Journal of Urban Planning and Development

The successful development of bicycle-sharing systems (BSSs) is influenced by the socioeconomic characteristics and geographic attributes of metropolitan areas. Trip generation and attraction volumes, which represent the actual flows of resident activity in a specific area, may influence BSS ridership, particularly for travelers using a BSS for first- or last-mile services. However, most studies have used population and other socioeconomic data to investigate BSS ridership without considering trip attributes. Population-related attributes may influence BSS ridership, but they cannot account for the spatial distributions of vehicular or passenger trips between specific origin–destination pairs. In contrast to past studies, this study collected 9 years of BSS rental data and related socioeconomic characteristics of the CityBike system in Kaohsiung City, Taiwan, including residents’ trip attributes. Panel data were analyzed using autoregressive with exogenous variable models. The results indicated that trip attributes that are more appropriate than population data are in BSS ridership prediction. Accurate predictions of BSS ridership volumes over time enable the allocation of limited resources to establish new stations or infrastructures for sustainable BSS development.

The internal characteristics of dwellings and their level of accessibility to basic services have traditionally been the main variables in establishing their level of quality; however, in large cities, problems associated with traffic and environmental quality are becoming increasingly important because of their impact on people’s quality of life. This paper aims to build a well-being index for dwellings in the central districts of Madrid that can help the urban managers to take decisions increasing citizens’ well-being. For this purpose, we have developed an indicator using the P2-distance method on a database of variables related to environmental quality, and on the other hand, variables related to the characteristics of the dwelling. We find that, in general, the distance to services variables correlates negatively with the well-being index as we expected. On the other side, a positive and unexpected correlation is observed between the well-being index and the variables of pollution and noise, which indicates that these variables are usually higher in the points best located with respect to basic services, places that we could consider as service centers of the central almond. Therefore, the index allows urban planners to test complex solutions in presence of the trade-offs between elements that affect negatively the well-being such as noise or pollution, versus positive variables such as higher density of services availability.

Smart mobility and transit-oriented development (TOD) are closely intertwined with smart urban living in developing a smart city. A number of initiatives were taken through smart mobility or TOD projects to ensure smart urban living over time. However, there is a lack of consistent approach to combining smart mobility and TOD for smart urban living. The connection between TOD and smart mobility performance indicators remains unexplored for smart urban living. Therefore, the study aim was to develop a conceptual framework for eco-friendly smart urban living with the integration of TOD and smart mobility performance indicators. A compendious literature search was conducted to identify the smart mobility and TOD performance indicators. A Delphi questionnaire was also used to rank the indicators by experts. The eco-friendly smart urban living framework was developed with the integration of smart mobility and TOD performance indicators. This study found eight TOD performance indicators, namely utilization of transit nodes, user-friendliness of a transit system, parking at the station, walkability and cyclability, land-use diversity, access and accessibility, density, and economic development, that needed to be considered to design a city for smart living. Six smart mobility indicators, namely, location efficiency, reliable mobility, health and safety, environmental stewardship, social equity, and robust economy, were also identified and included in the smart urban living framework due to their importance to ensure smart living environments. Future research should test this framework using local data in different geographical settings.

The remains of industrial culture have been in place for hundreds of years and have gradually become the object of research for heritage protection and renewal. To assist in value assessment and planning for the reuse of urban industrial heritage, we built a concept model for value evaluation and renewal suitability evaluation based on the characteristics of the industrial heritage and by consulting experts. In addition, according to the characteristics of the evaluation index, we adopted a calculation of mixed qualitative and quantitative criteria and reasonably allocated weights. Thirty industrial heritage sites in the urban area of Chengdu, China, were selected as case studies; the results showed that there were clear differences in the value and renewal suitability of the industrial heritage sites. This study determined an evaluation model for the protection and reuse of industrial heritage and laid the foundations for future practical work. In addition, the Chengdu Industrial Heritage Database was constructed, to provide guidance on industrial heritage planning for decision makers.

