Built-up Environment Research Articles

Hypertension risk pathways in urban built environment: the case of Yuhui District, Bengbu City, China.

The rapid development of urbanization has brought about changes in residents' living environment and behavior, leading to health challenges such as hypertension. An improvement in the built-up environment in the community could contribute to the construction of a healthy city, promote the active life of the residents, and prevent and relieve hypertension. However, there is little research on the relationship between the built environment of the community and hypertension. This cross-sectional study aims to evaluate the relationship between communities' built environment, health behavior, and hypertension grade of residents in Yuhui District of Bengbu City. This study is based on data from the 2022 Health Survey of Residents in 21 communities. To investigate the impact of the community's built environment on residents' hypertension and the underlying mechanisms, regression and structural equation modeling were employed. The results show that the built environment of urban communities has a significant impact on the residents' hypertension. The presence of high densities of supermarkets, convenience stores, parks and plazas, but low densities of clinics and hospitals, has been identified as a significant risk factor for the development of high blood pressure among the residents. Nevertheless, the adoption of healthy behaviors, including regular walking, physical activity, and a diet rich in fruit and vegetables, can play an important role in reducing the risk of hypertension. The findings of this study show that enhancements to the built environment in urban neighborhoods could contribute to a reduction in the prevalence of hypertension among residents. Furthermore, the implementation of efficacious health interventions in urban settings would facilitate the alteration of residents' health behaviors and enhance their overall health status.

Examining the suitability of the local climate zones (LCZ) framework in informal urban settlements: Insights from Kabul, Afghanistan

To better investigate the Urban Heat Island (UHI) effect, a standardized framework known as Local Climate Zones (LCZ) has been developed and widely applied to numerous cities. However, cities from least-developed countries with heterogeneous typologies are underrepresented in the LCZ literature. This study assesses the applicability of the LCZ framework in the slum-dominant built-up environment of Kabul. Using a combined method involving GIS and remote sensing, we classified natural and built-type LCZs and analyzed LCZ-LST fluctuations. The analysis revealed that four new subclasses cover 23 % of the built type LCZs: LCZ 35 (mid/high-rise buildings within compact lowrise layouts) and LCZ 65 (midrise buildings among open lowrise areas) have the lowest LSTs at 34.36 °C and 34.42 °C in July, respectively. In contrast, LCZ 73 (two/three-story buildings in lightweight configurations), and LCZ 9F (sparse buildings on bare soil or sand) have higher LSTs at 37.2 °C and 38.6 °C in July, respectively. These subclasses showed distinct zone parameter thresholds compared to standard LCZs. In most built-type LCZs, Average Building Height (ABH) and Pervious Surface Fraction (PSF) negatively influenced LST, while impervious surfaces and Sky View Factor contributed to higher LST. Based on the findings, LCZ-specified strategies (Vegetation, urban form, and using high-albedo materials) for LST mitigation are proposed. Furthermore, we provide planning, design, and policy recommendations aimed at mitigating urban heat, with potential applicability to other cities facing rapid urbanization and growth of informal settlements. The findings can inform action toward urban climate change adaptation.

Integrating Spatiotemporal Analysis of Land Transformation and Urban Growth in Peshawar Valley and Its Implications on Temperature in Response to Climate Change

Examining the interconnected dynamics of urbanization and climate change is crucial due to their implications for environmental, social, and public health systems. This study provides a comprehensive analysis of these dynamics in the Peshawar Valley, a rapidly urbanizing region in Khyber Pakhtunkhwa, Pakistan, over a 30-year period (1990–2020). A novel methodological framework integrating remote sensing, GIS techniques, and Google Earth Engine (GEE) was developed to analyze land use/land cover (LULC) changes, particularly the expansion of the built-up environment, along with the land surface temperature (LST) and heat index (HI). This framework intricately links these elements, providing a unique perspective on the environmental transformations occurring in the Peshawar Valley. Unlike previous studies that focused on individual aspects, this research offers a holistic understanding of the complex interplay between urbanization, land use changes, temperature dynamics, and heat index variations. Over three decades, urbanization expanded significantly, with built-up areas increasing from 6.35% to 14.13%. The population surged from 5.3 million to 12.6 million, coupled with significant increases in registered vehicles (from 0.171 million to 1.364 million) and operational industries (from 327 to 1155). These transitions influenced air quality and temperature dynamics, as evidenced by a highest mean LST of 30.30 °C and a maximum HI of 55.48 °C, marking a notable increase from 50.54 °C. These changes show strong positive correlations with built-up areas, population size, registered vehicles, and industrial activity. The findings highlight the urgent need for adaptive strategies, public health interventions, and sustainable practices to mitigate the environmental impacts of urbanization and climate change in the Peshawar Valley. Sustainable urban development strategies and climate change mitigation measures are crucial for ensuring a livable and resilient future for the region. This long-term analysis provides a robust foundation for future projections and policy recommendations.

