Urban Spatial Patterns Research Articles

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.

Review on road congestion pricing: a long-term land use effect perspective

Road congestion pricing (RCP) is an important way of controlling traffic congestion from the perspective of traffic demand management. This paper introduces the concept and four main types of applications of RCP, summarises the development of RCP theory, reveals the first- and second-order effects of RCP on transportation systems and land use, and analyses the long-term impact of RCP on the spatial location structure of land use. Relevant research progress considering land use effects is systematically and comprehensively reviewed from three research perspectives: demand modelling (pre-RCP), monitoring and analysis (post-RCP) and modelling methods (integration models and other models). The results showed that RCP will affect residents’ travel behaviour in the short term and will lead to changes in spatial location decisions in the long run, thus creating new travel demands and travel modes, affecting the transportation system and urban spatial patterns again. Implementing cordon charges has an agglomeration effect on the population in city centres. Cordon charges also have a significant negative impact on businesses in the toll area and a dispersive effect on jobs. Combined with appropriate strategies for shared autonomous vehicles, RCP can simultaneously improve transportation efficiency and regional accessibility.

Study on temperature regulation function of green spaces at community scale in high-density urban areas and planning design strategies

In recent years, the frequency of extreme high-temperature events has gradually increased. To better understand the impact of urban green space coverage's spatial pattern on land surface temperature (LST), this study selected three sample areas along the urban-rural gradient in Shanghai. Using LST inversion and resampling methods, LST data for different grid sizes were obtained for spring, summer, and winter in the 2010s, 2015s, and 2020 s. A boosting regression tree model was employed to determine the key indicators affecting LST and effective cooling thresholds. The impact of green quality, structure, and pattern at the community scale on LST was discussed, providing feasible suggestions for green space planning and design in different urban spaces. The study found significant differences in the spatial patterns of green areas and LST among the three sample regions. The quantity and integrity of green spaces in the Huangpu, Minhang, and Songjiang sample areas have progressively improved, with overall green coverages of 19 %, 38 %, and 43 %, respectively. As grid size increases, the relative influence of fractional vegetation coverage (FVC) on LST generally decreases, whereas the relative influence of green structure and patterns gradually increases. Taking the summer of the 2020 s as an example, the influence of FVC on the three study sample areas was 80.79, 83.36, and 87.18 at a 30 m grid size, which decreased to 48.87, 40.59, and 47.64 at a 120 m grid size. The green structure's impact rose from 13.09, 15.22, and 10.6–30.01, 51.82, and 38.5; the influence of green patterns increased from 6.12, 1.42, and 2.21–21.13, 7.6, and 13.86. Key indicators affecting LST include FVC (Fractional Vegetation Coverage), AREA (Green Patch Area), PD (Patch Density), COHESION (Patch Cohesion Index), and ED (Edge Density). High temperatures in summer are one of the ecological issues that need special attention in Shanghai's green space design. Setting the green space proportion to 35 % while avoiding fragmentation and low vegetation coverage can achieve effective cooling. This study's main advancement lies in utilizing machine learning algorithms to identify the principal green spatial pattern impact factors and key thresholds influencing LST at the community scale in Shanghai. The related results and proposed strategies provide a research framework and strong basis for special regulations in urban green space system planning concerning urban thermal environments. They offer references for urban renewal and new town planning to address climate change and urban high-temperature issues, such as clear requirements for optimal green space area at the community scale, community park spatial layout and quantity regulations, and urban park planning design suggestions. This study also highlights obstacles in the practical application of planning and design strategies, which can help avoid difficulties in implementing planning policies. It attempts to set goals for community-scale vegetation planning in China from a policy perspective and provides relevant recommendations.