There is diversity and complexity in the spatial analysis that encompasses the analytical perspectives of social segregation in new communities. This research aims to explore the correlations that could predict potentials for walkable environments as a contributor to minimizing social segregation in new communities. The research addresses the spatial configuration analysis of street networks, using space syntax as well as the ground floor use considering the spatiotemporal dimension. The study was conducted in Sheikh Zayed City, a new community in the Greater Cairo Region, Egypt. Various theories and methods use space syntax in practice and empirical research to analyze the spatial relationships in the physical built environment. This research explores the predictive power of space syntax and introduces mixed methods to better investigate the significant relationships between walking behavior and street spatial analysis. The syntactic measures of the streets (global and local integration, choice, and connectivity) are articulated, and ground floor use [using geographic information system (GIS)] is overlaid. Walking behavior is recorded at different times of the week, incorporating the purpose of pedestrian trips, and added in the correlational analysis. A principal component analysis (PCA) followed by multiple regression analysis reveals the explanatory results of relations between the spatial variables for predictable actions. The research findings deduced that ground floor use distribution could predict walking behavior and trip purposes at different times of the week while street syntactic measures vary in their explanatory power on walking behavior, especially when considering the time of the day dimension. Thus, the study concludes that space syntax as an analytic tool should be complemented by other methods that address a wider spectrum of variables pertaining to spatial street properties. The proposed combination of methods can better guide street design, create more walkable communities, and achieve social integration.

Sustainable and smart public spaces play a key role in enhancing cities’ potential to address current urban challenges and evaluating and implementing such plans for public spaces is a complex process. A performance model was developed to assist stakeholders in decision making, which integrates this evaluation process. Following an integrated, adaptive approach, the proposed model is based on the multisectoral, demand–supply estimation of the urban comprehensive carrying capacity and the urban smartness of alternative development plans. A comparative evaluation of the new and existing models in a case study area indicated that the holistic methodological framework of the performance model and indicators could better support identification of the best development plan for implementation. Results indicated that the performance model could assist decision makers in addressing the specific needs of individual public spaces and the common urban need for sustainability and smartness.

The importance of analyzing travel mode choice to understand travel behavior in urban areas is crucial in the formulation of mobility policies, especially considering the growing concern to reduce the use of private transport modes in favor of sustainable ones. Although multinomial logit models have been widely used in travel behavior research, machine learning models are becoming an interesting alternative to perform this task, in which tree-based ensemble models, such as random forest and gradient boosting models, have demonstrated superiority in accomplishing this goal, although they both have not been compared using household survey data. This paper compares different logit and machine learning models, with a specific emphasis on gradient boosting, random forest, and multinomial logit models to predict travel mode choice and to identify the determinants in travel behavior in an urban area for three transport modes (public transport, private transport, and walking/bike), using household survey data. Although the methodology is defined following the case and features of the metropolitan area of the Aburrá Valley—Colombia (MAAV), it can be applied to any urban area. The results show that an optimized gradient boosting model is able to predict travel mode choice in an urban area using household survey data, outperforming the other compared models. In addition, travel time, parking type at the destination, the number of motorized vehicles in the household (cars and motorbikes), age, and gender are features that explain the travel mode choice in the MAAV. The optimized gradient boosting model presented in this paper can be employed as a policy tool to study and analyze strategies to promote the reduction of the use of private transport modes in the MAAV and increase the use of more sustainable transport modes.

Trans-sectoral urban planning is a crucial element of sustainable urban development using local synergies and closing regional material, energy, and finance flows. Two trans-sectoral scenarios for Da Nang (Vietnam) will be analyzed linking the waste sector to other urban sectors: (1) agriculture and (2) energy and agriculture. The scenarios will be analyzed and compared with their reference scenarios in a regional impact assessment (RIA) with respect to their economic, social, and ecological impacts. Results show that both trans-sectoral scenarios contribute to regional independence and self-supply, to the closure of regional material and energy cycles, to improvements in working and living environment, and to soil quality and climate protection. They also revealed that regional value chains are especially activated and the economic value that stays within the region can be raised significantly from EUR 1.4 to 2.8 million/a in trans-sectoral Scenario 1 and from EUR 1.7 to 4.8 million/a in Scenario 2. The RIA results provide a holistic fundament for sustainable urban decision making and supports the local implementation of the sustainable development goals.

