City Center Research Articles

The impact of latent policy synergy between cities on air pollution: An empirical analysis from China's 12,764 air policies

Policy synergy plays a crucial role in managing regional air pollution. However, the current process of formulating collaborative policies often focuses too heavily on achieving optimal emission reduction outcomes, while neglecting the execution costs at the local level. This not only leads to a lack of coordination between existing governance measures and new policies but may also result in inefficient policy implementation and the wastage of administrative resources. To address this issue, we have conducted a thorough analysis of the latent interconnections in local governance and explored the possibility of formulating collaborative policies based on latent policy synergies. Utilizing a dataset of 12,764 policy documents from China spanning from 2000 to 2023, we employed unsupervised learning techniques and panel regression models to investigate the impacts of latent policy synergies among local governments. Our findings reveal that local governments initially relied on rigid command-and-control strategies to address air pollution, which were later enhanced with economic incentives like emissions trading and subsidies, thus broadening the scope of policy tools and improving compliance flexibility. Subsequently, as comprehensive monitoring networks were established, enabling real-time data acquisition and more accurate pollution assessments, the focus of policy efforts shifted towards a more integrated approach to regional air pollution management. This similar evolution facilitated latent policy synergy among local governments, leading to significant reductions in air pollution emissions. Notably, regions such as the Central Plains and coastal cities, characterized by their dense industrial activity and high energy consumption, have shown remarkable potential for collaborative efforts, achieving greater pollution control efficiencies. This study provides a valuable reference for the coordinated governance of air pollution policies.

Remote monitoring of patients with chronic heart failure: A prospective randomized study

BACKGROUND: Chronic heart failure is one of the key problems of the Russian domestic healthcare system. E-health can be used to improve medical care quality and reduce the of hospitalizations and mortality. AIM: To examine the effect of telemedicine monitoring on mortality, frequency of hospitalizations, and clinical and functional states of patients with chronic heart failure. MATERIALS AND METHODS: A prospective, controlled, randomized study was conducted in the Central City Hospital No. 20 in Ekaterinburg (Russia), covering the period from December 2020 to December 2022. Patients with a confirmed diagnosis of chronic heart failure were randomized using the envelope method into three groups: group 1, a telephone control group (n=58); group 2, a remote control group using a Russian medical platform Medsenger (n=52); and group 3, the standard control group (n=103). All patients were examined, including NT-proBNP measurement and echocardiography on the first day of the study and at 3, 6, and 12 months. The occurrence of primary and secondary outcomes was evaluated at these reference points. Stata14 and jamovi software were used for statistical processing. RESULTS: The study involved 213 participants, and all three groups were comparable in terms of basic demographic and clinical characteristics. The advantage of remote control (groups 1 and 2) over face-to-face observation in reducing cardiovascular mortality was observed after 3 (odds ratio 2.73, 95% confidence interval 1.1–7.39; p=0.042) and 12 (odds ratio 2.1, 95% confidence interval 1.1–3.7; p=0.027) months and that in reducing the occurrence of the combined primary endpoint (odds ratio 2.1, 95% confidence interval 1.1–5.6; p=0.015) after 12 months. The use of the Medsenger platform also demonstrated an advantage over face-to-face observation in the development of the combined secondary endpoint (odds ratio 1.39, 95% confidence interval 0.19–0.81; p=0.011) after 3 months and over telephone control by a nurse after 12 months in reducing cardiovascular mortality (odds ratio 0.177, 95% confidence interval 0.06–0.487; p=0.021) and development of the combined secondary endpoint (odds ratio 0.427, 95% confidence interval 0.189–0.964; p=0.041). When using the Medsenger platform, the ejection fraction increased from 47% initially to 55% after 12 months (p=0.004). The NT-proBNP level decreased from 817 to 582 pg/mL (p 0.001) after 3 months and then to 233 pg/mL after 12 months (p 0.001). CONCLUSION: Remote monitoring protocols can be a good alternative to the traditional face-to-face monitoring of patients with chronic heart failure, which may improve clinical and functional health indicators.

