Journal of Urban Planning and Development

An investigation is reported on bus bunching and its spatiotemporal patterns that considers six bus routes in Kolkata City, West Bengal, India. With historical GPS data as inputs, bunching occurrences are identified using the spatiotemporal–density-based spatial clustering of applications with noise (ST–DBSCAN) algorithm. To determine the impact of bunching on various bus stops, k-means++ clustering was used on top of ST–DBSCAN, and subsequently, spatiotemporal bunching patterns were investigated. Some bus stops are consecutively impacted by bunching; however, others are impacted in an isolated manner. To capture the spatiotemporal propagation of bunching, a new indicator termed the propagation ratio is proposed, which could classify the bunching as propagating or isolated. Bunching occurrences are propagating for some bus routes and isolated for others, which justifies the need to prioritize routes displaying propagating nature. Of interest, bunching is identified on high and low-frequency bus routes, which indicates the need to relook at the operational planning of all the bus routes regardless of their frequency. At times, excessive bunching is detected during lean periods of the day, which suggests the necessity of modifying the dispatching headways that are based on passenger demand during these lean periods. The outcomes from this work further indicate that all the bus stops along a bus route are not equally impacted by bunching. The spatiotemporal cluster plots could successfully capture the initial bunching occurrence points and their variation with time, which could provide an opportunity for the operators to apply time-varying remedial measures. The insights developed from this work could be used advantageously by operators and policymakers for mitigating bus bunching and improving the urban bus service.

The speed of urbanization in China has been unprecedented, and its driving force has been given much attention in the field. Previous literature analyzes the driving factors of China's urbanization from various aspects, including the economy, population, transportation, housing, and other market factors. However, this study explored the influence of power factors on urbanization from a new perspective of city leaders. Based on the panel data from 285 Chinese cities from 2006 to 2017, a fixed effects model was used to analyze the influence of city leaders’ power hierarchy and promotion pressure on the speed of land and population urbanization. The main conclusions are as follows: First, the power hierarchy of party secretaries has a significant positive impact on land urbanization speed. Party secretaries with a higher position hierarchy can promote land urbanization speed. Second, the promotion pressure of party secretaries exerts a significant impact on land urbanization speed. An inverted “U” relationship has been observed between the age of party secretaries and the speed of land urbanization. The speed reaches its maximum when party secretaries are approximately 56 years old. Furthermore, party secretaries’ tenure has a positive and significant impact on land urbanization speed. Third, the power hierarchy and promotion pressure of party secretaries have no significant impact on the population's urbanization speed. In addition, this research finds that land finance acts as a mediating factor in the influence of party secretaries’ power hierarchy and promotion pressure on land urbanization speed. The conclusions can provide suggestions for improving official evaluation mechanisms and expanding financing for urban construction to promote the development of new human-centered urbanization in China.

In the past, research on urban spatial structure under complex terrain conditions has mostly remained at the level of analyzing a specific city and a single type of terrain, the limitations of the research scope and perspective making it difficult to fully determine any general laws. In order to effectively grasp the mode of spatial expansion, development law, and evolutionary mechanism, we innovatively chose to combine dynamic and static research methods, utilizing static and dynamic maps as two mutually supportive analysis paths, and taking 71 typical cities in China as samples to provide empirical evidence. Our results indicate that there is a phenomenon of differentiation in the types of preferred spatial structure of cities under different terrains, which is realized through the urban space adapting to the topographic constraints, penetrating into the topography, and crossing the topography to break through barriers of scale. Compared with plains cities, the spatial structure of cities under complex terrain changes from compact to decentralized, the urban form tends toward complex from single, and the development rate is divided into two trends of continuous acceleration and reduced growth rate. The reason for this is that the topographical environment is the fundamental influencing factor, and social factors, such as economy and population, play an inherent driving role. National policies directly determine the flow of land and other factors, which are ultimately reflected in the spatial structure. These insights are beneficial for improving the academic research system in this field, as well as supporting the foresight of planning schemes, the direction of optimization measures, and the decision-making of urban agglomeration development.

From the perspective of transportation infrastructure upgrading, this paper discussed the motivation behind industrial firms’ pollution transfer to provincial borders. Using a panel data set of 41 cities in China's Yangtze River Delta from 2005 to 2020, this paper empirically tested the impact of intracity and intercity transportation infrastructure upgrading on pollution transfer through a two-way fixed-effects model. The results revealed the following: First, intracity transportation infrastructure upgrading forces local industrial firms to transfer pollution outward. Second, intercity transportation infrastructure upgrading accelerates pollution transfer to provincial borders. Third, in the central region, intracity transportation infrastructure upgrading does not significantly impact local pollution transfer. Intercity transportation infrastructure upgrading can aggravate border pollution, whether in the eastern or central regions. Furthermore, border pollution is more serious in the central region. The results have important practical significance for improving China's regional development planning and environmental governance system.

