Urban Structure Research Articles

A Transdisciplinary Analysis of the 2009 Catastrophe in Giampilieri Superiore by Land Use Evolution Over Time

AbstractOn October 1 2009 a deluge hit the Peloritani Mountains, in NE Sicily, Italy, where the rainfall data recorded 225 mm in 9 h. Giampilieri Superiore was the most affected townlet in terms of infrastructural damages and human losses (37 dead, 37 wounded, and more than 1000 evacuees). The debris flows, triggered by flash floods wreaked havoc of the urban structure. More than 200 mln € was granted to protection works for conveying water and debris flows to bypass the town. The disaster was numerically simulated by SCIDDICA (Digital Twin) with excellent approximation, and the effects of the safety installation were tested as well, proving to offer sufficient protection for the village. The Peloritani area overlooking the Ionian See flourished during the Saracen domination, whose legacy of systems of terraces, cisterns and wells guaranteed the finest water management in steep terrains, allowing a safe emplacement of watermills, around which Giampilieri and other villages developed. This hydraulic legacy has been undermined during the last decades due to lack of appropriate maintenance because of the progressive loss of the Saracen culture. It is unconceivable that subsidies on the scale granted to Giampilieri are sustainable when facing innumerable future climatic disasters. A cheaper and more viable solution is to be found, e.g., the settlement of immigrants in the area, promoting the labor-social inclusion of those persons who already possess such a Saracen culture or are willing to acquire it from the last local depositaries, according to a retro-innovation perspective and methodology.

Urban Drainage Network Structure Optimization Using Emperor Penguin Optimization Algorithm

Urban drainage systems are an essential component of urban infrastructure that plays a critical role in managing stormwater and preventing flooding in urban areas. With the changing climate and urbanization, the challenges faced by urban drainage systems are becoming increasingly complex. Additionally, aging infrastructure further exacerbates the problem, creating anurban sewage line that must be made more resilient. Redundancy is just a fundamental characteristic of such a robust urban drainage network. Redundancy in urban drainage systems can help to ensure that the system continues to function during extreme weather events or emergencies, reducing the likelihood of flooding and damage. However, the exact locations where redundancy should be increased and its contribution to resilience are not well understood. In recent years, several studies have focused on developing frameworks for optimising urban drainage structures which account pipeline redundancy.One similar research presented a paradigm for constructing the ideal network layout for urban drainage infrastructure, which considers pipeline redundancy under consideration. The original architecture and structure of the urban drainage network was developed using emperor penguin optimizer algorithms and graph theory in the research. Complicated system modelling was done to find extra water pathways or redundancy which might well be implemented to boost resistance. The suggested approach has been utilised to the test region in Dongying City, Shandong Province, China, and its findings revealed even under rainfall above the design specification, the entire overflow capacity of such urban drainage network including pipeline redundancy significantly decreased about 20-30%, compared to the network without pipeline redundancies. The interest in creating optimization algorithms had also increased recently that can be used to design and manage urban infrastructure systems. One such algorithm is the Emperor Penguin Optimization (EPO) algorithm. EPO was a recently developed swarm-based optimization An algorithm which simulates Emperor penguins behaviour in their search for food in Antarctica. The algorithm has shown promising results in solving complex optimization problems in different fields, including engineering, computer science, and management. The EPO algorithm's key features include an emperor search strategy, local search, and randomization, enabling that to efficiently and successfully examine the search process. The algorithm's emperor penguin search strategy enables it to dynamically adjust the search parameters based on the problem's characteristics and progress. The local search feature allows it to escape local optima and explore the search space further. Finally, the randomization feature adds stochasticity to the search process, helping to ensure that the algorithm can avoid getting stuck in a sub-optimal solution. In this article, we aim to explore the potential of EPO as a tool for optimizing Urban drainage solutions which take into account pipeline redundancy. We will start by reviewing the existing Literature upon that optimization in urban drainage facilities, particularly the application of particle swarm optimization, genetic algorithms, and ant colony enhancement. The EPO algorithm will next be described in full including its working principle, key features, and the steps involved in applying it to an optimization problem. Finally, we will present a case study that applies the EPO technique was developed to optimise the network model of such an urban drainage infrastructure taking into account pipeline redundancies, and compare the results with other optimization algorithms. Through this, we aim to demonstrate the potential of EPO as a powerful tool for designing and managing urban infrastructure systems, particularly for enhancing the resilience of urban drainage systems. The study will provide valuable insights into the optimal design of urban drainage technologies which take into account pipeline redundancy, helping policymakers and urban planners make informed decisions about improvingthe adaptability of urban drainage networks. The findings can contribute to the development of sustainable and resilient urban infrastructure systems, which are essential for ensuring the well-being and prosperity of urban residents.