Can government-led urban expansion simultaneously alleviate pollution and carbon emissions? Staggered difference-in-differences evidence from Chinese firms

The outward expansion of city centers is a typical feature of rapid urbanization in developing countries, leading to complex environmental pollution effects due to evolving urban spatial patterns. This study examines the impact of government-led urban expansion on pollution and carbon emissions by firms, utilizing firm and city-level data. Employing the staggered difference-in-differences (DID) method and taking the county-to-district conversion (CDC) as a quasi-natural experiment, the study finds that CDC reduced SO2 emissions by 80.95% and CO2 emissions by 13.12%. The key to this synergistic emission reduction lies in a series of source control strategies, including enhancing energy efficiency and innovation, industrial restructuring, and production reduction. Furthermore, the study reveals that CDC has a more significant effect on emission reduction for NOEs and small firms. Additionally, large cities, cities with high fiscal self-sufficiency, and cities with high per capita GDP exhibit greater environmental regulatory strength, leading to more effective emissions reduction. This paper seeks to explore potential gaps in research on the environmental impacts of government-led urban expansion, and it may provide empirical support for relevant policies in developing countries.

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.

Scale Differences and Gradient Effects of Local Climate Zone Spatial Pattern on Urban Heat Island Impact—A Case in Guangzhou’s Core Area

With the continuous development of cities, the surface urban heat island intensity (SUHII) is increasing, leading to the deterioration of the urban thermal environment, increasing energy consumption, and endangering the health of urban residents. Understanding the spatio-temporal scale difference and gradient effect of urban spatial patterns on the impact of SUHII is crucial for improving the climate resilience of cities and promoting sustainable urban development. This paper investigated the characteristics of SUHII changes at different time periods based on local climate zones (LCZs) and downscaled land surface temperature (LST) data. Meanwhile, landscape pattern indicators and the multiscale geographically weighted regression (MGWR) model were utilized to analyze the impacts of urban spatial patterns on SUHII at multiple spatial–temporal scales. The results indicated that the SUHII of each LCZ type exhibited diverse patterns in different time periods. High SUHII occurred in summer daytime and autumn nighttime. Compact and high-rise buildings (LCZ1/2/4) showed markedly higher SUHII during the daytime or nighttime, except for heavy industry. The extent of influence and the dominant factors of LCZ spatial patterns on SUHII exhibit obvious scale differences and gradient effects. At the regional scale, highly regular and compacted built-up areas tended to increase SUHII, while single and continuously distributed built-up areas had a greater impact on increasing SUHII. At the local scale, the impact of the PLAND (1/2/4/5/10) on SUHII exhibited a trend of diminishing from urban to suburban areas. In urban areas, the PLAND of LCZ 1, LCZ 2, and LCZ4 was the major factor affecting the increase in SUHII, whereas, in suburban areas, the PLAND of LCZ 2 and LCZ 10 was the major influencing factor on SUHII. The results can provide a scientific reference for mitigating urban heat island effects and constructing an ecologically ‘designed’ city.

Image-based machine learning and cluster analysis for urban road network: employing Orange for codeless visual programming

ABSTRACT In the pursuit of sustainable urban development, it is imperative to address strategies for optimizing and harmonizing the configuration of urban spatial layouts, especially in response to rapid urbanization. Urban road networks play a pivotal role in shaping intricate urban spatial patterns as they intricately weave throughout the cityscape, significantly influencing land utilization, spatial arrangements, and the mobility of residents. The urban environment is a complex system teeming with multifaceted human activities. With the continuous evolution of advanced data and computational technologies, it is now feasible to construct intricate models for an in-depth exploration of urban spatial structures. In this study, we constructed an analytical framework that leveraged road network image recognition, multi-scale influence factors analysis, and predictions using codeless visual programming. Within this framework, deep learning and unsupervised clustering are applied to complete the hierarchical clustering of road networks and exploit the intrinsic association between cities. Meanwhile, hierarchical clustering and natural and humanistic attributes of cities are connected to investigate the strength of different attributes on specific clusters. The research has the following results: (1) In addition to the alignment of urban road network clustering outcomes, quantitative unevenness and geographical heterogeneity are also observed. (2) Multiple attributes have a complicated impact on urban space, including city size, and socioeconomic and geographic characteristics. Among these factors, socio-economic variables emerge as the principal drivers influencing urban spatial structure. (3) The research enhances the model’s generalization capability and predictive accuracy. As attributes increase and model learning improves, both the Area Under Curve (AUC) and F-1 scores exhibit continuous enhancements, ultimately achieving error-free predictions. The study’s findings offer valuable insights into urban spatial structures and systems, supporting urban decision-makers in addressing challenges associated with urban growth.