Urban national parks (UNPs) provide tourism services in cities worldwide. However, the factors affecting tourist distributions in UNP activity and path spaces remain uncertain. Using Web crawler technology, location big data were tracked and sampled in Donghu National Park in Wuhan, China, and 12 predictor variables were analyzed using a machine-learning method (i.e., random forest). The consistency of the big data compared to the population census and tourist observations was determined at 79.5% and 77.8%, respectively. The tourist number (p) and tourist density (p/ha) per day in the park space in Donghu National Park were 0–2,531 p and 0–198.0 p/ha, respectively. Peak tourist periods showed pressure flows of 0.3–34.5‰ between scenic areas in the park. An analytical framework was formulated for UNPs to link the urban environment, park attributes, and configurational attributes, which here explained 66.4%–72.5% of the tourist distribution in the path and activity spaces. Random forest models performed better than geographically weighted regression (GWR) or ordinary least squares (OLS) models, indicating a complex nonlinear relationship between the independent variables and tourist distribution in UNP spaces, rather than the linear relationship that has previously been found in urban parks. First, both activity and path spaces near developed urban environments or park entrances bore higher tourism pressure. Second, winding routes attracted tourists to path spaces, while water landscapes attracted tourists to both path and activity spaces. Third, tourism pressure in path spaces was determined by configurational attributes. These results are important reference points for the planning and management of UNPs.

Air pollution and carbon emissions are highly homogeneous and closely correlated. The cobenefit and spillover effects of environmental policies have garnered increasing attention in recent years. This study adopts low-carbon city pilot policies as a policy perspective to investigate the comprehensive effect of reducing air pollution and mitigating carbon emissions. By employing the difference-in-differences model, this study examines the impact of low-carbon city pilot policies on air pollution and carbon emissions across 281 Chinese cities, further analyzing the influencing mechanism and heterogeneity of policy effects. The findings of this study indicated that: (1) low-carbon city pilot policies could significantly mitigate urban carbon emissions (−0.117), while increasing air pollution (0.134), thus resulting in the spillover effect. The benchmark regression results passed a series of robustness tests. (2) The spillover effect generated through three influencing mechanisms: market resource crowd-out, industrial structure lock-in, and environmental policy substitution. (3) The local characteristics of cities, such as economic development, resource endowment, and administrative authority, would inevitably influence the implementation of low-carbon city pilot policies. Eastern cities, resource-based cities, and prefecture-level cities have yielded obvious spillover effects. Consequently, this study proposes several policy implications to coordinate urban planning to curb air pollution and carbon emissions, including exploring policy combinations, guiding resource inputs, considering local characteristics, and establishing comprehensive monitoring systems.

Abstract

This paper introduces a novel methodology for devising bike trajectory plans. In this approach, the entire trip is associated with a complex network or graph, where the nodes and edges correspond to potential trajectory segments. Utilizing the information collected from a bike-sharing system, the cost attributed to each segment is determined using the multinomial logistic regression (MLR) technique by analyzing its usage frequency and other user preferences. Consequently, segments with high usage and strong preferences entail lower costs, whereas those with limited use and weaker predilection assume higher costs. After assigning costs to all segments within the network, the subsequent step involves generating the trajectory with the lowest accumulated cost. Unlike other approaches, our method considers realistic conditions and user preferences without inconsistencies imposed by the techniques based on surveys. To validate the performance of the proposed method, a set of extensive experiments and case studies were conducted considering the urban model from downtown Guadalajara, Mexico. As a result, this approach improves the efficiency of the bike trajectory planning system by providing shorter and safer routes for both cyclists and motor vehicle drivers.

Practical Applications

The proposed bicycle trajectory planning methodology, grounded in multinomial logistic regression, unfolds various practical applications. Beyond conventional distance-centric models, our approach, driven by user-generated data from bike-sharing systems, crafts tailored routes prioritizing safety and convenience. This breakthrough optimizes trajectories and strategically targets new cyclist adoption, fostering sustainable biking cultures. Successfully validated in the urban model of Guadalajara, Mexico, our methodology equips urban planners and policymakers with a powerful tool for designing trajectories that are not only shorter but also safer. The versatility of our method extends its applicability to diverse data sets, positioning it as a forward-thinking solution in the realm of efficient and sustainable urban transportation. Practitioners can harness its potential to reshape micromobility systems, aligning them with the evolving needs of urban mobility. It is a comprehensive framework for crafting user-centric, secure, and efficient biking experiences. Cities aspiring to enhance their micromobility infrastructure could find a blueprint for urban planners in our methodology, facilitating the creation of accessible, safe, and enjoyable biking environments. In summary, our method catalyzes a transformative shift in micromobility, prompting cities to prioritize the development of not just functional but delightful biking experiences, ultimately contributing to healthier, more sustainable urban living.

Abstract

In today's increasingly complex stock era, resilient community planning for uncertainty risks is important for building resilient cities and communities and for realizing the refinement, process, and systematization of planning. Therefore, this paper proposes the concept of community planning resilience based on resilience theory and explores a framework system for evaluating the planning resilience of renewal and transformation community by taking renewal and transformation future community planning of Zhejiang as the research object. At the same time, the technical path of realizing public participation in community planning is explored through the method, mechanism, and technical platform of fuzzy group decision-making. Finally, the feasibility of the aforementioned framework and approach is experimentally explored and verified based on a typical case of renewal and renovation of future community planning. In order to make community regeneration planning more planning resilient, this paper develops a community planning group decision-making study from the perspective of community planning resilience, which provides a new research perspective for the field of community resilience and provides a reference for community planning evaluation and the construction of resilient communities.