Geodatabase, metric reconstruction and a GIS platform of historical-archaeological sites in Aquino

This paper presents the contents of a geodatabase developed from the outcomes of survey operations carried out, in several stages since 2015, within the archaeological context of the Roman city of Aquinum, in southern Lazio. The proposed geodatabase integrates traditional topographic surveying techniques with total station, GPS and GNSS geodetic receivers with photogrammetric surveys and terrestrial laser-scanner (TLS) measurements, including the realization of HBIM (Historical Building Information Modeling) models, to investigate some specific historical-archaeological evidence useful to understand the Roman and medieval urban structure of the city. The processing and management of the metric and information datasets were entrusted to a GIS platform, implemented in the opensource Quantum-GIS software, to optimize the flowchart of the acquisition/processing process and to realize an intra-site Web-GIS useful for the visualization and dissemination of the results. The methodological-operational approach applied in the research activities highlights the fundamental contribution that the technological innovations of geomatics can provide for the construction of elaborate knowledge concerning cultural heritage, also becoming the base for the elaboration of more complex and detailed analyses. In this case, for example, the HBIM digital model of the Church of Santa Maria of Libera was also used for an in-depth study in the field of structural engineering, as input to model the masonry vaults of the aisles of the church and assess their structural safety through the analysis methodology denominated "Thrust Network Analysis (TNA)." In addition, the high-precision 3D models developed from detailed photogrammetric measurements of the archaeological fragments and human remains found in the excavation areas made it possible to create interesting "visual digital products" that are immediately understandable even for non-experts, and thus particularly useful for wide-ranging knowledge dissemination.

Impact of urban form on carbon emissions of residents in counties: evidence from Yangtze River Delta, China.

Urban form is a key factor affecting carbon emissions. Accurately estimating the impact of urban form on the carbon emissions of residents (CER) is an important prerequisite for China to adopt effective low-carbon spatial planning strategies and respond to climate change. However, counties mainly account for China's energy consumption, and the relationship between their urban form and the CER remains unclear, limiting their low-carbon development. Therefore, in this study, the PLS-SEM model and data from 90 counties in the Yangtze River Delta are used to determine the extent and ways that urban form affects the CER. The model considers the impact of both geometric-aspect urban form factors (urban scale, compactness, spatial structure, and urban shape) and built environment-aspect urban form factors (public service facilities, urban greening, road traffic, public transportation, and urban energy infrastructure) on the CER. The results indicate that urban form factors related to the built environment (public service facilities, urban greening, road systems, and municipal infrastructure) have a direct impact on the CER. Geometric-aspect urban form factors (size, compactness, spatial structure, and shape) not only directly affect the CER but also indirectly affect the CER by altering built environment-aspect urban form factors. This study identifies the complex relationship between urban form and the CER, facilitating the coordinated integration of multiple elements and providing a basis for the formulation of low-carbon spatial planning strategies for counties.

Spatial insights for sustainable transportation based on carbon emissions from multiple transport modes: A township-level case study in China

Understanding the CO2 emissions and influencing factors of travelers' multiple modes can provide direction for energy conservation and emission reduction, which is of great significance for developing sustainable cities. Previous studies focused on the CO2 emissions of the transportation sector or individual modes. Which has overlooked the variations of emissions within the transport system. Hence, this study focuses on multiple modes (i.e., car, subway, bus, and bike) in the township in the Guangdong-Hong Kong-Macao Greater Bay Area. This study proposes a framework for exploring the spatial autocorrelation of urban transport emission structure based on ratios (i.e., CO2 emissions from each mode divided by total emissions) and key factors by combining spatial econometric model (i.e., Moran's I index and Spatial Error Model) and machine learning model (i.e., Random Forest and SHAP model). In addition, the spatial autocorrelation of ratios at different spatial scales is investigated. The results indicate the high spatial dependence in the ratios from each transport mode and Moran's I indices for four ratios are 0.883, 0.886, 0.706, and 0.776, respectively. In addition, subway and car ratios exhibit a negative spatial correlation (−0.798), and subway and bike show a positive correlation (0.570). Population density, road length, and land use diversity are the key drivers of CO2 emission ratios and have different effects on various transport modes. Furthermore, as the spatial scales expand from townships to distinct and city, the spatial autocorrelation of the ratios decreases. This study could provide policy implications for optimizing urban transport strategies and reducing CO2 emissions.

