flood damage on community recovery. The results indicate that: first, the severity of residential flood damage significantly affects the speed of community recovery. A greater extent of residential flood damage suppresses community recovery not only locally but also in the surrounding areas; second, the spillover effects of residential flood damage on community recovery decay with distance from the highly damaged areas with a spatial reach of up to 31.2 miles (49.92 Km); third, areas display heterogeneous spatial decay coefficients, which are associated with urban form and structure features such as the density of facilities and roads. These findings provide a novel data-driven characterization of the spatial spillover effects of residential flood damage on community recovery and move us closer to a better understanding of complex spatial diffusion processes that shape community resilience to hazards. This study also provides valuable insights for emergency managers and public officials seeking to mitigate the non-local effects of flood damage.

Practical aspects of morphological research in urban renewal projects

The small towns of North-Eastern Germany suffered great losses in historic buildings and economic dynamics during the Second World War and the subsequent decades of communist rule. Since 1990, these communities have suffered a major decrease in the number of inhabitants, resulting in a large number of buildings being empty. To adjust the urban structure to twenty-first century standards and regain economic vitality, both regional and local governments are supporting urban renewal projects. Sites inside medieval town centres are under pressure to amalgamate and be recreated as large-scale developer architecture or to fall into ultimate decay. As part of the study of medieval urban structures, a study of the site of the former Holy Spirit Hospice (Heiligengeist-Quarter) of Woldegk has been carried out. This paper shows how contextualization and a re-definition of the site, based on historic narratives developed by morphological research, inspired authorities and stakeholders to initiate a narrative-based development of the site. It demonstrates that urban renewal, based on historic narratives, creates wide public support for contemporary redevelopment in small urban communities. It further shows how morphological research is contributing to the establishment of relevant narratives.

Integrating carbon reduction and ecological resilience strategies in the silk road economic corridor

The Silk Road Economic Belt has become a pivotal region for China's sustainable development, focusing on the balance between carbon emissions and ecological resilience. Understanding the coordination between these factors is crucial for advancing China's westward economic shift and optimizing urban and demographic structures. This study investigates the coupling and coordination dynamics between carbon emissions and ecological resilience across 15 key cities in the Silk Road Economic Belt, using data from 2008 to 2018. By applying a "pressure-state-response" framework, the ecological resilience of the region is quantitatively assessed. Spatial disparities and the dynamic evolution of coupling coordination are analyzed through the Gini coefficient and kernel density estimation. The findings reveal significant regional variations in ecological resilience and a decline in coupling coordination over time. Shifts in the patterns of coordination indicate opportunities for enhancing resource utilization and environmental management. This research provides theoretical insights for policymakers to improve green development strategies, optimize industrial structures, and plan urban green spaces more effectively within the Silk Road Economic Belt.

How workable is a 20-minute city in Australia? Re-examining the challenge of change in spatial labour and job relations

ABSTRACT Most x-minute city studies focus on liveability and neighborhood accessibility to local services, but rarely include primary employment. This paper complements these studies by examining the urban employment structure and transport dynamics of an Australian city under the 20-minute city concept framework. To do this, we develop a comprehensive method to model residents’ job access time using census-based journey to work (JTW) data and detailed household activity and travel survey. Analysing JTW time stepping down to diverse industry and employment categories and transport modes allows new insight into the disparity in residents’ job and housing locations and transport choices at local scales. By evaluating the distribution of working residents, types of employment, and transport performance, this paper examines possible policy responses and challenges of change in expanding the 20-minute planning target for employment. The analysis suggests that housing infill development could support reduced JTW time for residents experiencing longer time for work travels. However, this would require active planning of both land-use mix and dwelling design to meet prevalent household expectations about dwelling size and quality.