Protests in urban environments: review and research agenda

Abstract Although knowledge about the role of space in the field of social movement studies is already well established, it is rarely discussed within the framework of urban spatial design (with some important exceptions). We consider not only how political power is related to architectural design in urban environments but also how it is performed (and contested) during protests within these spaces. We argue that urban spatial planning should address the dual nature of street demonstrations. Public assemblies are seen as symbols of democracy, but they are also disruptive and may turn into riots. This tension is evident along two design lines: facilitating and obstructing street demonstrations in a built-up urban environment. In our essay, we show that street protests are an immanent part of neoliberal democracy, and that cities cannot avoid street demonstrations or simply exclude them in the design process.

Quantitative Analysis and Spatial Pattern Research of Built-Up Environments and Surface Urban Heat Island Effect in Beijing’s Main Urban Area

Quantitative Analysis and Spatial Pattern Research of Built-Up Environments and Surface Urban Heat Island Effect in Beijing’s Main Urban Area

Unsupervised Domain Adaptation with Contrastive Learning-Based Discriminative Feature Augmentation for RS Image Classification

High- and very high-resolution (HR, VHR) remote sensing (RS) images can provide comprehensive and intricate spatial information for land cover classification, which is particularly crucial when analyzing complex built-up environments. However, the application of HR and VHR images to large-scale and detailed land cover mapping is always constrained by the intricacy of land cover classification models, the exorbitant cost of collecting training samples, and geographical changes or acquisition conditions. To overcome this limitation, we propose an unsupervised domain adaptation (UDA) with contrastive learning-based discriminative feature augmentation (CLDFA) for RS image classification. In detail, our method first utilizes contrastive learning (CL) through a memory bank in order to memorize sample features and improve model performance, where the approach employs an end-to-end Siamese network and incorporates dynamic pseudo-label assignment and class-balancing strategies for adaptive domain joint learning. By transferring classification models trained on a source domain (SD) to an unlabeled target domain (TD), our proposed UDA method enables large-scale land cover mapping. We conducted experiments using a massive five billion-pixels dataset as the SD and tested the HR and VHR RS images of five typical Chinese cities as the TD and applied the method on the completely unlabeled world view 3 (WV3) image of Urumqi city. The experimental results demonstrate that our method excels in large-scale HR and VHR RS image classification tasks, highlighting the advantages of semantic segmentation based on end-to-end deep convolutional neural networks (DCNNs).

Setting up a CFD model to evaluate the impact of green infrastructures on local air quality

AbstractGreen infrastructures have been pointed out as innovative solutions to deal with current and future challenges related to air pollution and climate change. Although the potential of green infrastructures, such as green walls and green roofs, to mitigate air pollution has been documented, evidence at a local scale is still limited. This work aims to increase knowledge about the potentialities of green infrastructures in improving local air quality, focusing on particulate matter, nitrogen dioxide and ozone pollutants, and by using a local-scale computational fluid dynamics model. The ENVI-met model was applied to a particular hour of a summer day over a built-up environment centred on a main avenue in the city of Lisbon (Portugal). The dimensions of the computational domain are 618 m × 594 m × 143 m, and it contains 184 buildings, with the tallest building being 56 m. In addition to the baseline simulation, modelling was also done considering the application of green walls and green roofs to specific buildings located near the main avenue, together with a green corridor. The overall results show no disturbances exerted by green walls on the turbulent flow dynamics and on the air quality levels when compared to the baseline scenario (without green walls). The integrated scenario, which includes green walls, green roofs and a green corridor, will lead to potential local benefits of green infrastructures on O3 concentrations, followed by variable impacts on NO2 and particulate matter concentrations.