Novo-Nikolaevsk (Novosibirsk): Planning Solution of the Future Siberian Metropolis Late in the 19th and Early 20th Centuries

The paper studies the urban planning of future Novosibirsk in the period of formation of its general plan late in the 19th and early 20th centuries. The initial structure of the city as Central, Railway and Zakamenskaya parts with their orthogonal scheme of blocks, streets and alleys is investigated.The urban planning phenomenon of pre-revolutionary Novo-Nikolaevsk is of great interest for the history of national and world urban planning. The urban planning is considered and evaluated as well as the use of other planning concepts and new techniques available in those years.The necessity of preserving the existing historical urban structure in the central part of modern Novosibirsk is substantiated, the possibility of its practical use in reconstruction and development of historical quarters of the city is considered.

The Relationship Between Three-Dimensional Spatial Structure and CO2 Emission of Urban Agglomerations Based on CNN-RF Modeling: A Case Study in East China

Good urban design helps mitigate carbon dioxide emissions and is important for achieving global low-carbon goals. Previous studies have mostly focused on the two-dimensional level of urban socio-economic activities, urban land use changes, and urban morphology, neglecting the importance of the three-dimensional spatial structure of cities. This study takes 30 cities in East China as an example. By using urban building data and carbon emission datasets, four machine learning algorithms, BP, RF, CNN, and CNN-RF, are established to build a CO2 emission prediction model based on three-dimensional spatial structure, and the main influencing factors are further studied. The results show that the CNN-RF model performed optimally in both the testing and validation phases, with the coefficient of determination (R2), root mean square error (RMSE), and residual prediction deviation (RPD) of 0.85, 0.82; 10.60, 22.32; and 2.53, 1.92, respectively. Meanwhile, in the study unit, S, V, NHB, AN, BCR, SCD, and FAR have a greater impact on CO2 emissions. This indicates a strong correlation between urban three-dimensional spatial structure and carbon emissions. The CNN-RF model can effectively evaluate the relationship between them, providing strategic support for spatial optimization of low-carbon cities.

The interplay of cloud cover and 3D urban structures reduces human access to sunlight

The interplay of cloud cover and 3D urban structures reduces human access to sunlight

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

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

Research on the Characteristics and Evolution of Urban Spatial Structures under Complex Terrain Conditions: Taking 71 Typical Cities in China as an Example

Research on the Characteristics and Evolution of Urban Spatial Structures under Complex Terrain Conditions: Taking 71 Typical Cities in China as an Example

Characterizing the livingness of geographic space across scales using global nighttime light data

The hierarchical structure of geographic or urban space can be well-characterized by the concept of living structure, a term coined by Christopher Alexander. All spaces, regardless of their size, possess certain degrees of livingness that can be mathematically quantified. While previous studies have successfully quantified the livingness of small spaces such as images or artworks, the livingness of geographic space has not yet been characterized in a recursive manner. Zipf’s law has been observed in urban systems and intra-urban structures. However, whether Zipf’s law is applicable to the hierarchical substructures of geographic space has rarely been investigated. In this study, we recursively extract the substructures of geographic space using global nighttime light imagery. We quantify the livingness of global cities considering the number of substructures (S) and their inherent hierarchy (H). We further investigate the scaling properties of the extracted substructures across scales and the relationships between livingness and population for global cities. The results demonstrate that all substructures of global cities form a living structure that conforms to Zipf’s law. The degree of livingness better captures population distribution than nighttime light intensity values for the global cities. This study contributes in three aspects: First, it considers global cities as a whole to quantify spatial livingness. Second, it applies the concept of livingness to cities to better capture the spatial structure of the population using nighttime light data. Third, it introduces a novel method to recursively extract substructures from nighttime images, offering a valuable tool to investigate urban structures across multiple spatial scales.

The gentrification of health: an analysis of its convergence

The article explores how gentrification impacts public health, with a particular focus on urban transformations and their repercussions on communities. Using a desk review methodology in the Scopus database, this study analyses the literature between 2018 and 2023 to identify how changes in urban structure influence the accessibility and quality of health services. It highlights that while gentrification can improve infrastructure and services, it can also exacerbate health inequalities and lead to the displacement of vulnerable populations. The analysis reveals the need to adapt medical education to these new urban challenges and suggests future lines of research to develop more equitable interventions. This multidisciplinary approach offers valuable insights for more inclusive policies that consider both urban development and health equity

The dynamics of urban structure and form as a tool for rejuvinating the image of the path and edge of the city in anticipation of urban sprawl

The dynamics of urban structure and form as a tool for rejuvinating the image of the path and edge of the city in anticipation of urban sprawl

Understanding the spatial pattern and structural characteristics of cities in late feudal China: evidence from the local chronicle maps of the qing dynasty (1644–1911)