Climate Change and Cities of Lithuania: Threats, Problems and Prerequisites for Solution

The emerging threats of climate change and their impacts on cities and residents are increasingly highlighting the need to assess whether countries are adequately prepared for the potential consequences of this process. While many international agreements on climate change, sustainable development and environmental protection have been adopted, countries often face various local obstacles that hinder their implementation. To address these issues, this paper reviews the climate change projections, emerging threats and hazards in Lithuania and their potential impacts on the country’s cities and highlights the main challenges in preparing for these growing threats. This article presents an evaluation of the climate change forecasts and past climate events in three selected Lithuanian cities—Vilnius, Kaunas and Klaipėda. The study includes a diagnostic assessment of the climate changes since 1961 and climate change forecasts up to 2100, based on the RCP4.5 and RCP8.5 scenarios, using regional and global climate models. It identifies the impacts of potential climate change consequences on cities, forming the basis for the evaluation of the urban situation in the country. The urban situation is assessed in terms of legislation, urban development, environmental requirements and the development of safety infrastructure. Based on the evaluation of urban development, preliminary proposals are provided for the creation of a resilient living environment. One of the key proposals in shaping the living environment—which could be particularly significant in adapting to emerging threats—is the complex formation of new, sustainable urban structures that take into account the social, ecological and economic factors of climate change and other rising threats.

Identification and Spatiotemporal Evolution Analysis of the Urban–Rural Fringe in Polycentric Cities Based on K-Means Clustering and Multi-Source Data: A Case Study of Chengdu City

Urban fringe areas, serving as transitional zones between urban and rural landscapes, are characterized by their transitional nature, high dynamics, and spatial heterogeneity. Identifying the extent of an urban–rural fringe (URF) and analyzing its evolutionary characteristics are crucial for urban planning and development. However, limited research exists regarding the identification of a URF and the analysis of its spatiotemporal evolution in polycentric cities. Using Chengdu as a case study, this research employed the K-means clustering method to identify the spatial extent and evolution patterns of the URF in Chengdu from 2010 to 2020 based on the spatiotemporal characteristics of multi-source data. The results indicate that (1) the K-means clustering method can reasonably and efficiently identify URF in polycentric cities; (2) Chengdu exhibited a polycentric urban structure with a “main center-subcenter” pattern, where the URF was adjacent to the main and subcenters, assuming an overall annular wedge shape; (3) there was a significant expansion of the URF in the northeast–southwest direction from 2010 to 2020, accompanied by substantial land use changes. The evolution of the URF was driven by the dual mechanisms of urban suburbanization and rural urbanization, exhibiting characteristics such as singular urban functions, dispersed and chaotic land use, fragmented landscapes, and increasing complexity. This study extended the research on URFs, aiding in the understanding of urban spatial growth patterns and providing decision support for the integrated development of urban and rural areas.

Analysis of Behaviour Pattern of Bicycle-sharing Users Based on Complex Network: a Case Study of Beijing Downtown Area

Abstract. The introduction of the Bicycle-sharing System (BSS) has provided great convenience for residents for short travel in city. However, the parking lot planning and bicycle logistics distribution remain suboptimal, adversely affecting traffic order. Studying the spatial and temporal usage patterns can be helpful for better management of BSS. In this paper, we propose an analytical framework for detecting the bicycle-sharing pattern based on the community detection algorithms from complex networks to study the spatial-temporal patterns of usage.Firstly we identify the potential demand for bicycle among urban residents with a dataset from the BSS in Beijing downtown area. Then we construct a linkage network for modelling the BSS by applying community detection algorithms to identify regions of both high and low connectivity. Following this, based on the division of sub-areas, three indicators (graph density, cross-area travel demand, and confidence ellipses) are established for characterizing these sub-areas. Our findings include: (1) The usage pattern of the BSS within the downtown area consistently exhibits relatively stable clustering phenomena over time. (2) The usage pattern is related to the urban spatial structure, with significant differences between weekdays and weekends. (3) Residents tend to complete their cycling within the current sub-areas. (4) Generally, smaller sub-areas tend to have denser bicycle travel behaviour. These insights are vital for improving BSS parking lot planning and logistics distribution.

Research on a Multi-Scale Clustering Method for Buildings Taking into Account Visual Cognition

Building clustering is a key problem that needs to be solved in the realization of the automatic synthesis of large-scale maps. The selection of different feature and spatial distance calculation methods has a great impact on the clustering results, and the need to manually select appropriate feature and distance metrics leads to the problem of not being able to fully consider the complexity and diversity of buildings. In this paper, we propose a multi-scale clustering method for buildings that takes visual perception into account using the Gestalt principle to simulate how humans classify buildings through visual perception. Moreover, by analyzing the spatial features and texture attributes of buildings, a visual distance is designed to be used as a condition for building classification to assess the similarity between buildings, solving the complexity of manually selecting feature vectors and spatial distances and realizing the adaptive selection of features. Through experimental validation at different scales (macro, meso and micro), the present method is able to achieve the accurate clustering of buildings, and a frequency threshold of 91% is found, which is able to determine the optimal clustering results. The experimental results show that the proposed method can not only fully consider the complexity and diversity of buildings but also effectively support the understanding and analysis of urban spatial structure and provide a scientific decision-making basis for urban planning and management.