Spatiotemporal dynamic relationships and simulation of urban spatial form changes and land surface temperature: a case study in Chengdu, China.

Exploring the spatiotemporal dynamic evolution of local climate zones (LCZ) associated with changes in land surface temperature (LST) can help urban planners deeply understand urban climate. Firstly, we monitored the evolution of 3D urban spatial form in Chengdu City, Sichuan Province, China from 2010 to 2020, used the ordinary least squares model to fit the dynamic correlation (DR) between the changes in urban spatial patterns and changes in LST, and revealed the changes of urban spatial patterns closely related to the rise in LST. Secondly, the spatiotemporal patterns of LST were examined by the integration of the Space-Time Cube model and emerging hotspot analysis. Finally, a prediction model based on curve fitting and random forest was integrated to simulate the LST of study area in 2025. Results show the following: the evolution of the urban spatial form consists of three stages: initial incremental expansion, midterm incremental expansion and stock renewal, and late stock renewal and ecological transformation. The influence of the built environment on the rise of LST is greater than that of the natural environment, and the building density has a greater effect than the building height. The overall LST shows a warming trend, and the seven identified LST spatiotemporal patterns are dominated by oscillating and new hotspots patterns, accounting for 51.99 and 11.44% of the study area, respectively. The DR between urban spatial form and LST varies across different time periods and built environment types, whereas the natural environment is always positively correlated with LST. The thermal environment of the city will warm up in the future, and the area affected by the heat island will shift to the central of the city.

River valley urban network and morphology: A study on the urban morphology evolution of Lanzhou.

The present study investigates the dynamic evolution characteristics of urban spatial morphology by analyzing real road network data from 2000, 2010, and 2020, along with nighttime lighting data employing spatial analysis methods and spatial syntax models. Accordingly, two separate dimensions of urban morphology: internal and external, are covered. First, the integration and synergy of interior morphology features are analyzed using spatial syntactic modeling. Subsequently, the spatial compactness, fractal dimension, and level of center of gravity shift of the city are assessed by combining the nighttime lighting data with the earlier dataset. This analysis facilitated the deep exploration of the spatiotemporal evolution of the city's external morphology. Building upon this foundation, the interaction between the "internal and external" domains was analyzed further. The main findings of the study reveal a synchronous pattern of urban expansion throughout the evolution of urban spatial morphology. Furthermore, the urban form was observed to undergo a progressive transformation, transitioning from a "single core" morphology to a "primary and secondary double core" morphology. Over time, this development progressed and evolved into a "belt-like multi-core" structure. Additionally, the coupling characteristics further validate the relationship between the structure of the road network and the urban morphology in river valley-type cities. In particular, accessibility of dense and horizontally distributed transportation network was found to significantly influence the spatial development of these cities. As observed, the findings provides valuable insights into understanding the characteristics of internal and external associations regarding urban spatial patterns.

Impact of territorial spatial landscape pattern on PM2.5 and O3 concentrations in the Yangtze River delta urban agglomeration: Exploration and planning strategies

PM2.5-O3 composite pollution has become a pressing atmospheric challenge in China. Assessing the impact of territorial spatial landscape pattern on PM2.5 and O3 concentrations within the context of territorial spatial planning will provide ideas for atmospheric governance and spatial planning. Based on the agricultural-urban-ecological space system, this study first reclassifies territorial space within the Yangtze River Delta urban agglomeration (YRDUA) and calculates multilevel and multidimensional landscape metrics. Then, variables are screened by the random forest model and collinearity test. Furthermore, the spatiotemporally heterogeneous impact of selected landscape metrics on PM2.5 and O3 concentrations is explored using the geographically and temporally weighted regression (GTWR) model, with a tradeoff-synergy analysis being conducted to propose planning strategies. The conclusions show: (1) Two pollutant concentrations have both numerical and spatial correlations. The temporal stability of concentrations' responses to metrics is increasing, while the spatial heterogeneity continues to be significant. (2) Aggregation index of agricultural production space (AP_AI) and percentage of forest area (FO_PLAND) are trade-off and synergy factors of coordinated control, respectively. Largest patch index of grassland (GR_LPI) and patch density of other ecological spaces (OT_PD) are individual factors of PM2.5 reduction. (3) Spatial zoning supported by intra-zonal and inter-zonal cooperation policies, and coordinated control guidelines centered around the utilization of agricultural production space, have been advocated. This study aims to provide theoretical supplement and practical support for urban agglomeration's atmospheric governance and territorial spatial landscape pattern optimization.