ABSTRACT Our study analyzes the spatial pattern and structural characteristics of cities in late feudal China based on multiple correlation and geographic information system spatial analysis, using 58 local Chinese chronicle maps of Jiangsu in the Qing Dynasty as research material. The elements in the city map were dominated by the types of official buildings, transportation facilities, and religious buildings. The urban spatial pattern can be classified into four types, such as extraverted and introverted, with each type having an aggregated spatial distribution and a gradual introverted orientation in time. The urban spatial structure can also be divided into four types: traditional, axial, random, and composite. Spatial distribution of each type is relatively stable, with little change over time. The geographic environment and the traditional concept of city building are the basic reasons for the formation of the spatial pattern and structure. The flood disaster, commercial and military factors contribute to the diverse structures. Our study demonstrates the feasibility of quantifying the ancient Chinese chronicles’ city maps. The findings have important value for contemporary ancient city restoration and shaping urban characteristics.

Evaluation of thermal effects on urban road spatial structure: A case study of Xuzhou, China

Urban heat islands (UHI) are important environmental issue in cities where urban spatial structure has been proven to play an important role in alleviating UHI effects. The relationship between land surface temperature and urban spatial structures has been explored, providing strong support for their cooling effects. Urban roads are the skeleton of urban spatial structures, with obvious spatial structure characteristics; however, research on the relationship between roads and the thermal environment has been mostly focused at the micro and meso level, lacking exploration at the macro spatial structure scale. Xuzhou—a typical average-sized city in China—was selected as the research object and the road system as the carrier. The thermal environmental effects of road elements such as their structural attributes, geometric attributes and unique construction attributes were quantitatively analyzed using geographically weighted regression analysis. The results revealed that 1) the contribution of roads in the study area to the UHI effect is relatively stable; therefore, this area should become an important cooling space to decompose UHI patch connectivity and thus decrease the UHI effect. 2) the self-organizing structural characteristics of urban roads affect their thermal environments where in the straightness of the road structure and road thermal environment showed a clear overall negative correlation And 3) the length and width of the road segments had negative and positive effects on the thermal environment, respectively. The green coverage of the roads has a global negative effect on the thermal environment, but shows obvious spatial non-stationarity. Therefore, green measures must be implemented in different regions. The results here provide a quantitative basis for urban road system planning and urban form management and control that incorporates thermal environment improvements, as well as a reference for the study of urban thermal environments under different spatial forms and planning control systems in other countries and regions.

Investigating the influence of morphologic and functional polycentric structures on urban heat island: A case of Chongqing, China

Polycentric urban structures are widely regarded as solutions to mitigating urban heat islands (UHI). However, few studies clarified the influences of morphological and functional polycentrism on UHI. Using Chongqing as the case study, we revealed the spatial pattern of UHI based on ECOSTRESS images and morphological/functional polycentrism based on multi-source data. Then, we quantified the spatial and nonlinear effects of polycentric structures on UHI using spatial regressions and XGBoost-SHAP methods. The results showed that polycentric structures exhibit spillover and nonlinear effects on local heat variation. Building volume alleviated UHI in the urban core, signifying a substantial shadowing effect in a mountainous setting. Population density positively but weakly affected local UHI among urban centers. Facility mixture positively affected UHI mainly in facility-abundant subcenters within the effective range between 0.5 and 1.0. As a functional factor, functional linkages exerted positive effects mainly in the urban cores where the degree centrality is larger than 1,500 while exhibiting negative correlation in the peripheral subcenters, suggesting the cooling effects by dispersing functions in the urban core. These findings help mitigate UHI by targeting measures for optimizing polycentric structures.

Evolution of Confinement Stress in Axially Loaded Concrete-Filled Steel Tube Stub Columns: Study on Enhancing Urban Building Efficiency

In the context of green building and sustainable urban development, understanding the mechanical behavior of structural components like concrete-filled steel tube (CFST) columns is crucial due to their improved load-bearing capacity, energy efficiency, and optimized material usage, which enhance structural resilience and sustainability. This research addresses the complex development of confining stress and its impact on the concrete core (CC) behavior within these columns, which are essential for urban infrastructure. Through extensive numerical studies, this study proposes a model to estimate the confining stress in axially loaded CFST short columns. Study findings reveal that the confinement effectiveness is influenced by variables such as compressive strength (CS) of the concrete, cross-sectional shape, and depth-to-wall thickness percentage. Additionally, the confinement is also significantly affected by the yield strain of steel εy/εc to the peak strain of unconfined concrete εc. A three-dimensional finite element model (FEM) was built for the simulation of the columns’ nonlinear behavior and was rigorously validated against experimental data. This model aids in the design and implementation of more efficient and resilient urban structures, supporting the principles of sustainable construction. The study underscores the importance of structural integrity in sustainable urban development and provides valuable insights for improving the design of green building materials.