The purpose of this study is to determine the impact of data-driven urban management and its impact on upgradation of slums in Islamabad in the mediation of privacy and security concerns. The study was quantitative in nature, and the data were gathered from 301 personnel who were responsible for the planning of urban management. The structural equation modeling technique was utilized for analyzing the responses determining the mediation effect. It was found that privacy and security concerns partially mediate relationship among framing the future and upgradation of slums and evidence-based decisions and upgradation of slums. However, full mediation of privacy and security concerns the relationship of real-time urban management and upgradation of slums. The study focused on the upgradation of slums in Islamabad only, which restricts the results of this to one city. Moreover, the study has used quantitative design, which only provided numerical evidence of the impact rather than cause and detail of the issues

Designing urban residential landscapes in arid regions requires careful consideration of water use and costs. Landscape performance assessment at the residential scale has historically been limited to esthetic preferences. Landscapes provide many more services. Quantifying these services allows a comprehensive understanding of the costs and benefits of landscapes. Landscape architecture decisions impact urban planning goals like water-use efficiency, yet the links between planning and planting criteria are rarely evaluated in design decisions. To address these deficiencies, this paper presents a Landscape Decision Assessment Tool (LDAT), a multicriteria, geometrically explicit, multiresolution modeling framework. Its use is targeted to urban planning and water engineering departments in arid regions as well as design practitioners. It aims to improve the multicriteria design of villa landscapes to explicitly include beauty, privacy, shade, views, and water conservation. Results from a typical parcel-level case study in the United Arab Emirates identify substantial opportunities to improve water efficiency without compromising residential design criteria by adjusting landscape configurations. Multiple configurations perform nearly equally well indicating a range of choices for households to choose from based on the household weighting of criteria.

The establishment of the Xiong’an New Area has been an important decision for China to remove noncapital functions. This paper will use the Xiong’an New Area policy as a quasi-natural experiment and will use the synthetic control and difference-in-difference (DID) methods to study the influence of the establishment of the Xiong’an New Area on the quantity and prices in the new and secondhand housing markets in Beijing. This paper found that after the Xiong’an New Area was established, the overall quantity of new houses in Beijing decreased and the quantity of secondhand houses first increased and then decreased. The price of new housing increased steadily and the price of secondhand housing had a downward trend. Overall, the Xiong’an New Area policy had a significant influence on the quantity of new and secondhand housing and the prices of the new and secondhand housing index in Beijing. Based on the empirical results, to promote the rational development of Beijing’s real estate market through the Xiong’an New Area policy, and to achieve the national policy goal of “no speculation on housing” and “housing for housing the planning and construction in the area need to be strengthened.

Research on public space has long been a primary focus in urban studies. Most previous studies have measured public space from the macroscale perspective, such as the distance to the city center, and therefore cannot specify the social significance and economic benefits related to its quality or details. Hence, we fill this gap by evaluating the impact of quality and the presence of specific public space elements on housing prices after dividing public space into two parts: public space surrounding the gated community (PSSG) and public space inside the gated community (PSIG). We measure the visible and touchable features of PSSG and PSIG and estimate the effects and the monetization value of PSSG and PSIG on housing prices. Our empirical analyses focused on the area within the Beijing 5th Ring Road and revealed the following: For the PSSG, wider streets, higher buildings along the streets, higher street greenery levels, higher proportions of street wall continuity, and lower street spatial disorder can contribute to higher housing prices. For PSIG, the presence of most gated community facilities can raise housing prices. We infer that the economic value of PSSG and PSIG, including housing prices will increase by 546 yuan/m² as the gated community gains a sport field.