Practical Applications

In China's advancing urbanization, major cities are grappling with diverse risks, necessitating urban planning and governance with heightened resilience to face unforeseen black swan events and foreseeable gray rhinoceros challenges. This urgency is particularly pronounced in community renewal, prompting a vital shift from rigid to resilient planning methodologies. To address this shift, this paper advocates for resilient community construction to be a focal point in both policy and practical implementation of community regeneration. A novel approach utilizing the fuzzy decision-making method is proposed to establish a comprehensive resilient community renewal decision-making technology support system. This system employs a fuzzy comprehensive evaluation method, integrating an empowerment approach to simplify the complexities of a multicriteria index system. By mitigating the risks inherent in resilience planning, our approach enhances the scientific foundation and feasibility of decision-making in community renewal. A case study on the Future Community in Zhejiang Province validates the effectiveness of our approach, providing practical insights for constructing resilient community renewal models and system technology platforms. This research contributes to the ongoing exploration of strategies and technologies capable of addressing diverse challenges in urban development, providing references in enhancing urban resilience.

Cities have emerged as the epicenters of economic activities, innovation, and cultural exchange in the era of urbanization and globalization. The concept of urban competitiveness has garnered increasing attention as a means of understanding the factors driving cities to compete locally and globally. Given cities represent the driving force of economic, social, and cultural development, there is an increasing need to identify the stages of development and establish a system for ranking and positioning cities and regions in this process. Therefore, our study attempts to help Egyptian cities enhance their competitiveness by assessing the competitiveness of 42 cities. These cities have been identified as the most competitive by the government’s Economic Development Strategy 2030 and the National Plan 2050. A total of 10 global power city index indicators for each city during 2015–2022 represent five categories: cultural interaction, economics, research and innovation, environment, and connectivity. The indicators were selected based on data availability by 11 experts. The indicators and alternatives were weighted and ranked using the fuzzy analytic hierarchy process and multi-criteria optimization and compromise solution (AHP-VIKOR) hybrid method. The geographic information system was then used to map Egyptian cities into four categories. Our findings, which are compatible with previous articles, reveal that in the case of Egyptian cities, high-government expenditure-based metropolitan cities are more competitive than small and natural resource-based peripheral cities. Egyptian cities’ most effective competitiveness indicators are the gross domestic product (GDP) and unemployment rates of 0.58 and 0.26, respectively. At the same time, the lowest effectiveness is the number of universities among the 50 best in the world as well as the number of hotel rooms, which are 0.039 and 0.044, respectively. Through the proper utilization of opportunities following the competitiveness indicators, medium-sized Egyptian cities with potential will be cities with national and even transnational competitiveness within 10 years. Our results can potentially provide beneficial insights to enhance our comprehension of Egyptian cities’ weaknesses and assist in formulating urban policies for enhancing urban singularity and competitiveness.

While extensive research has been conducted to explore factors influencing mode choices and first- or last-mile connectivity, few studies have delved into the underlying hierarchy of decision making processes. An understanding of this hierarchy, which illustrates causal relationships, is crucial for modeling travel decisions, as trip structure depends on choice behavior and vice versa. Traditional mode choice models often neglect these underlying causal relationships, necessitating the development of new models. By incorporating mediating effects of trip chaining and mode choice, alongside traditional factors, a more holistic understanding of mode choice behavior is achieved. In this study, hierarchical relationships are identified between trip chaining and mode choice in Hyderabad, India, using a structural equation modeling (SEM) method, owing to its inherent strength in handling latent causal relationships. SEM analysis provides the total effects of sociodemographic variables on mode choices and trip chain types through these causal relationships. Findings reveal that, for nonwork trips, the decision making process is simultaneous, regardless of the mode chosen. In contrast, for work trips, the decision making process is simultaneous for active and public modes, but the choice of mode precedes trip chaining for private modes. Furthermore, in this study, we learn from those who own private vehicles but use active or public transport by choice and extract the factors that had indeed motivated their choice. Confirmatory factor analysis is employed to validate the identified factors. The identified factors, coupled with the understanding of decision making hierarchy, offer valuable insights for shaping policies that can maximize the potential of active and public transport modes.

Environmental issues are often neglected in previous studies on site layout evaluation problems. To address this research gap, a comprehensive evaluation model is developed to evaluate construction site layout planning in this paper. The proposed evaluation model includes four aspects: (1) land use; (2) safety; (3) logistics; and (4) sustainability evaluations. To make the results of the evaluation more accurate, the evaluation model includes the subjective factors that need to be scored by the experts and the objective factors that could be gained from the inspections of the projects and the related materials. Then, the entropy weight method-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is chosen to solve the proposed multicriteria evaluation model. In this paper, the construction site layout planning for four different typical and practical cases, which include two commercial mixed buildings, a residential building, and a sewage treatment plant, is studied. The evaluation results proved that the proposed model is suitable to evaluate common types of construction, such as residential and commercial buildings but not specific functional types, such as the sewage treatment plant.