The confrontation and symbiosis of green and development: Coupling coordination analysis between carbon emissions and spatial development in urban agglomerations of China

Chinese cities face challenges of uneven development, high carbon emission intensity, and low efficiency in urbanization processes. Achieving harmonization and equilibrium between urban development and carbon emissions is crucial for sustainable development. This paper analyzes the development trajectory from 2013 to 2021 of four urban agglomerations in China: Northeast China (NEC), Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD). It identifies and calculates the urban spatial development patterns and carbon emissions, comparing the spatial-temporal variations in carbon emissions under different urban development patterns. The study also explores the coupling coordination relationship between these two aspects at various stages. The findings suggest that urban spatial development and carbon emissions are often uncoordinated in shrinking cities. In terms of coordination within urban agglomerations, BTH and NEC show suboptimal development, characterized by overall lag and polarization; YRD exhibits the best development, being consistently stable and balanced; PRD is generally improving, though with some cities lagging. Planning departments should revise urban and environmental policies to optimize spatial structures and infrastructure, aligning with regional development and promoting synergy in urban agglomerations. This research provides theoretical and empirical support for China to formulate relevant policies aimed at green, coordinated, and sustainable urban development.

Analysis of Changes in Ecological Environment Quality and Influencing Factors in Chongqing Based on a Remote-Sensing Ecological Index Mode

Chongqing is a large municipality in southwestern China, having the characteristics of a vast jurisdiction, complex topography, and a prominent dual urban–rural structure. It is vitally important to optimize the spatial layout of land and efficiency of natural resource allocation, achieve sustainable development, and conduct influence assessment and causation analysis in this region. Here, using the Google Earth Engine platform, we selected Landsat remote-sensing (RS) images from the period 2000–2020 and constructed a remote-sensing ecological index (RSEI) model. Considering the urban spatial pattern division in Chongqing, the Sen + Mann–Kendall analytical approach was employed to assess the fluctuating quality of the ecological environment in different sectors of Chongqing. Subsequently, single-factor and interaction detectors in the Geodetector software tool were used to conduct causation analysis on the RSEI, with the use of eight elements: elevation, slope, aspect, precipitation, temperature, population, land use, and nighttime lighting. Findings indicate that, over the course of the investigation period, the eco-quality in Chongqing displayed a pattern of degradation, succeeded by amelioration. The RSEI decreased from 0.700 in 2000 to 0.590 in 2007, and then gradually recovered to 0.716 in 2018. Overall, the eco-environment quality of Chongqing improved. Spatially, changes in the RSEI were consistent with the planning and positioning of the urban spatial pattern. The main new urban area and periphery of the central urban area showed a slight deterioration, while other regions showed marked improvement. The combined effect of any two elements enhanced the explanatory power of a single factor, with elevation, temperature, and land use being the strongest explanatory elements of eco-quality in Chongqing. The most influential factor explaining the spatial variation of the RSEI was determined to be the combined impact of elevation and land use. At the temporal scale, elements related to human activities showed the most evident trend in explanatory power.

Study of the Correlation between the Urban Wind–Heat Environment and Urban Development Elements in High-Density Urban Areas: A Case Study of Central Shanghai