Impact of Land Use and Land Cover Changes on Ecosystem Services Value in Mwanza City, Tanzania

Ecosystem services are vital services that support life and are the basis for human socio-economic progress. However, changes in land use and land cover (LULC) brought about by urban expansion degrade them. Thus, analysing the impact of land use and land cover (LULC) change on ecosystem service values (ESVs) is crucial for understanding and informing resource policy decisions. This study aims to analyse the impact of land use and land cover changes on ecosystem service values in Mwanza City, Tanzania. To achieve that, the benefits transfer approach was employed to analyse the changes in ESV in response to LULC. We estimated and analysed changes in ESV using satellite image datasets from 1999, 2009, and 2019. The LULC classes that were identified are vegetated land, agricultural land, waterbodies, built-up area, and bareland. The results exhibit that Mwanza City experienced significant LULC changes. While vegetated land, agricultural land, and bareland decreased by 49%, 15%, and 36%, respectively, the built-up area and water bodies increased by 568% and 48%, respectively, during the two decades. The total ESV decreased from 31.35 million US dollars to 26.3 million US dollars between 1999 and 2009 and to 23.96 million US dollars between 2009 and 2019. The waterbodies increased due to the increased volume of water in streams that expanded the floodplains, which resulted from surface runoff attributed to increased paved surfaces as more land was converted into a built-up environment upstream. The built-up area and bareland contributed nothing to ESV. However, the built-up area was the driving force behind the reduction of ESV in other LULC classes, as it was encroaching on them. The study concludes that the decrease in ESV reflects the degradation of ecosystem services due to the change in LULC. Hence, it is recommended that sustainable management of ecosystems be adhered for the proper functioning of the earth’s life-support system.

Impact of Urban built-up volume on Urban environment: A Case of Jakarta

In this paper, the spatial patterns of urban form (e.g., 2D and 3D characteristics) from 2000 to 2020 in Jakarta are assessed and the interdependent relationships between urban built-up volume and urban environment are examined. Jakarta experienced rapid urban built-up land expansion of 19 %, from 483 km2 in 2000 to 574 km2 in 2020 but with moderate urban built-up volumetric expansion at 4 %, from 23.6 × 108 m3 in 2000 to 24.5 × 108 m3 in 2020. The inverse S-shaped function revealed that urban land density declined from the city center to surrounding areas in Jakarta. Urban built-up area expanded outward at a much faster rate than upward, reflected by the D value, i.e., the radius of the central city area. The D value remained around 17 km from 2000 to 2020 for 3D but grew substantially from 28 km to 50 km for 2D during the same period. Furthermore, structural equation model (SEM) analysis showed that, while increases in urban built-up volume are associated with increases in urban green space, with a path coefficient of 0.620, they also are linked with worsening air pollution and urban heat islands, with statistically significant path coefficients of 0.304 and 0.440, respectively.

Restoration of Kano Metropolitan Built Environment’s Vegetative Enclaves

Kano metropolis has over the years witnessed constant redevelopment of green corridor and reserve urban spaces within residential spaces and along major route which spines into commercial and public buildings. This is due to the pressure of urban expansion of the built-up environment. However, these changes do not take into considerations the social, physical and economic factors as such; the redevelopment has altered the built-up areas affecting the relationship between man and his built environment. The study is aimed at restoration of Kano Metropolitan Built Environment’s Vegetative Enclaves as they generate urban patterns through the use of green spaces to induce proper urban growth. Data were collected from the six area councils that make up Kano metropolis and analyzed using seventeen (17) identified attributes on effect of vegetation on the built environment. Descriptive statistics such as Simple distribution frequency (SDF) and Mean weighted score (MWS) were used to analyze the data presented, while inferential statistics employed was relative satisfaction index which was used to rank the environmental scores. Findings showed that the urban open space features significantly affect the level of residents’ satisfaction. The RSI scores for the relatively impact of vegetation on Kano metropolis are on the significance rating (RSI: 0.70 – 0.74 to 0.60- 0.69 corresponding to “Low Impact” and “Less Impact” respectively for most of the attributes, while fewer attributes such as “improved urban environment, improved lively and enhance city image” are areas of significance “high impact” rating, with RSI (0.75 and above). The study recommends the implementation and adherence to strong urban growth management law within the Kano metropolis, as a measure for sustaining the degraded environment and impacts of rapid urban growth in Kano metropolis