The influence of residential location and public transit options on commuters’ intention to use travel apps for different travel purposes

While living in city centers is usually linked to higher accessibility levels, shorter travel times, and higher levels of public transit (PT) utilization, the opposite is true for residents of suburban areas. This assumption holds in metropolitan contexts, where central areas offer better accessibility and are associated with higher levels of PT use. In metropolitan peripheries, a large part of commuting is done on an interurban basis, so that the level of use of public transit can be linked to the supply and information available. This work aims to understand the conditions in terms of transit supply and land use, considering the most frequent trip, psychological variables, and the modal choice of commuters’ motorized modes, in the intention to use the new real-time multi-modal travel app, such as advanced traveler information systems (ATIS) for digital mobility-management assistance. A Structural Equation Model is developed to empirically test a sample of 768 respondents collected in two suburban corridors in the Lisbon Metropolitan Area (LMA). Finally, our findings indicate that residential location, mode choice, and trip complexity have a relevant influence on the intention to adopt travel apps. Male students belonging to Generation Y/Z are the most likely users of travel apps. Regardless of the reason, travel patterns associated with more complex (more transfers) and more frequent trips can reinforce the intention to use apps. Also, it is worth noting that students are frequent public transit users, and public transit is also related to trip complexity.

Radial analysis and scaling of housing prices in French urban areas

Urban scaling laws summarize how attributes evolve with city size. However, one limitation concerns the aggregate view of this approach, which leads to neglecting the internal structure of cities. This is an important issue regarding housing prices, given their significant variations across space. Based on a dataset compiling millions of real estate transactions over the period 2017–2021, we investigate the regularities of the radial (center-periphery) profiles of housing prices across cities, with respect to their size. Results are threefold. First, they corroborate prior findings in the urban scaling literature stating that largest cities agglomerate higher housing prices. Second, we find that housing price radial profiles scale in three dimensions with the power 1/5 of city population. After rescaling, great regularities between radial profiles can be observed, although some locational amenities have a significant impact on prices. Third, it appears that our approach with rescaled profiles fails to explain housing price variations in the city center across cities. In fact, prices near the city center rise much faster with city size than in the periphery. This has strong implications for low-income households seeking homeownership because prohibitive prices in the center may contribute to pushing them out into peripheral locations, especially in large cities.

Towards Sustainable Development of the Old City: Design Practice of Alleyway Integration in Old City Area Based on Heritage Corridor Theory

Urbanization has increasingly led to the overlapping of old and new spaces in historic city areas, creating challenges in preserving valuable urban heritage. To meet the requirements of the effective protection, utilization, and sustainable development of these historical spaces, this study introduces a comprehensive framework grounded in the theory of heritage corridors. The proposed framework subdivides and connects fragmented historical spatial resources through the “point–line–plane” dimensions, fostering sustainability across the environmental, ecological, and cultural domains. To validate the effectiveness of the framework, we apply it to the historic city center of Wuxi. This case study demonstrates that integrating spatial resources within the old city enhances the overall quality of urban living spaces in the historic district. The findings suggest that the heritage corridor framework is a feasible and systematic approach for the sustainable renewal of historic urban areas. Furthermore, this study offers valuable insights for advancing Sustainable Development Goal 11 (SDG 11), particularly in promoting inclusive, safe, resilient, and sustainable cities.