Abstract

Transformation of agricultural land into urban areas causes negative impacts on the livelihood of people in rural areas and affects their overall condition. To maintain or increase the opportunities for living and well-being during any disturbance resulting from a development project is called livelihood resilience. This research presents a comprehensive assessment of the effects of urban development-induced displacement and resettlement on the livelihood resilience of rural households. The sustainable livelihood approach (SLA), proposed by the Department for International Development (DFID), has been utilized to achieve these objectives. This research designed a measurement model through a systematic selection of indicators under five livelihood assets. The measurement model was verified by interviewing 348 households and applying a confirmatory factor analysis. Then, through a pairwise comparison of three scenarios of households (already displaced, economically displaced, and to-be-displaced) applying Mann–Whitney U-tests, the study evaluated the livelihood resilience of the households of Atal Nagar-Nava Raipur, Chhattisgarh, India. The findings show variability in physical assets across the scenarios, while there is no significant difference in social assets. The economic assets are significantly different for economically displaced and to-be-displaced households. Moreover, the result also shows that economically displaced households suffer the most, while the already displaced households get accustomed to the situation with time. The research reveals that rather than only providing monetary compensation, intensifying agricultural or farming activities, along with providing various supports for maintaining social and human assets, can better ensure the sustainable development of affected people and the efficacy of urban development projects. Moreover, it highlights the critical role of well-structured resettlement programs in mitigating negative impacts and bolstering livelihood resilience. With a novel methodological approach and the obtained results, this research provides valuable insights for policymakers and urban planners that can help craft urban development strategies that prioritize the welfare of the affected people from rural areas and improve their livelihood resilience.

Practical Applications

Urban development, through the transformation of agricultural land, negatively impacts the lives and livelihoods of the people in rural areas. This research endeavors to mitigate the risks by strengthening the livelihood resilience of the households in rural areas impacted by a new city/town development. This research identified four livelihood assets, namely, physical, social, economic, and human, to understand the nature of livelihood resilience. The research reveals that rather than only providing monetary compensation, intensification of agricultural or farming activities, livestock breeding, and accessibility of irrigation facilities are more crucial for people in rural areas. Moreover, the physical infrastructure, although improved after resettlement, may not ensure long-term resilience for displacees and resettlers due to the loss of regular income and employment. In addition, providing necessary information related to displacement and resettlement and various government schemes and assessing and planning by local government, institutions to enhance communication with neighbors and friends are important for making the deprived people resilient.

Abstract

The objective of this research was to examine the influence of urban configuration on the mitigation of land surface temperature (LST) and the prediction of land use and land cover change through the utilization of convolutional neural network modeling. The results indicate that the formation of different urban heat island patterns is significantly influenced by both urban geometry and land use land cover (LULC) types. However, there is no significant correlation between these factors and LST across all configuration metrics. The associations between landscape configuration and land cover types exhibit variability contingent upon the particular forest cover categories under examination. Furthermore, the application of predictive LULC mapping reveals a divergent pattern, characterized by a rise in the overall extent of vegetation but a decline in the inner context of the Shiraz metropolitan area. The projected trajectory of built-up areas indicates a continued trend of urban expansion. The unique landscape patterns are a result of the distinct characteristics of each LULC. According to recommendations, to address the issue of mean LST, it is advisable for urban landscape planning to give priority to cohesion, density, and continuity while simultaneously minimizing fragmentation, variability, and complexity.

Practical Applications

This research provides valuable insights into the following aspects for urban planners, policymakers, and practitioners to address the following. (1) Selecting appropriate landscape metrics: this study identifies suitable landscape metrics to represent and interpret different landscape structures and land use land cover changes (LULCCs) over time. (2) Understanding regional variations: this research highlights that different landscape metrics have distinct effectiveness in different regions. This knowledge helps urban planners and policymakers to tailor their strategies and interventions based on specific regional characteristics, ensuring more effective mitigation of the urban heat island effect. (3) Different correlations with configuration metrics: this study reveals that the correlations between landscape configuration and LST differ in land cover types. (4) Anticipating future changes: this research utilizes machine learning models to predict future LULCC and landscape metrics. This information is valuable for urban planners and policymakers in anticipating and preparing for future urban expansion and changes in vegetation areas. It enables them to proactively design and implement strategies to manage the surface urban heat island effect. Urban planners and policymakers can utilize these insights to develop comprehensive strategies that integrate land-use design, landscape configuration, and urban form to mitigate the negative impacts of urbanization.

Doha, the capital city of Qatar, has experienced remarkable urban growth over the last two decades. This raises concerns regarding the city’s fulfillment of compactness, complexity, and connectivity. This paper considers transit-oriented development (TOD) as a potential tool to attain a sustainable and diverse urban landscape in a situated context. Qualitative research methods, which include observations and mapping, are employed to gain a deeper understanding of the physical aspects of a situated context in the neighborhood of Al-Slata, Doha. Specifically, this paper aims to investigate the implementation of TOD in metro station precincts within Al-Slata based on five design aspects: (1) walkability; (2) balance of ground use; (3) mixed-use spaces; (4) intermodality and transportation hubs; and (5) a public transportation network. The findings include a lack of complexity and connectivity between urban activities and spaces adjacent to the metro station. In addition, these findings demonstrate the potential of metro stations to preserve the cultural heritage and social identity in a rapidly developing city like Doha. The recommendations include a layout design proposal to increase connectivity and complexity within the situated context and suggestions on how transit nodes and metro stations could become active hubs within the city.