To prevent damage to human life and health caused by high temperatures and extreme weather and to promote sustainable urban development, it is necessary to optimize the layout of urban development elements to improve the urban wind–heat environment. Taking the high-density urban area of Shanghai as an example, this study used wavelet analysis to investigate the cyclic changes of the average annual temperature of Shanghai from 1950 to 2022 and the average annual wind speed of Shanghai from 2000 to 2020. The correlation between the urban heat environment and the urban development elements was analyzed using geographically weighted regression. The correlation was then examined using BP neural network, and finally, the impacts of different urban spatial patterns on the wind environment were analyzed using CFD numerical simulation. The results show that the average annual temperature of Shanghai city has an overall upward trend, with significant cycles of 44 and 32 years that are shortening over time. The average annual wind speed has a downward trend, with a significant main cycle of 22 years. Greening and water coverage, as well as the floor area ratio, have a significant reducing effect on surface temperature, whereas building density is positively correlated with surface temperature. Building density has a significant reducing effect on wind speed, whereas the effect of floor area ratio is not significant. The effect of building density on wind speed is significantly weakened, whereas the effect of the floor area ratio is not significant. This study provides valuable references for Shanghai and other high-density cities to optimize urban spatial patterns in order to improve the safety and comfort of the urban wind–heat environments. This study is of significant importance and value in promoting sustainable urban development, protecting the health of urban residents, and advancing spatial justice and equal well-being.

Can spatial patterns mitigate the urban heat island effect? Evidence from German metropolitan regions

This study examines the efficacy of urban spatial patterns at alleviating the urban heat island (UHI) effect in Germany’s city regions ( Großstadtregionen) using multivariate and non-parametric regression methods. Urban spatial patterns are quantified using five landscape metrics that capture the spatial arrangement of urban footprints and greenspaces, along with a polycentricity index that measures the distribution of human activities. The results indicate that certain features of urban fabric, including fragmentation, mixed land use, and regular-shaped urban patches, have the potential to mitigate the UHI effect. Moreover, dispersing multiple smaller greenspaces throughout the urban area demonstrates a greater cooling effect compared to having a single large and more aggregated park. In addition, our analysis reveals that a doubling (100%) of the polycentricity degree corresponds to a significant decrease in both day- and night-time UHI effects, with reductions of 10.4% and 24.6%, respectively. This study confirms that polycentric development yields greater benefits in reducing urban heat for large-sized city regions compared to medium- and small-sized ones; and its effectiveness is mostly pronounced near urban center(s). These findings suggest that polycentric development represents an efficient and feasible strategy for urban thermal planning of large-sized city regions, surpassing other commonly discussed urban configurations, such as compact or dispersed urban development.

Urban express logistics connection network and spatial balance pattern in the Yangtze River Delta

Urban express logistics connection network and spatial balance pattern in the Yangtze River Delta

Optimization of urban spatial pattern under carbon emission constraints: Theoretical framework, index system and practical paths

Optimization of urban spatial pattern under carbon emission constraints: Theoretical framework, index system and practical paths

The coupling relationship and driving mechanism between urbanization and ecosystem services in the Yellow River Basin from a multi-spatial scale perspective

Rapid urbanization has led to ecological destruction and associated issues. Macro policies wield substantial influence over urbanization and its relationship with the environment. Without considering the differences in scale, macro policies may be ineffective at addressing urbanization’s adverse impacts on the environment, and even worsen this relationship. We used data on 622 counties, 76 prefectures, and 7 urban agglomerations in the Yellow River Basin to examine the development level, coupling coordination degree, and spatial patterns of urbanization and ecosystem services at three scales during 2000–2020. Further, we explored the driving mechanisms in the relationship between urbanization and ecosystem services. We found that: First, the coupling coordination was relatively low but showed an upward trend. A sizeable spatiotemporal difference existed, with higher (lower) coordination in the east (west). Second, the coupling coordination of each scale exhibited significant spatial positive correlations. The low-value heterogeneous region was embedded around the agglomeration region, and polarization was significant. The larger the scale, the stronger the agglomeration effect. Further, the coupling coordination spatial agglomeration effect of each scale gradually weakened over time. Third, the spatial and temporal distributions of coupling coordination and its agglomeration characteristics at different scales differed. The urban agglomeration scale showed significant overall coordination or agglomeration characteristics, and prefecture and county regions showed local and unique characteristics within urban agglomerations. Fourth, the dominant factors influencing the spatial patterns of the coupling coordination at the county, prefecture, and urban agglomeration scales differed. The interaction and factor detection showed linear and double-factor enhancements. We find that economic development, government policies, environmental protection, and natural factors are the combined effects of urbanization and ecosystem services. Our research method can provide a reference for other river basins, and the results can help governments in formulating policies for sustainable development at different spatial scales.