A Socio-Political Aspect of Housing and Communal Sanitation in the USSR, 1950s–1960s (Based on Materials of Leningrad and Vyborg)

Introduction. The article examines the interactions between the sanitary service, other departments, and city residents in the 1950s and 1960s to improve sanitary conditions, using the examples of Leningrad and Vyborg. It shows how the level of housing safety increased as the state allocated material resources to service organizations and improved sanitary standards. Methods and materials. The article is based on materials from the State Archive of the Russian Federation, the Central City Archive of St. Petersburg, and the Leningrad Oblast Archive, and a number of newspaper publications. Minutes of meetings, reports and explanatory notes, and citizens’ appeals to various authorities show that littered exits, uncollected cesspools, irregular cleaning of adjoining territories, and mountains of garbage often became a source of epidemics. Analysis. These problems were addressed as communication between government agencies and the public evolved. The legislative framework governing sanitary safety in cities was formed as early as the 1930s. The situation was aggravated by the lack of education of the population, which did not want to comply with sanitary rules. Solving the problem required concerted work by authorities, academics, and community activists. In order to reduce the risks of disease for city residents, city authorities organized trash pickups, lectures for citizens with representatives of sanitation services, etc. Thus, practices were formed to maintain compliance with the necessary norms. Results. The identified features of the implementation of housing and communal sanitation norms give the idea that established communication between government and public organizations was a channel for reducing the risks of epidemics and the comfort of the dwelling. Increased use of specialized machinery that allowed for garbage collection and a number of other problems was able to accelerate sanitation problems. This article illustrates how the risks – the high likelihood of epidemics – forced the state and citizens to seek effective ways to develop and maintain sanitary standards. The successful development of practices was thus related to the development of the necessary infrastructure and the awareness of city residents of the benefits of complying with practices.

Initial Insights into Teleworking’s Effect on Air Quality in Madrid City

Commuting to work by private vehicle is one of the main sources of air pollution in cities, mainly from NO2 and particulate matter (PM2.5 and PM10). With the spread of telework, traffic congestion during peak hours is reduced on certain days of the week, improving air quality. This study analyzes the relationship between the improvement of air quality and urban traffic resulting from teleworking activities after the COVID-19 pandemic in Madrid, Spain. This article considers road traffic and teleworking before the COVID-19 pandemic (2018 and 2019), during the pandemic (2020 and 2021) and in the period after (2022 and 2023) in the city center and the influence on certain environmental factors. Daily NO2, PM2.5, PM10, and O3 concentration data were collected at air quality stations in Madrid municipality, and traffic data and some meteorological variables such as wind speed, precipitation and temperature were considered. When conducting correlation and regression analysis among the variables, there is a clear association between NO2 and traffic before the pandemic, which is lower for both PM and O3. This correlation was maintained during the pandemic, except for O3, the association of which increased during this period and then decreased in the later period due to various motives. These results seem to indicate the existence of a relevant relationship between urban mobility and air quality and an especially relevant relationship with telework, suggesting the need for policies aimed at promoting sustainable mobility in the future.

Enhancing Urban Sustainability: Developing an Open-Source AI Framework for Smart Cities

To address the growing need for advanced tools that enable urban policymakers to conduct comprehensive cost-benefit analyses of traffic management changes, the Urbanite H2020 project has developed innovative artificial intelligence methods. Among them is a robust decision support system that assists policymakers in evaluating and selecting optimal urban mobility planning modifications by combining objective and subjective criteria. Utilising open-source microscopic traffic simulation tools, accurate digital models (or “digital twins”) of four pilot cities—Bilbao, Amsterdam, Helsinki, and Messina—were created, each addressing unique mobility challenges. These challenges include reducing private vehicle access in Bilbao’s city center, analysing the impact of increased bicycle traffic and population growth in Amsterdam, constructing a mobility-enhancing tunnel in Helsinki, and improving public transport connectivity in Messina. The research introduces five key innovations: the application of a consistent open-source simulation platform across diverse urban environments, addressing integration and consistency challenges; the pioneering use of Dexi for advanced decision support in smart cities; the implementation of advanced visualisations; and the integration of the machine learning tool, Orange, with a user-friendly GUI interface. These innovations collectively make complex data analysis accessible to non-technical users. By applying multi-label machine learning techniques, the decision-making process is accelerated by three orders of magnitude, significantly enhancing urban planning efficiency. The Urbanite project’s findings offer valuable insights into both anticipated and unexpected outcomes of mobility interventions, presenting a scalable, open-source AI-based framework for urban decision-makers worldwide.