Abstract

In recent years, small-area population prediction methods have been widely applied in urban and regional planning. This study aims to empirically compare two small-area population forecasting methods and explains how to choose prediction results through a case study. This study utilizes the geographically weighted regression (GWR) model and the cohort change rate (CCR) method proposed by Inoue to forecast Wuhan’s population. In terms of data requirements and the complexity of the prediction process, GWR necessitates considering more drivers of population change and is more effective for population prediction at the county administrative unit or on smaller scales. The model requires substantial input data and involves integrating statistical and geospatial data. Unlike GWR, the CCR method requires population data for only two statistical years, necessitating a smoothing of population data for each area. Consequently, it is generally unsuitable for predicting populations of small geoadministrative units. With regard to forecasting results, the CCR results suggest that Wuhan’s future population will continue to experience relatively rapid growth. In contrast, the GWR results indicate that Wuhan’s future population will be more stable. Given China’s demographic shifts, urbanization trends, and Wuhan’s recent population changes, this study concludes that GWR produces results more consistent with reality. The value of this study lies in using a case study to provide researchers and planning practitioners with a better understanding of GWR and CCR and how to choose prediction results for planning.

Practical Applications

The study’s findings demonstrate that the cohort change rate (CCR) method proposed by Inoue overestimates the actual population, whereas the geographically weighted regression (GWR) method underestimates it. These population prediction methods may produce different results in other cases due to variations in the situations, as observed in Wuhan, China. In the actual planning project research process, multiple prediction methods are often employed to obtain interval prediction results, the median of which is then used to approximate the actual result. To obtain age-specific population prediction results, only the CCR method may be used for planning projects or research. However, the choice of method may be constrained by data availability, requiring results based on the researcher’s specific circumstances.

Abstract

Urban parks in Vietnam are undergoing expansion plans, yet the actual area is dwindling, attributed to limited ecosystem services and inadequate public engagement. This study addressed the dual challenge of shrinking green spaces and the need for enhanced ecosystem services in urban areas. We aimed to devise strategies to bolster ecosystem service development through a comprehensive survey of park users and an analysis of the impact of green areas on ecosystem service quality. Specifically, we surveyed 400 residents to gauge perceptions, attitudes, and insights regarding park ecosystem services. Additionally, we assessed the importance of urban green spaces through various indicators $(\mathrm{pH},\mathrm{DO},\mathrm{TSS},\mathrm{COD},{\mathrm{N}\text{–}\mathrm{NH}}_4^{+},{\mathrm{N}\text{–}\mathrm{NO}}_2^{-},{\mathrm{N}\text{–}\mathrm{NO}}_3^{-},{\mathrm{P}\text{–}\mathrm{PO}}_4^{3-})$ in surface runoff samples, both with and without vegetation, during five rainfall events. The findings reveal a limited understanding of park ecosystem services among the populace, reflected in their minimal willingness to pay for such services. Moreover, the study uncovers significant differences in the impacts of parks on sustainable urban drainage, as evidenced by contrasting qualities of rainwater samples processed through green areas versus typical stormwater runoff. These results underscore the need for targeted interventions to raise awareness and improve ecosystem services in urban parks, which is pivotal for sustainable urban development. This case study from Vietnam contributes both theoretically and practically by highlighting the crucial role of public awareness and engagement in enhancing ecosystem services in urban landscapes.

Practical Applications

Our study illuminates the crucial role of nature-based solutions in enhancing ecosystem services within urban environments, as exemplified by Gia Dinh and Tao Dan Parks in Ho Chi Minh City, Vietnam. This research is particularly valuable for urban developers, park management, and city planners because it underscores the potential of urban parks to contribute significantly to environmental sustainability and public well-being. We found that the public’s awareness and valuation of the parks’ ecosystem services are key to their willingness to support and fund park improvements. Therefore, educational programs aimed at increasing understanding of the benefits provided by these green spaces could lead to greater community involvement and investment in their maintenance and development. For policymakers, our findings suggest that investing in the ecological aspects of urban parks can pay off in terms of both enhanced environmental quality and increased public usage and enjoyment. Additionally, the implementation of sustainable drainage systems within these parks not only mitigates urban flooding but also improves the quality of urban runoff, presenting a compelling case for integrating similar nature-based solutions in urban planning initiatives. By presenting clear, real-world examples from Gia Dinh and Tao Dan Parks, our study provides a framework for other cities looking to link ecosystem services with urban development. The insights gained here can guide the transformation of urban green spaces into multifunctional areas that support biodiversity, provide recreational opportunities, and serve as cornerstones for sustainable city living.