Cities have been growing rapidly over the past 30 years. This urban growth requires proper planning for sustainable development. Considering the possible future urban planning problems to Sialkot city, Pakistan, it is taken as a study area because of its significance as an industrial and economically emerging city. This study applied Remote Sensing (RS) and Geographical Information Systems (GISs) to recognize, compute, analyze, and plot urban sprawl susceptibility. A multicriteria evaluation method was used, employing factors such as land cover, Digital Elevation Model (DEM), population density, and road proximity as inputs. The weights of all input factors were estimated according to urban sprawl dynamics between the years 1990, 2000, 2010, and 2020. The Analytical Hierarchy Process (AHP) was used for Sialkot city to assess the susceptibility of urban sprawl and pattern. The outcomes showed that 118 km² (45%) of the area was not susceptible, 62 km² (24%) was slightly susceptible, while 42 km² (16%) was restrained susceptible, and 38 km² (15%) was extremely susceptible to urban sprawl. We found a linear scattered and leapfrog sprawl pattern in the study area. The substantial variations in the field of study for 30 years showed threats for fertile farming land and other natural resources, consequently threatening the production and security of food. The findings of this research would aid the government in monitoring and estimating susceptible sprawl to prevent agricultural land and ecology.

In the era of the knowledge economy, the polycentricism and polycentricity of urban regions holds important implications for knowledge production, collaboration, and innovation. Using data from Chinese and English journal repositories on urban paper publications and intercity paper collaborations, this paper measures morphological and functional knowledge polycentricities in 19 urban agglomerations in China in 2014–2016. We find that, first, the morphological polycentricity of urban agglomeration is on the whole higher than the functional polycentricity of agglomerations, but that no obvious correlation exists between these two types of polycentricities. Most agglomerations, further, are found to be characterized by high morphological and low functional polycentricities, while the dual low morphological and functional polycentric types are rarely seen, indicating that homogeneous knowledge production characteristics are not necessarily accompanied by high levels of knowledge cooperation. Second, urban agglomerations that are both highly morphologically and functionally polycentric (such as most urban agglomerations along China’s eastern coast) tend to be characterized by a higher overall level of knowledge innovation. The development of functional polycentricity is, therefore, closely related to the knowledge stock and innovation foundations of an urban agglomeration. Third, the typological basis for the development of functional knowledge polycentricity is predominantly the level of economic development of a given agglomeration, which also steers the potential impact of (synergistic) innovation policies on knowledge polycentricity. The study argues that, while it is difficult to establish a relationship between morphological knowledge polycentric and the level of innovation in urban agglomerations, functional polycentricity is an important condition for urban agglomerations to function as innovation incubators.

Optimizing the spatial distribution of public service facilities (PSF) is important to promote the quality of life and the equitable distribution of public services. The spatial distribution of PSF is not only related to public service capability but also related to individual preference, so it is essential to integrate residents’ preferences and the service capability of PSF for PSF evaluation. This study proposes a new evaluation model for the spatial distribution of PSF by integrating four indicators. We perceive subjective preferences from Sina Weibo data to construct the online popularity indicator and construct three indicators including service area ratio, service population ratio, and service coordination to characterize the service capability of PSF by using land cover data, nighttime light data, road network data, and demographic data. We take Wuhan for example and show the veracity of results and the model’s superiority through field investigation and comparative analysis. The results show that the model has high accuracy and timeliness, and it is free from the influence of administrative boundaries. This study is expected to provide the auxiliary basis of PSF evaluation and decision-making for urban planning and relative departments of management.

In this paper, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers’ clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles’ abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%–15% of all moving vehicles in the Dallas–Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle’s actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials—a common visualization of arterial signal performance for transportation planning and operations.

One of the most common activities among tourists is walking, providing visitors with a range of different experiences of the places they visit. These experiences can vary, depending on the time of the year, weather, and, most importantly, the motivations of the individual. Much attention has gone into understanding the ways in which built and natural environments create opportunities for people to walk. However, the motivations and walking behaviors of tourists can differ from those of local residents. This paper explores walkability by adopting a systematic review of literature on different databases. The descriptive theme is focused on the general importance of walkability and four major themes on tourist walking studies are identified. The findings from the studies and their limitations point toward a need for further study, with a focus on local residents and tourists in order to understand whether there are differences and to understand the attributes that may affect their walking behaviors and experiences.