Local Democracy in America: How Access, Competition, and Place Shape Turnout in Mayoral Races

The vast majority of the roughly half-million elected officials in the U.S. occupy local offices, however, research examining how they get elected to remains scant. The present study examines turnout in local elections, focusing on the effects of electoral rules, the competitiveness of local races, and whether and how place matters. Based on a sample of roughly 10,000 mayoral elections, this study represents the most systematic empirical analysis of local turnout to date. While we find substantial differences in turnout across rural towns, suburbs, and central cities, these differences are largely explained by electoral and contextual factors that are unevenly distributed across the local landscape. Though election timing is far and away the most important factor, uncontested mayoral races, local elections in states with restrictive voting laws as well as those mid-sized municipalities are associated with significantly lower turnout.

Analyzing K-12 AI education: A large language model study of classroom instruction on learning theories, pedagogy, tools, and AI literacy

There is growing recognition among researchers and stakeholders about the significant impact of artificial intelligence (AI) technology on classroom instruction. As a crucial element in developing AI literacy, AI education in K-12 schools is increasingly gaining attention. However, most existing research on K-12 AI education relies on experiential methodologies and suffers from a lack of quantitative analysis based on extensive classroom data, hindering a comprehensive depiction of AI education's current state at these educational levels. To address this gap, this article employs the advanced semantic understanding capabilities of large language models (LLMs) to create an intelligent analysis framework that identifies learning theories, pedagogical approaches, learning tools, and levels of AI literacy in AI classroom instruction. Compared with the results of manual analysis, analysis based on LLMs can achieve more than 90% consistency. Our findings, based on the analysis of 98 classroom instruction videos in central Chinese cities, reveal that current AI classroom instruction insufficiently foster AI literacy, with only 35.71% addressing higher-level skills such as evaluating and creating AI. AI ethics are even less commonly addressed, featured in just 5.1% of classroom instruction. We classified AI classroom instruction into three categories: conceptual (50%), heuristic (18.37%), and experimental (31.63%). Correlation analysis suggests a significant relationship between the adoption of pedagogical approaches and the development of advanced AI literacy. Specifically, integrating Project-based/Problem-based learning (PBL) with Collaborative learning appears effective in cultivating the capacity to evaluate and create AI.

Travel Time Variability in Urban Mobility: Exploring Transportation System Reliability Performance Using Ridesharing Data

Travel time variability (TTV) is a crucial indicator of transportation network performance, assessing travel time reliability and delays. This study investigates TTV metrics within the context of shared mobility using probe data from transportation network companies (TNCs) in Chicago, Los Angeles, and Dallas–Fort Worth. Eight reliability metrics are analyzed and compared for each origin–destination (OD) pair in the network, including standard deviation (SD), the Planning Time Index (PTI), the Travel Time Index (TTI), the Buffer Index (BI), On-time Measures PR (alpha), and the Misery Index (MI), to evaluate their effectiveness in clustering OD pairs using K-means clustering. The findings confirm that SD, PTI, and MI are particularly effective in measuring travel time reliability and clustering within urban systems. This study identifies the most unbalanced supply–demand OD pairs/regions in each city, noting that low/medium-SD clusters around metropolitan airports indicate stable travel times even in high-demand zones, while high-SD clusters in downtown areas reveal significant traffic demands and unreliability. These patterns become more pronounced in study areas with multiple city centers. This study highlights the need for targeted strategies to enhance travel time reliability, particularly in regions like Dallas–Fort Worth, where public transportation alternatives are limited.