Traditional and Modern Disaster Resistant House Construction Techniques

A large portion of the wealth of any nation is invested in its built-up environment viz, housing, infrastructure, industrial and commercial facilities. The quality of this built-up environment, expressed in terms of durability, safety and functionality, is a determining factor for the quality of life and economic development of the society, and the competitiveness of its industry and services. Extensive loss of this wealth is caused by natural disasters that strike periodically. A natural disaster is an event of nature that causes sudden destruction, damaging the economy and social structure on a massive scale. The calamity results in a huge financial burden in terms of relief and rescue operations. All-round decline in production, unemployment, indebtedness as well as increased cost of goods and services are the other debilitating results of natural disasters. This research paper deals with the traditional as well as modern disaster resistant construction techniques to meet the aftermath of disasters. It examines the issue of damage to Reinforced Concrete Cement (RCC) buildings by underlying the necessity of adherence to building codes and standards. Some recent advances in housing technology are also highlighted.

Exploring the spatial interplay between built-up environments and surface urban heat island phenomena in the main urban area of Shanghai

The urban built-up environment, consisting of buildings, roads, and various facilities, plays a crucial role in forming surface urban heat islands (SUHI). This study aims to address this issue by creating a comprehensive indicator system for the urban built-up environment, drawing from previous research. By employing multi-source data and diverse geospatial processing methods, this article examine the influence of 20 environmental factors on the spatial and temporal variability of SUHI in Shanghai during the summer and winter seasons from 2016 to 2020. This article findings reveal four key observations. (1) The average SUHI intensity in Shanghai's main urban area during the summers of 2016–2020 showed an increasing trend, with the heat island's shape and location differing between seasons. (2) The correlation values (R-values) between the built and road environment indicators and SUHI changed with season and year, reflecting the dynamic interplay among urban morphology, weather conditions, and human activities that affect heat generation and dissipation. (3) This article found that the increasing SUHI trend was not solely dependent on changes in individual built-up environment parameters. (4) This article analysis demonstrated that the built environment factor significantly influenced heat island intensity in summer, while the green space environment factor had a substantial impact during winter. In conclusion, the results emphasize the complex relationship between the urban built-up environment and SUHI, highlighting the need to consider various environmental factors when assessing their impact on SUHI formation. This study offers valuable insights to inform the development of effective strategies for mitigating the negative effects of SUHI on urban environments and promoting sustainable urban development.

Constructing a multi-functional small urban green space network for green space equity in urban built-up areas: A case study of Harbin, China

Ensuring equitable access to green spaces in urban built-up areas is not only vital for fostering environmental justice but also aligns with the United Nations Sustainable Development Goals (SDGs). However, there is a noticeable gap in the current body of research regarding the role of small urban green spaces, especially their multifunctionality from an ecosystem services perspective. Taking the urban built-up area of Harbin as an example, this study first applied the Analytic Hierarchy Process to classify the supply and demand of green space into three types. Then, the article further analyzes the potential functional positioning of the newly added green spaces, including ecological and social functions, using Minimum Cumulative Resistance and Point of Interest. Finally, multi-criteria decision models are used to explore the priority and functional positioning of green space and construct a multi-functional and highly-efficient small urban green space network. The results indicate a significant imbalance in green space supply and demand, with severe and medium mismatch areas accounting for 30.17 % and 48.50 %, respectively. By assessing the multifunctionality of small green spaces, we propose guidelines that include five types of areas: Concentrated Development (85.85 km2, 16.94 %), Backup Development (70.74 km2, 14.31 %), Maintenance (304.49 km2, 61.51 %), Protection (14.94 km2, 3.02 %), and Optimization (20.89 km2, 4.22 %). Finally, the article proposes a 277.60 km multifunctional small urban green space network. By examining small urban green spaces, this study crafts a pivotal framework for enhancing green space equity in urban built-up environments, providing valuable insights for policymakers and urban planners. The approach has significant implications for developing multifunctional green networks in varied urban contexts and offers a model for wider application, serving as a reference for achieving green space equity in developing countries globally.