Developing countries face greater urbanization challenges than developed countries. The majority of the challenges that developing countries face are due to demographic changes (DCs). The DCs, particularly in disparities, have a major influence on development processes and inclusive and balanced growth. Due to the lack of a regular monitoring mechanism for DCs, several tools and methods were developed to extrapolate the data for DCs. Most of them rely on census data and do not take into consideration the dynamic aspect of migration that plays a major role in DC. This study develops a hybrid approach to model the magnitude of spatial and temporal changes in DCs. The rational choice theory was considered to understand the reasons for the movement of people. To model DCs, some of the macro factors that play an important role were identified. A hybrid approach that integrates the analytical hierarchy process–entropy (AHP) method was used to evaluate criterion weights subjectively and objectively. The method was applied on a mesoscale, which showed interdistrict disparities. The real-time values were scaled and overlaid with AHP-entropy obtained weights with the help of weighted sum overlay tool. The values were processed in a geographic information system (GIS), which showed the regional disparities and their effects on the overall demographic scenario of a district. The ratio of changes in DCs was further evaluated as discrete values. The final values of the DCs obtained from the model were compared with the actual values of different districts, which showed an average of 80% accuracy of the model.

In both rural and urban environments, transportation and access to food are coupled, especially in regions known as food deserts (FDs). However, transportation is not the only factor that may impede food access. This study identifies factors that influence where a household chooses to shop by creating a location-choice model using real travel patterns of low-income households in Dallas. While this analysis shows that travel time to the store remains the most important factor, the results indicate that accessibility also depends on the (1) age of household members (e.g., the presence of seniors or children), (2) access to mobility options, (3) built environment and urban development, (4) household size, and (5) employment. A new metric of food accessibility is formulated, incorporating multiple contributors to inaccess and overcoming limitations of the USDA FD definition. The results show that the proposed metric adapts to any level of aggregation, identifies where targeted interventions could be implemented, and allows for the integration of real travel and shopping behaviors to better coordinate urban planning approaches that increase access to food in the urban environment.

Decreasing automobile dependence is an important public policy among those commuting to suburban universities. This study focuses on travel behavior, transportation mode choices, and their determinants of Najran University, a suburban university. A questionnaire survey was distributed to faculty members, staff, and students. Based on statistical analyses and multinomial logit models, the results show that the average daily commuting distance is 41 km, and the average trip duration is 46 min. Most of the commuters drive alone, although some rideshare or use buses, especially females. Male students and married members show more of a tendency to use alternative transportation modes than driving alone, but male faculty members and staff show positive utility for driving alone. The longer the trip, the higher the probability of carpooling for males. On the other hand, female staff and faculty members increase the propensity of commuting alone with a chauffeur or carpooling. Females who spend around 50 min commuting to campus are less likely to use alternative transportation modes. The study concludes by setting some recommendations and a framework for implementing, administrating, and enhancing sustainable transportation modes that can make a zero-carbon transportation network is within reach.

Several cities around the world have been developing specific strategic plans to foster urban resilience. These plans, which are known as urban resilience strategies, do not follow a default format; however, they do follow similar patterns when they are designed by cities within a given collaborative network, such as the Resilient Cities Network (R-Cities). This study will identify the predominant sectors considered by the Brazilian city of Salvador’s resilience strategy, based on actions, shocks, and stresses, and will compare these with the sectors considered the most by other cities within the R-Cities. The results demonstrate that when urban resilience increases, the resilience strategies of the cities studied, which include Salvador, place particular importance on the social and urban planning sectors. The predominance of both sectors reveals the importance of maintaining a broad view when developing strategic urban plans and acts as an alert for urban planners on the importance of analyzing urban resilience holistically, beyond building safe infrastructure. In addition, this study will highlight the importance of including resilience as a guiding theme in urban planning agendas and when developing public policies to prevent risk and develop infrastructure plans. All aspects and sectors of social and urban planning that are fundamental to building urban resilience must be involved.