Chronological Analysis of The Ontological Sequence of The Neighborhood in Urban Physical Stratification; Şükran Neighborhood-Konya

The aim of this study is to understand the change in the spatial structure of Şükran district, which has been shaped by the concept of neighborhood from past to present in the urban memory of Konya. In this context, the stratification in the urban space with the historical stratification, the structure and road relationship that will be revealed together with the ontological structure of the neighborhood, and the evolution of the land subdivision form and situation over the years will be examined in detail. In this sense, the connection of the structure, which is expected to be completely changed in the future with the urban transformation of the neighborhood, which is located in the historical city center of Konya and where mainly dwellings are built, will be questioned and the systematic structure of the transformation will be investigated. As a result, questioning the transformation of urban spaces where the urban physical gradation continues is important in order to transfer urban memory to future generations. In line with these purposes, within the scope of the study, the ontological structure of the neighborhood will be questioned within the urban physical stratification that took place in the historical process, its formation in the city in unplanned and planned periods from the past to the present will be investigated in detail within the framework of the decisions taken by the city administrators and the changing regulations and a documentation will be done at the point of transferring the urban memory to the future.

The Primacy Evaluation and Pattern Evolution Mechanism of the Central City in Nanjing Metropolitan Area

Economic globalisation has accelerated the cross-regional flow of resource elements and broken through the constraints of traditional regional administrative boundaries. Urban agglomerations are core carriers that drive and accelerate regional integration development and can promote the division of urban functions and cooperation. This study considers the Nanjing metropolitan area as a case study to construct a comprehensive first-degree evaluation index system for cities from a factor-flow perspective, focusing on economic, cultural, and transportation connections. We found that (1) Nanjing, which has long been ranked first, shows a downward trending score, dropping from 0.956 in 2017 to 0.937 in 2023; (2) The comprehensive first-degree spatial structure of metropolitan-area cities presents a network hierarchical development feature of “one core, multiple centres, and multiple areas”. With Nanjing as the regional core city, Chuzhou (0.879), Yangzhou (0.915), and Wuhu (0.897) as sub-centre cities, and other cities as sub-regional nodes, the urban system structure gradually forms; (3) The indicators of economic (0.166 **), cultural (0.226 **), and transportation (0.644 ***) element connections were interrelated and mutually reinforced, forming a unified entity with internal connections. This study quantitatively measured the level of integrated development in the Nanjing metropolitan area and provided a reference for formulating regional policies.

Multi-scale matching and simulating flows of ecosystem service supply and demand in the Wuhan metropolitan area, China

Metropolitan areas face the challenge of balancing increasing social needs against limited natural resources. The multi-scale evaluation of ecosystem services (ES) supply, demand and flows is crucial but under explored. Four prominent ES, food provision (FP), carbon sequestration (CS), soil conservation (SC), and outdoor recreation (OR) in Wuhan metropolitan area (WMA) were selected as cases. ES supply and demand were assessed by InVEST model, geographic information system (GIS) spatial analysis, and statistical methods. A linear programming model was employed to reveal the characteristics of ES flows. Results showed the following: (1) the total ES supply capacity can meet the demand of the study area. At different scales, the supply patterns were fundamentally consistent, except for FP, which was significantly higher in Wuhan's suburban areas. In contrast, the other three ES exhibited high supply in the northeast and south WMA, encompassing the Dabie and Mufu Mountains. The high demand for all ES radiated from the city center, except for SC. (2) A significant scale effect of ES mismatch was found, and ecological deficit patches decreased with increasing research scale. The Mismatch was evident on finer scales but lessened at coarser ones. (3) ES flows, consisting of FP, CS, and OR, formed a flow pattern from the suburbs to the city center. Coarse-scale management integrating ecological flows may better maintain ES balance than fine-scale measures. These findings provide insights for multi-scale management strategies that not only contribute to localized ecological restoration, but also optimize strategies for ecological corridors and compensation mechanisms.