In metropolitan areas, rising house prices make it more difficult for low- and middle-income people to access affordable housing. However, the availability of affordable rental housing in metropolitan areas serves the survival and social sustainability of all social groups in urban areas. Despite the critical importance of rental housing affordability at the metropolitan level, studies on this issue, especially spatial studies, are limited. This article spatially analyzes housing affordability for low- and middle-income households in Istanbul, a city experiencing a neoliberal housing policy. The methodology of the study is based on an analysis of rental housing affordability in the metropolitan area of Istanbul by taking into account the polycentric structure of Istanbul, the central grading (center, subcenters, and periphery), and regular and irregular housing subregions. The findings of the article demonstrate that low- and middle-income households in Istanbul have no access to affordable rental housing in the city center and limited access to the subcenters. Furthermore, low- and middle-income households have access mainly to irregular housing areas within the city. The findings imply that without social policies, they will be excluded from central or regular housing areas. This points to the critical role of social policies in neoliberal housing markets.

Transit as an alternative means of travel allows travelers to access a wide range of activities and services. In addition to focusing on how many job opportunities and other basic urban services such as parks and healthcare can be accessed by transit, more attention should be paid to how many transit services can be obtained and how easy it is to access them. It should be noted that accessibility by transit and accessibility to transit are not the same thing, and most existing studies tend to focus on the former while ignoring the measurement of the latter. However, accessibility to transit is an important concept that can provide a framework for understanding and explaining the availability of transit services. In the literature, transit is more often used as a tool for accessing activities and opportunities to analyze the basic services such as healthcare resources and job opportunities that can be accessed, which not only ignores the transit service provided by the means of transit as a supplying facility, but also ignores the diversity of facilities in the integrated public transportation system. With this in mind, this paper introduces the entropy index into the adjusted Gaussian two-step floating catchment area (2SFCA) method to measure accessibility to transit to capture how the overall accessibility changes when considering different transit facilities. From the spatial distribution of accessibility, the areas with high accessibility score are distributed in the six core administrative districts of Beijing, accounting for 99.3% of the grids with high accessibility scores. When considering facility diversity, 46.7% of the grids within the core administrative districts experience an increase in their accessibility rank, and there is an increase in the number of grids with high accessibility. The research results indicate that considering facility diversity enhances the accessibility level of grids, elucidates the diversity differences in each area, and provides valuable information for the location selection of transit facilities and urban planning. The applicability of the proposed method to Beijing illustrates that it can provide valuable insights for the measurement of accessibility, which can help planners obtain more effective evaluation results.

Abstract

Urban vitality is a core feature of sustainable cities and neighborhoods. Acknowledging the significant role of the spatial and physical attributes of built urban landscapes in influencing urban vitality, scholars and planners in the field of urban studies have meticulously examined the relationship between urban morphology and variations in urban vitality. While most previous studies have primarily focused on a narrow range of factors when analyzing urban form, often neglecting its multifaceted nature, this study utilizes urban morphometrics using Python's Momepy library to offer a comprehensive typology. It integrates diverse urban components from individual buildings and streets to entire neighborhoods into a unified, holistic framework, providing a more integrated understanding of urban form's influence on urban vitality. Our spatial econometric models identified higher building floor areas, taller and narrower streetside buildings, diversely aged buildings, and higher building coverings on lots as favorable urban form settings for urban vitality. Measuring urban morphology with advanced methods and identifying their relationship to urban vitality provides insightful implications for urban planners and designers for creating vibrant cities and neighborhoods.

Practical Applications

This study utilizes advanced methods to assess the design and layout of cities and neighborhoods and analyzes their effects on urban vitality. The Momepy Python package is used in this study to capture urban form in terms of size, density, layout, diversity, and connectedness. This study measures how diverse urban morphologies affect the variation of urban vitality captured by mobile phone data. This study introduces an integrated approach that identifies spatial relationships between buildings and street networks into a comprehensive framework. This holistic approach can suggest effective strategies for decision-making by urban planners and policymakers to create livable and sustainable cities and neighborhoods. Moreover, this study reveals how the effects of the urban morphology on urban vitality vary depending on the time of day and day of the week. The core findings suggest that urban planners and designers should consider spatial configurations of buildings and streets as well as residents’ behavior over time.

Climate change is one of the main variables affecting the landscape design of urban open spaces. However, it is currently the case that climate change is not being considered as a factor in the design of every urban open space. This is leading to a decrease in the benefits that these areas, which are important for increasing the resilience capacity of cities, could provide. In addition, this approach is leading to a prolongation of the time required for the designs to provide a positive impact when they are ultimately put into practice, which has a knock-on effect on resetting our carbon footprint. This study covers the evaluation of spatial solutions for landscape designs created through spatial analyses using a case study and applying climate change adaptation strategies and a climate-positive design approach. The study was aimed at providing an example of how spatial solutions can be produced using climate change adaptation strategies in the redesigning of urban open green areas. The study also aimed to increase the ecosystem services and reduce the carbon footprint of the designs by integrating climate change adaptation strategies into the design process. In this context, the requirements identified through the spatial analyses were transformed into spatial solutions using climate change adaptation strategies, with 21 climate change adaptation parameters divided into six categories. These parameters were transformed into 47 spatial solutions. These spatial solutions were analyzed within the framework of land use, vegetation, water, and ecosystem services. Three-layered (trees, shrubs, perennials) planting decisions were made. Using a climate-positive design approach, it was found that the design created through spatial analysis would balance the carbon footprint only after 20 years, and that the design would produce 598,307 kg of CO₂ after 50 years. This suggests that such designs should be evaluated within the scope of climate adaptation strategies as soon as possible. These findings should increase the level of awareness of the benefits that come from evaluating the spatial needs of cities in the design process in the context of climate change.