The Miskolc Method: Modelling the Evolution of a Natural City with Recursive Algorithms Using Simulated Morphogenesis

This article explores the application of procedural design methods in urban morphology, drawing inspiration from the innovative work of the Architectural Workshop of Miskolc in Hungary during the late 20th century. This study presents a generative approach termed “Simulated Morphogenesis” (or the “Miskolc Method”), which models organic city growth by analysing historical urban tissues and applying recursive algorithms to simulate natural urban development. The method leverages advanced generative tools, such as Rhinoceros 3D and Grasshopper, to model the step-by-step growth of Central European cities, with a particular focus on Miskolc. By incorporating controlled randomness into the algorithmic processes, the method captures the complexity of organic urban growth while maintaining structured development. The Miskolc Method emphasizes the importance of continuity and context, allowing for the “healing” of urban fabric discontinuities or the generation of new urban structures. This article demonstrates how this approach, while rooted in geometrical analysis, offers a valuable foundation for preliminary urban planning. The findings are relevant for understanding the morphogenesis of cities and provide a flexible framework applicable to various urban contexts globally.

Research on Smart City Road Network Capacity Optimization Configuration Based on Deep Learning Algorithms

At present, the urban traffic system is faced with the problems of congestion and low efficiency, and the traditional methods have certain limitations when dealing with the complex urban road network. This paper aims to explore a new method of capacity Optimization of Road Networks in a Smart City environment and proposes a method based on a Graph Neural network, named “Smart City Road optimization Graph Neural Network” (SCRO-GNN). SCRO-GNN first collects and preprocesses multi-source data, including road network data, traffic flow, accident records, environmental factors, etc. The key node and edge features, including the number of lanes at the intersection, the traffic flow of the section, and the adjacency matrix of the road network are defined to characterize the structure of the road network. Then, the graph neural network model is constructed and trained to predict the traffic flow of different sections and evaluate the road capacity by using the graph structure of the road network. This paper tests the performance of SCRO-GNN on real road networks in multiple cities. The results show that, compared with the traditional traffic flow prediction model, SCRO-GNN can significantly improve the prediction accuracy, especially when dealing with the highly complex urban road network structure. Based on these predictions, the proposed optimization strategy performed well in reducing traffic congestion and improving the efficiency of road use. The research in this paper not only demonstrates the potential of graph neural networks in smart city road network optimization, but also provides a new direction for future traffic system research. The successful implementation of the SCRO-GNN approach is expected to provide more efficient and intelligent solutions for urban traffic management and planning.

Integrating an urban fire model into an operational wildland fire model to simulate one dimensional wildland–urban interface fires: a parametric study

Background Wildland fires that occur near communities, in the wildland–urban interface (WUI), can inflict significant damage to urban structures. Although computational models are vital in wildfires, they often focus solely on wildland landscapes. Aim We conducted a computational study to investigate WUI fire spread, encompassing both urban and wildland landscapes. Methods We developed a 1D landscape-scale semi-physical model by integrating a semi-physical urban fire spread model into an Eulerian level set model of wildfire. The model includes ignition and spread through radiation, direct flame contact and ember deposition. Key results Through a parametric study, we compare the relative change of spread rate from various structural properties and landscape layouts represented by model parameters, highlighting the significant impact of fire-resistant structure materials over surface treatments. Layout configurations play a pivotal role in fire spread, with isolated islands of combustibles effective in reducing spread rate, aligning with existing mitigation strategies. Conclusion Despite using a 1D domain and limitations on spatial and temporal variability, our model provides insights into underlying phenomena observed in WUI fires and their mitigation. It offers early-stage development of strategies for managing structure materials and landscape layouts. Implications Our model and findings provide insights into WUI fire dynamics, paving the way for advanced mitigation strategies.