A study on the coupled effects of climate and built environment elements at urban block scale——A case study of Fengtai district in Beijing

ABSTRACT In recent years, rapid city development has significantly impacted the microclimate environments in urban blocks. Many studies have shown that varied built-up environmental factors lead to corresponding degrees of influence on microclimate. Urban blocks are one of the most concentrated urban settlements, and their impact on the urban climate and environment cannot be ignored. Taking the Fengtai district in Beijing as an example, using the ArcGIS platform inputted with meteorological data and built-up environment data, this study selected climate-sensitive units in the Fengtai district, of which 746 highly sensitive block units were obtained. SPSS software was used to analyze the correlation between built-up environmental factors and climate elements, and the relationship between the degree of influence and magnitude was analyzed using a regression equation. An optimization strategy for built-up environments on an urban block scale was proposed. A model for improving the climate environment at the urban block scale is summarized. Coupling study between climate environment and influencing factors at the urban block scale is an effective way to deal with the improvement of the urban microclimate environment and refinement transformation in the post-epidemic era.

Constructing a Composite Disaster Resilience Index towards Natural Disasters in Mauritius

Mauritius is a Small Island Developing State (SIDS) which faces regular environmental hazards due to its geographical location. Building disaster-resilient communities has become the goal of many disaster risk reduction (DRR) frameworks. This study aimed at quantifying the resilience of the population of Mauritius towards natural disasters using statistics drawn from secondary sources of data. A Composite Disaster Resilience Index (CDRI), which ranged from 0 to 100, was established. Four indicators and sixteen sub-indicators which reflected domains of resilience in terms of community capacity, economic, built-up environment and social, were used to develop the CDRI. Geographic Information System (GIS) was used to map the CDRI across 144 administrative areas, which included 124 Village Council Areas (VCAs) and 20 Municipal Council Wards (MCWs), for a visual representation. Resilience indices were classified into least and most resilient. Results showed a spatial variation in resilience levels towards natural disasters across the administrative areas. Nearly fifty percent of the eleven most resilient communities were found in urban areas (MCWs). Twelve administrative areas were the least resilient towards natural disasters and emerged from rural (VCAs) and marginalised areas only. Coastal villages of Grand Sable, Quatre-Soeurs, Bambous-Virieux, Le Morne and Case Noyale formed a cluster of least resilient communities along the East coast. A t-test analysis revealed a statistically significant difference in resilience levels between urban and rural regions at p < 0.05. Results suggested that infrastructure and the social capacity building were likely to be less developed in rural areas than in urban areas. Findings also demonstrated that most VCAs and MCWs performed less well in community resilience when compared to the rest of the dimensions of resilience. Results provided evidence with potential to help decision-makers in the allocation of resources to improve resilience in Mauritius.

Assessing completeness of global airport data in OSM

Abstract. Airports are not only important infrastructure for both civil and military use but also have significant impacts on socio-economic development and the built-up environment. OpenStreetMap (OSM) can be an essential data source for acquiring various airport elements, but few studies have investigated data quality. To fill this gap, this study aims to assess the quality (especially completeness) of airport data in OSM by comparing it with locations of airports acquired from the OurAirports platform. More precisely, the three different types (large, medium, and small) and the four different elements (runway, taxiway, apron, and terminal) of airports are assessed for over 40,000 airports worldwide. Results show that completeness varies depending on types, elements, and geographical regions. Specifically, 1) almost all large airports are complete; most medium airports are also complete; but most small airports are not complete. 2) The runway element is much more complete than the terminal element. 3) In most cases, completeness is relatively high in India, China, and Northern Africa but relatively low in Canada, the United States, Russia, and Australia, where the total number of airports is much larger. We conclude that most large and medium airports in OSM have been mapped well. The reasons for incomplete airport data in OSM and potential applications of OSM airport data are also discussed.

The built-up environment modulates the association of artificial night-time lights with the urban extent

ABSTRACT Artificial night-time light (NTL) emissions, collected by satellites, are a reliable and widely used remote proxy for urban extent. Recently, it was demonstrated that NTLs are stronger associated with the total volume of the buildings than with their total footprint area, a traditional urban extent measure. However, this finding may not be a general rule: We presume that both associations are sensitive to characteristics of the built-up environment, while the latter is known to be quite heterogeneous within and between cities. Moreover, we hypothesize that at least in specific built-up environments, NTL may even stronger correlate with another urban extent measure – the total lateral surface area of the buildings, due to its more accurate proportionality to the area of light-emitting windows. The present study uses NTLs and buildings datasets of 38 European capital cities and compares the associations of NTLs with the three aforementioned urban extent measures (the total footprint area, the total volume, and the total lateral surface area of the buildings) across different built-up environments. The results indicate that in urban areas characterized by a high density of tall buildings the strongest observed association is between NTLs and the building’s footprint area. In comparison, the total volume of buildings is better related to NTLs in urban areas that host compact settings of relatively small buildings. But there is a third type of physical urban configuration, characterized by large buildings sparsely distributed in space. In this type of urban area, the strongest observed association is between NTLs and lateral surface area. We conclude that monitoring urban growth using NTLs will benefit from a preliminary assessment of the local built-up characteristics.