Accessibility is a vital measure of convenience for seniors in accessing urban park green spaces (UPGS). However, current research on accessibility for seniors faces challenges in terms of the reliability of results, and existing categorization methods lack an exploration of accessibility equity. Consequently, there are limited references for city managers to formulate urban planning programs. In this context, this study focuses on Ningbo City, China, and establishes a framework connecting accessibility research and urban planning practices by (1) utilizing the smallest unit in urban planning and zoning regulations as the study's basis; (2) enhancing the reliability of accessibility results through improved input data for the two-step floating catchment area (2SFCA); and (3) exploring accessibility equity by constructing an Accessibility Difference Index (ADI) and employing Hotspot Analysis and Pearson's correlation coefficient. The study identified blocks as the smallest unit for accessibility analysis by extracting centerlines from major urban roads. Additionally, the study controlled park division shapes using the Slenderness Ratio and incorporated Baidu population data and path planning time, resulting in more precise 2SFCA results. Consequently, the findings indicated inadequate accessibility in areas where seniors gathered and in the periphery of the study area. Public transportation can significantly improve accessibility equity. The results of the correlation analyses at 15 and 30 min supported this finding. Additionally, the results from the ADI revealed a left-skewed distribution in the assessment data on accessibility equity at 15, 30, and 45-min intervals. Therefore, the accessibility equity for seniors in Ningbo was insufficient. Finally, this paper proposes solutions based on the 2SFCA model, including enhancing the areas and quality of UPGS and optimizing the distribution of seniors. This study can inform urban planning by enhancing transport planning and improving minimum standards for UPGS in zoning regulations. This framework assesses the degree of equity in specific blocks and can guide equity planning in urban areas.

This paper studied the spatial pattern of supergentrification in the core area of Shanghai. The area is divided into 23 subdistricts based on the standard pattern of subdistrict division provided by CREIS (China Real Estate Index System) and then the 23 subdistricts are taken as objects for analysis. By establishing the evaluation index system of supergentrification level, the integrated analysis method entropy weight method and exploratory spatial data analysis is used to explore the general characteristics of the spatial pattern, spatial agglomeration characteristics, and spatial agglomeration hotspots of supergentrification in the core area of Shanghai. The research results of the spatial pattern reveal that the level of supergentrification in the core area of Shanghai is high in Puxi and low in Pudong. The Puxi district, represented by the People’s Square subdistrict, West Nanjing Road subdistrict, and Hengshan Road subdistrict, has a higher level of supergentrification, while the Pudong district, represented by the Tangqiao subdistrict, Yangjing subdistrict, and Huamu subdistrict, has a lower level of supergentrification. The results of spatial autocorrelation analysis reveal that supergentrification in the core area of Shanghai presents obvious spatial agglomeration characteristics on the subdistrict scale and that the significantly high-high subdistricts are mainly distributed in the core area of Puxi.

The public–private partnership (PPP) environment in Asia is complex due to the different levels of development. Thus, investigating critical success factors (CSFs) of PPP projects plays an important role for both the public and private sectors to ensure sustainable development. The purpose of this study is: (1) to seek and evaluate CSFs of PPP infrastructure projects in Vietnam; and (2) to compare top CSFs among several countries in Asia. Data were collected through a questionnaire survey with 36 obtained responses. Collected data were analyzed using the mean score technique, factor analysis, and fuzzy synthetic evaluation (FSE) method. Finally, a comparison among countries in Asia was carried out. Seventeen CSFs were identified and five main groupings were grouped, including favorable investment environment, good partnership management, sound financial package, effective contract management, and ability of the private sector. The comparative result has shown that PPP investment in middle-income countries is more complicated than the high-income countries. This finding not only helps the government and investors to be more understanding of CSFs for implementing PPP procurement in Vietnam, but also offers the overall picture of the PPP market in the Asia region. In addition, it provides practitioners with an evaluation framework regarding CSFs in decision-making for PPP implementation.

Abstract

To boost the high-quality integrated development in late-developing regions, an examination of the temporal and spatial patterns of urban growth and the primary drivers of urbanization in these regions is crucial. An exemplar case study of Anhui Province is presented in this research. The extraction of urban built-up areas in Anhui Province was conducted using nighttime light (NTL) data and urban statistical information. The study investigated the dynamic transformations and evolutionary features of urban expansion by utilizing measurement indexes for urban growth and center of gravity transfers. By employing gray relational analysis on economic, demographic, and other statistical data, the key influencers behind urban expansion in Anhui Province were scrutinized. The results revealed a steady annual increase in the urban built-up area of Anhui Province from 1996 to 2020. Furthermore, the shift of the urban built-up area’s center of gravity in Anhui Province transitioned toward the east–south direction between 1996 and 2008, but gradually shifted toward the west–north direction thereafter. These alterations were mainly driven by factors such as urbanization rate. This study is expected to help decision makers take appropriate countermeasures to achieve high-quality regional development.