County-to-district reform and "smart growth": The perspective of urban spatial expansion

Urban spatial expansion is a critical aspect of the policy of replacing counties with districts. This paper analyzes the spatio-temporal advancement of administrative division in China between 2000 and 2016, uses the Multi-Period method to examine the impact of county-to-district reform on urban spatial structure and “smart growth”. We find that the abolition of county borders leads to population migration within the city towards the newly established municipal districts, resulting in an irregular urban shape and a polycentric structure, particualrly the proactive-type reform. Further analysis shows that city-county merger promotes population polycentricity, but has no effect on employment polycentricity, leaving newly established municipal districts facing the “sleeping city”. Reformed counties expanded significantly but did not achieve substantial growth. The county-to-district reform inhibited overall urban economic growth, but cities with better population-industry match have less negative or uncertain effects.

Urban streets profiling with coupled spatio-temporal characteristics and topological information from the biking perspective

Urban street profiling is the spatio-temporal pattern discovery of street-level urban areas, which plays a vital role in understanding urban structures and dynamics. Due to the natural topology and various geographic characteristics on the streets, it is necessary to combine multi-dimensional spatio-temporal information to understand different profiles of streets. This research aims to develop a street profiling framework according to the coupled characteristics of streets. At the start, a bidirected dual graph and a spatial weighted graph embedding method were used to solve the street representation. Then, the street profiles can be extracted by clustering embedding vectors of streets and feature importance analysis. As the case study, we employed the bike trajectories and street view images in Xiamen, China to depict the geographic attributes of streets. The results can reveal nine spatio-temporal street profiles from the biking perspective, including three spatial distribution patterns and two spatial semantic patterns. Urban streets in the study area show a significant hierarchical pattern because of locations and the spatial lags of the biking behaviors. Meanwhile, the spatio-temporal characteristics of biking behaviors are the main factors of street profiles, though the street environment attributes participate in over half the number of profile types. We further evaluated the profiling ability of the proposed framework and the importance of urban street profiles using coupled characteristics. Overall, this study explored the profiling method for coupling static and dynamic characteristics of urban streets. The profiling results also help understand street usage and experiences by bikers, which have a practical value on the human-oriented classification of streets and further urban development from a geographic view.

Spatial and seasonal dynamics of zooplankton functional groups and their relationship with environmental factors in urban rivers in Haikou City, China

The urban rivers, including Changwang, Meishe, and Wuyuan in Haikou City, China, are vital water resources. Despite the rivers experiencing anthropogenic impacts, limited studies have investigated their water quality and ecological community structure. This study assessed zooplankton functional groups' spatial and seasonal dynamics relative to environmental factors in the three urban rivers. The samples were collected and analyzed seasonally between March and December 2019. The environmental factors varied significantly at spatial and seasonal scales (p < 0.05). Meishe and Wuyuan Rivers had higher electrical conductivity, salinity, TN, and TP than Changwang, which had low turbidity. Seasonally, higher TP, TN, NH3-N, and CODMn levels were found in the spring, while summer and autumn experienced high temperatures. Additionally, spring and summer had high Chl-a levels. Likewise, spring had the lowest heavy metal concentrations, while nearly all metals were elevated in winter and summer. Generally, the average metal content followed the order of Mn > Zn > Cu > Ni > As > Cr > Co > Pb > Cd. The environmental parameters were within class III of the China standard for surface waters (GB 3838–2002), suggesting negligible pollution. This study identified 159 zooplankton species, including 62 Rotifers, 50 Protozoans, 31 Cladocerans, and 16 Copepods. They were classified into 11 functional groups, dominated by Rotifers filter feeders (RF), Rotifers carnivores (RC), and small copepods and cladocerans filter feeders (SCF), followed by Middle copepods and cladocera carnivores (MCC) and Middle copepods and cladocerans filter feeders (MCF). Analysis of similarity (ANOSIM) revealed seasonal differences (p < 0.001) in zooplankton functional groups, with RF and RC most dominant in summer, autumn, and winter, while SCF, MCF, and MCC were dominant in spring. Hence, the redundancy analysis (RDA) and Pearson Correlation analysis revealed that temperature, Chl-a, TP, salinity, CODMn, NH3-N, TN, As, Co, and Cd were the main environmental factors influencing zooplankton functional groups. This study helps understand urban rivers' water quality and ecological community structure, bridging the knowledge gap. The findings are essential for water quality monitoring and management.