Effects of Traffic on Particulate Matter (PM2.5) in Different Built Environments

Globally, vehicular pollution is one of the greatest concerns in urban areas. Several studies on air pollution have been conducted using deterministic, statistical, and soft computing methods. However, there has been little research on how soft-computing methods like Artificial Neural Networks (ANN) can help us comprehend vehicular pollution’s non-linear and highly complex dispersion. This study uses an ANN-based vehicular pollution model to investigate the effect of vehicular traffic on PM2.5 concentrations in built-up and open terrain-surrounding environments. Five distinct pollution models were developed for two locations in Delhi, considering PM2.5 pollutants, meteorological variables, traffic flow, and traffic composition into account. The results concluded that under open terrain conditions, the significance of the traffic variable in its association with PM2.5 is almost half the significance observed under built-up conditions. Also, in terms of PM2.5 reductions, the maximum reduction observed at Location-1 (built-up environment), and Location-2 (open terrain environment) is 1.85 and 2.44 times the percent reduction in traffic during peak hours, respectively. The study’s findings have significant ramifications for the current practices of ignoring the contribution of traffic and the built environment to pollution and adopting measures like an odd-even rule and high fuel and parking prices to combat pollution.

Ethiopian urban land allocation policy and its contribution to urban densification

Urban densification is considered as the best tool for efficient urban land utilization, containment, and minimizing urban development costs. It is also a widely accepted approach to mitigate shortages of urban land and urban sprawl. With this in mind, Ethiopia has adopted a standard-based urban land allocation policy. The policy relies on population size during the urban planning process to address issues related to sustainable urban development by increasing the densities of its urban areas. However, the impact of the existing urban land allocation policy on urban densification has not been investigated adequately. Thus, this study examines the contribution of existing urban land allocation policies to urban densification in Ethiopia. A mixed research approach was employed to achieve the objective of the study. The study revealed that the policy gives more attention to the immediate and tangible conditions than the efficient use of land resources. Therefore, it allocated an average of 223 square meters of land to each person for urban development. The study implies that the country's urban land allocation policy is ineffective in achieving the intended outcome of urban densification. Instead, coupled with uncontrolled urban population growth, it has been exacerbating the rapid horizontal expansion of urban areas. With the current trend of horizontal expansion of urban areas, the country's land resources is expected to be converted into a built-up environment within the next 127 years unless the policy is radically changed. Thus, this paper calls for revisiting the existing urban land allocation strategy of the country in a way that responds towards efficient urban land allocation and sustainable urban development.

The nonlinear relationships between built environment features and urban street vitality: A data-driven exploration

The relationship between the built environment and urban street vitality, as a key issue of contemporary urban design, has been discussed over decades. However, most existing studies relying on linear regression models do not reveal the complicated impacts of built environment features and often neglect their threshold effects. As a response, this study applies the gradient boosting decision tree (GBDT) model with a large amount of new urban data to explore the in-depth understanding of urban street vitality. Based on the street samples from 12 Chinese cities, a series of morphological, functional, and human-scale features were analyzed together with socioeconomic indicators as control variables. The street vitality is measured by street activity intensity computed from billions of location-based service records. The results show that the nonlinear model brings an overall improvement in resolution. Specifically, compared with the functional and human-scale features, the morphological characteristics, especially the street intersection density, average block size, and building density, are dominant contributors to street vitality. It is also worth noting that most built-up environment features obtain the threshold effects on street vitality, which means there is a turning point where the effect of features changes. The interaction between built environment characteristic variables is common and can be divided into two typical types. Insights achieved in this study help to indicate an effective interval of built environment characteristics on vitality, which was missed in previous studies, and thus contribute to more precise urban design practices. Moreover, by clarifying the interaction influence mechanism, this study emphasizes the need for the planner to exploit synergies between variables through optimal combinations while avoiding their antagonistic effects.