Practical Applications

Understanding the spatiotemporal dynamics and influencers of urban expansion is vital for fostering sustainable urban development, ecological conservation, and enhancing residents’ quality of life. The dynamics and influencers of urban expansion vary across cities and different stages of urban development. This study aims to elucidate the dynamics of urban expansion in Anhui Province and identify the primary driving factors to assist urban policymakers and planners in making informed decisions regarding urban planning, land use, and ecological and environmental protection policies.

The concept of social infrastructure and its role in building disaster resilience has garnered significant attention in recent years. Defined as physical spaces that foster social connections and vibrant communities, social infrastructure has been recognized as a crucial element in providing support and resources during disasters. The coronavirus disease 2019 pandemic has further emphasized the importance of enhancing social infrastructure. However, divergent perspectives exist regarding the relationship between social infrastructure and socioeconomic factors in terms of distribution. Some studies suggest that the disproportionate distribution of social infrastructure may disadvantage certain racial and socioeconomic groups. Conversely, other research highlights instances where marginalized communities with robust social infrastructure exhibit resilience despite facing social and economic challenges. This discrepancy underscores the need for further investigation to reconcile these differing descriptions. Addressing this gap, this study aims to examine the relationship between social infrastructure, socioeconomic factors, and environmental justice. Specifically, the research question guiding this study is: Is the distribution of social infrastructure in a city related to specific racial or class factors from an environmental justice perspective? Utilizing the ordinary least squares regression, this study reveals that communities with a higher proportion of the non-White population have a greater number of social infrastructures, challenging expectations based on the environmental justice literature.

Urban thermal environment (UTE) deterioration seriously affects the production, life, and health of urban residents. Therefore, identifying the spatial and temporal evolution of the urban environment and exploring the main factors that affect the UTE are increasingly urgent and important. This study uses multisource spatial data to analyze the changes in surface temperature and its spatial and temporal differentiation patterns of Hangzhou, China in 2000, 2010, and 2021. Then, factors that are intimately connected to the alterations in the UTE are identified. Based on this, the contribution and impact of the UTE are calculated. The findings indicate that from 2000 to 2021, Hangzhou’s urban heat island area has been continuously expanding, with an increase of 622.74 km². In 2021, the maximum surface temperature difference reached 6.2°C, where the heat island area in the Xiaoshan and Yuhang Districts exhibited the largest increase. Hangzhou’s urban heat island space showed a scattering distribution in the northwest–southeast direction. High-temperature areas are concentrated in regions that are characterized by dense industrial and commercial distribution, which display local concentration and overall dispersion. Low-temperature areas are concentrated around vegetation-covered regions and bodies of water. The natural and social factors contribute to the changes in surface temperature within the study area. The contribution of social factors on surface temperature surpasses that of natural factors. The leading factors are landscape patterns, the natural environment, and construction activities. The combined effects of various factors increase the surface temperature by 0.965°C for each unit increase in the combined factors within the study area.

Historic cities serve as a crucial historical–cultural cornerstone within urban settings, and fostering its sustainable vitality has emerged as a focal point in urban research. Multisource data have advanced large-scale vitality research. Despite keen interest in the nexus between urban vitality and the built environment, the spatiotemporal intricacies influencing street vitality in smaller urban settings like ancient city are underexplored. To fill this gap, we use Chaozhou ancient cities as a case study to examine the relationship between street vitality and the built environment. Leveraging Jacobs’ urban vitality theory and the 5D system, this study develops initial tools to understand ancient city vitality, focusing on density, diversity, accessibility, and the streets’ spatial characteristics. Subsequently, employing a geographically and temporally weighted regression model, we delve into the spatiotemporal heterogeneity of vitality and the built environment. The research findings indicate that: (1) the association between street vitality and the built environment in historic cities exhibits dynamic variations over time and space. The impact of different built environment indicators on the vitality of the streets varies in intensity across different periods and areas. (2) Density and diversity play contrasting multifaceted and limited roles in enhancing the vitality of ancient cities. Accessibility's role in traffic attraction and navigability significantly sways vitality. The temporal nonstationary of street space characteristics is particularly pronounced. (3) The density of aged buildings, diversity of building ages, sky view ratio, and green view ratio generally show a negative correlation with the vitality of ancient cities across time and space.

Conducting an assessment of ecosystem service values and examining the influence of changes in land utilization on these values in Chengdu City help to deepen our comprehension of the ecological and environmental impacts of such changes. This, in turn, provides valuable insights into the construction of an ecological civilization and the sustainable utilization of land resources in Chengdu City. Based on land-use data from 2005 to 2020, this paper employs a dynamic model of land-use change, the land-use structure change index method, and an ecosystem service value measurement model to analyze the impact of land-use change on ecosystem service value in Chengdu City. The results showed that (1) the area of construction land in Chengdu City increased and those of cultivated land and unused land decreased; (2) from 2005 to 2014, the ecosystem service value in Chengdu City witnessed a rise of 1.559 billion yuan, while from 2014 to 2020, it experienced a decline of 947.77 million yuan; and (3) the sensitivity index of the ecosystem value shows that forest land contributes the most to the total value of ecosystem services. This paper comprehensively analyzes the impact of land-use change in Chengdu City from 2005 to 2020 on the ecosystem service value. It offers a reference foundation for advancing the efficient allocation of land resources in Chengdu City and nurturing the balanced and sustainable development of the economy and ecology.