Effect of Cell-to-Cell Internal Resistance Variations on the Thermal Performance of Lithium-Ion Batteries for Urban Air Mobility

This study examines the thermal behavior of lithium-ion battery modules intended for Urban Air Mobility (UAM), a forthcoming urban transport system designed to facilitate efficient and secure passenger and cargo transport within city centers. UAM applications necessitate batteries with high energy densities capable of sustaining elevated discharge rates during critical phases such as takeoff and landing. The battery module evaluated in this study comprises four cells arranged in series and configured as a submodule for UAM applications. A three-dimensional thermal model was utilized to analyze the impact of external temperature fluctuations and high discharge rates on the performance of the battery module. The numerical findings indicated considerable variations in temperature and internal resistance among the cells, especially under high discharge rates at low temperatures, with a maximum temperature deviation of 32.952 °C observed at an 8 C discharge rate. These thermal non-uniformities were attributed to variations in cell capacity and internal resistance, which were amplified by manufacturing inconsistencies and operational conditions. The study underscores the necessity of robust thermal management strategies to mitigate the risk of thermal runaway and ensure the operational safety and reliability of UAM systems. The results emphasize the critical role of advanced Battery Management Systems (BMS) in monitoring and controlling cell voltage and temperature to achieve consistent performance across the battery module. This research contributes valuable insights into the design of more efficient and reliable battery modules for UAM, highlighting the importance of addressing cell-to-cell performance discrepancies to enhance overall module efficacy and durability.

Study on Urban Growth of Pakse City

This research has considered the growth and important changes of Pakse city in Lao PDR from 2005 to 2020. The city is strategically located as a commercial and tourism center in the Mekong sub-region. In addition, Pakse's rapid urban growth is fueled by economic development, infrastructure improvements, demographic changes and strategic geographic location, all of which contribute to making it an important urban center in the south. The research aims to study the growth of the city of Pakse to create an understanding of the phenomenon, the driving force as well as the factors that lead to the growth of the city as a way to plan and control the development of the city for sustainable growth using the integrated research method of spatial analysis, quantitative analysis and document survey which analyzes the growth of the population and households, economic growth and the growth of the urban area. The analysis results show a population increase of 32.30 percent (from 78,669 people in 2005 to 116,200 people in 2020). Economic growth is also clear GDP per capita increased by 56.86 percent (from 1,097 dollars in 2005 to 2,543 dollars in 2020). The growth of the construction area of the city increased by 47.03 percent (from 285 hectares in 2005 to 538 hectares in 2020) and in Pakse city municipality, there is a growth of 46.35 percent (from 279 hectares to 520 hectares in 2020). Most of the built-up area is concentrated in the city center, covering 96.65 percent, and the number of buildings has increased by 45.18 percent (from 17,262 to 30,870 in 2020). These findings indicate the growth of Pakse city during the study period.

Enhancing bird habitat networks in metropolitan areas: Resilience assessment and improvement strategies – A case study from Shanghai

Constructing bird habitat networks (BHNs) is crucial for maintaining the health and service equilibrium of urban ecosystems, especially in large metropolitan areas where the pressure of urbanization is intense. However, most existing BHNs fail to account for the dynamic changes and unique requirements of local species, leading to homogenized construction outcomes and ecological corridor objectives. This study employs a comprehensive approach to identify bird habitat patches using multiple high-quality sources, then utilize circuit theory and complex network theory to construct and assess the resilience of BHN. Our key findings showed: (1)93 bird habitat sources were identified, predominantly situated in the continuous green spaces of southern and southeastern Shanghai, whereas habitat sources in the city center and other densely built-up areas are more dispersed, highlighting them as prime targets for future ecological restoration efforts. (2) The distribution of bird habitat corridors exhibits significant spatial heterogeneity, with primary corridors predominantly spanning the southwestern and eastern parts of the study area, while secondary corridors are more abundant in the western and northern parts, forming a denser network, whereas the central area shows fewer and more isolated corridors. (3) The decline in structural and functional resilience was notably more rapid under targeted attacks than under random attacks, underscoring the need to prioritize crucial bird habitat sources on the city's periphery, especially near highly urbanized areas, in urban planning and biodiversity conservation efforts to sustain ecological balance and biodiversity. These insights provide a crucial scientific basis for urban planners, emphasizing the integration of biodiversity conservation into urban development strategies by optimizing ecological sources and corridors to balance development with ecological preservation.