Transit-oriented development, development corridors and economic access: The Louis Botha development corridor’s impact

Apartheid’s impact on South Africa’s urban spatial patterns persists, resulting in spatial fragmentation and inequality. Unsustainable urban sprawl exacerbates challenges related to economic access. To address said challenges, the City of Johannesburg (CoJ) implemented the Corridors of Freedom (CoF) initiative, emphasising economic inclusion. Amid substantial public sector investment, the initiative prioritised the Louis Botha Development Corridor (LBDC) to create a dense, mixed-use, walkable urban environment. However, limited research investigated the LBDC’s impact from an economic access perspective. This study investigates how the LBDC has improved economic access and provides policy insights for urban areas in South Africa, within the conceptual framework of transit-oriented development (TOD) and development corridors. A quantitative research approach using Network Analyst reveals that the Rea Vaya Bus Rapid Transit (BRT) system increased economic access by 16% compared to other LBDC transport services. This study demonstrates the potential of the dual implementation of TOD and development corridors to foster economic access in the study area and concludes with policy recommendations centred on cross-departmental collaboration, feasibility studies and risk allocation, location-based criteria and transit accessibility targets, transit-oriented design guidelines, and integrated transport systems.

A COMPREHENSIVE MEASUREMENT MODEL FOR JOB-HOUSING BALANCE CONSIDERING SPATIAL INTERACTIONS: A CASE STUDY IN SHANGHAI

Abstract. Assessing jobs-housing balance (JHB) is crucial for the optimization of urban spatial pattern and transportation planning. However, due to the limitations of traditional data and the inability to integrate evaluation indicators, the evaluation results may be bias, conflicting with common sense. Considering interaction of multiple factors, a Job-housing balance measurement model (JHBM-SEM) was proposed to accurately evaluate the degree of JHB in a certain area. To address the problem of multi-indicator fusion, the structural equation model is used to incorporate the advantages, limitations and complementary relationships of each evaluation indicator into the evaluation process. A function relationship is defined between factor loadings, path coefficients, and variable scores to construct the measurement model and obtain comprehensive evaluation results. In addition, by integrating multi-source spatiotemporal big data mainly based on mobile signaling data, the paper can effectively mine the current status of job-housing balance in cities, and solve problems such as low precision and granularity of traditional data. The model was validated using Shanghai as an example, and the results show that compared with classical methods, the model's results are more consistent with the real situation of regional jobhousing patterns. It can identify the pseudo-balance phenomenon in underdeveloped areas of the suburbs and make reasonable evaluations, and the intermediate process can explain the direction of the imbalance factors in the region.

Examining the urban regeneration of public cultural space using multi-scale geospatial data: a case study of the historic district in Jinan, China

Introduction: Historical-cultural landscapes and urbanscapes integrate regional culture, collective memory, urban patterns, living habits, and other related historical and spatial information, and are important places for expressing the values of urban space. This study analyzes cultural landscapes and urbanscapes from the perspective of spatial values, taking the Baihuazhou historic and cultural district in Jinan as an example to analyze the spatial identification of public cultural space. The significance of this research lies in examining the urban regeneration of public cultural space using multi-scale geospatial data from both an objective and subjective perspective. This methdology is based on a large body of previous literature in relation to cultural heritage, and draws on a comprehensive understanding of the field.Methods: This study applies spatial syntax, visual graph, and survey analyses, focusing on urban spatial patterns, spatial culture, and spatial memory as heritage values.Results: The analysis results reveal that historic districts generally do not have good accessibility, predominantly because of the disorganized texture of the buildings and absence of spatial consistency.Discussion: There should be improved dynamic spatial identification and accessibility in older urban environments and enhancement of local spatial identification memory by increasing sightline accessibility. Based on consideration of values, corresponding suggestions are made from the three perspectives of urban space, cultural landscapes, and local collective memories to provide a reference for the protection of the Baihuazhou historic district and promote the preservation and development of similar heritage spaces.