Evolution Process and Land Use/Land Cover Response of Urban–Rural Space in Wuhan under Polycentric Structure

Polycentric development facilitates urban–rural spatial reshaping and land use/land cover (LULC) protection. Previous studies have predominantly focused on urban areas, with spatial delineation methods biased towards the macro-level, lacking a holistic perspective that situates them within the urban–rural spatial framework. This study proposes a spatial delineation framework that is applicable to the polycentric structure, taking into account the social, economic, and natural characteristics of urbanization. It employs semivariance analysis and spatial continuous wavelet transform (SCWT) to analyze the effects of polycentric development on the urban–rural space of Wuhan from 2012 to 2021 and applies a land use transition matrix, landscape indices, and bivariate spatial autocorrelation to quantify the responses and differences of LULC within urban–rural space. The results indicate that 600m×600m is the best scale for exhibiting the multidimensional characterization of urbanization. The polycentric structure alleviates the compact development of the central city, and it drives rapid expansion at the urban–rural fringe, exacerbating the spatial heterogeneity in LULC change pattern, spatial configuration, and urbanization response within urban–rural spaces. The overall effects of urbanization on LULC are relatively weak along the urban–rural gradient, experiencing a transition from positive to negative and back to positive. This study employs a novel spatial delineation framework to depict the polycentric transformation of metropolitan areas and provides valuable insights for regional planning and ecological conservation in the urban–rural fringe.

Combining human perception and street accessibility to provide information for better street construction: a case study of Chengdu City, China

ABSTRACT High-quality street spaces have a positive impact on residents’ lives. Revealing the differences in human perception and walkability across street spaces can highlight priority areas for street quality enhancement and provide valuable insights that help urban managers make informed decisions. This study first utilised machine learning models (SegNet) to extract visual elements from street view images and collected volunteers’ ratings of six perceptual dimensions of street scenes. Subsequently, it employed random forest algorithms and spatial autocorrelation models to predict and analyse overall street perception. Furthermore, principal component analysis was used to consolidate the six perceptual scores, coupled with an analysis of street walkability, to identify streets that most required quality enhancement. Finally, correlation and regression analyses were conducted between human perception ratings and street visual elements. The results indicated that buildings positively influence perceptions of wealth, safety, liveliness, and beauty and are the most significant positive perception elements. Conversely, walls were the most significant negative perception elements. Additionally, trees positively impacted perceptions of liveliness and beauty. Lastly, streets categorised as “high walkable-low perception” exhibited a radial dispersion from the city centre. In conclusion, the findings of this study provide valuable insights for enhancing street-space quality in Chengdu and other cities.

An MCDM-GIS framework for assessing flooding resilience of urban metro systems

Extreme rainstorms pose significant challenges to the operation of urban metro systems. This study proposes a data-driven framework for evaluating the flood resilience of metro systems, considering the spatio-temporal differences in rainfall patterns. Furthermore, it offers recommendations to bolster resilience against flooding, ensuring the safety and continuity of metro systems in the face of increasing climatic challenges. The proposed framework adheres to the tenets of design science research, a methodological approach that synergizes theoretical and empirical aspects. This framework was examined by assessing flood resilience at 254 metro stations in Wuhan. The study reveals insights into the spatial distribution of flood resilience among metro stations, with those located in suburban areas being riskier than their counterparts in city centers. Additionally, the implementation of emergency flood response strategies and the execution of pre-disaster drills play a pivotal role in reducing the potential losses caused by flooding.