The collective housing estates, setting, and place of life of thousands of people is an element that exerts a great influence on the image, positive or negative, that a city reflects. These urban entities accumulate several dysfunctions, deficiencies, and problems, thereby altering their inhabitants’ quality of life and well-being. This paper aims to assess the quality of life in these cities to improve it. For this purpose, a combinatorial approach will be used, based on the multicriteria approach, through the questionnaire survey and the lexicometric analysis. This combination of methods is a novelty in this field of research. It brings about an adequate change according to the real needs and expectations of the inhabitants and goes beyond the frequently used walking diagnosis. To sustainably improve the environment and the quality of life of the inhabitants of these cities, and, thus, to overcome the accumulated spatial, social, and economic deficiencies, a new policy is required. This is local urban management as a curative, multidisciplinary, and coresponsible approach. It aims to enhance urban quality, create quality spaces, and develop residential attractiveness by promoting services and activities within and near these cities to reduce social tensions, vandalism, and delinquency. Local urban management, which aims to be sustainable, offers a pleasant living environment, a better quality of life for inhabitants, and a fulfilling social life.

Reducing driving among young adults is an important topic because their travel behavior is shaping future travel trends. However, previous studies have paid less attention to the influence of compactness at both residences and workplaces on young adults’ commuting behavior in the Chinese context. Moreover, few studies have examined the influential pathways from compactness to young adults’ commuting behavior. To fill these gaps, based on a post-’80s (people born between 1980 and 1989) survey conducted in Shanghai in 2013, this study employed a generalized structural equation model to examine whether both compact residences and workplaces affect young adults’ choices of commuting mode and, if so, whether or not car ownership and commuting distance are mediators. Results show that compactness at both residences and workplaces is associated with young adults’ commuting behavior, but that the compactness at residences has a higher influence. Moreover, we identify that both car ownership and commuting distance are mediators in the relationship between compact residences and commuting behavior, but not in the relationship between compact workplaces and commuting behavior. This study concludes that applying the compact land-use policy at both residences and workplaces could reduce young adults’ driving behavior in China.

This paper will explore whether and how different modes of postsocialist urban transformation of inherited large housing estates (LHE) from the socialist past have influenced quantitative changes in urban green space (UGS) at the neighborhood level. The investigation will be conducted on a representative LHE neighborhood in the city of Niš, Serbia. This paper will introduce the Urban Green Transformation Index (UGTI) that combines five weighted parameters by employing the geographic information system–multicriteria decision-making (GIS–MCDM) method, which uses linear aggregation with a weighted overlay approach. This describes the impact that transformations have on UGSs for their permanency. The results from this paper indicate that the LHE redevelopment processes have caused constant pressure on the UGS throughout the postsocialist period, which has led to their regressive changes. The index presented in this paper could be used as a corrective, or mandatory, or both urban and land use planning and decision-making tool when assessing the degree of environmental and social sustainability of newly planned construction within the LHE neighborhoods.

The fast growth of megacities population has resulted in severe traffic issues. Developing highway networks is considered as one of the major strategies in Iran’s capital city. However, health, environmental, and social consequences have been observed due to increased motorization and megaconstructions. This study aims to explain how residents perceive the effects of urban elevated highways (UEH) on their quality of life. Therefore, the effects of Sadr highway before and after the double-deck construction are examined via pre- and post-phase assessments. Most studies have focused on the experts’ opinions to investigate the effects of UEHs on the quality of life and place, while more attention is required to residents’ experience and their perception. The methodology includes two steps: (1) identifying the influential factors of qualities of life and place in the context of UEH impacts based on focus group discussions (FGDs), designing a questionnaire as an assessment tool; and (2) surveying to assess the residents’ perceptions regarding the impact of Sadr UEH on their quality of life and place. Results showed that low volume of residents reported life improvements over the development of the UEH, and two criteria of liveability and environmental qualities have been significantly reduced. However, some factors such as branding and private investments have not been reported to be as significant as other qualities. Also, results indicated that two indicators of comfort and place identity are the most influential factors on residents’ perceptions. This research highlights the significance of residents’ opinions and preferences for developing transportation policies.

This paper addresses a problem in evaluating the impacts of internet-app-based dockless public bicycles and public transport (i-PB&PT) on young people's mode choices considering their choice intentions. A method is proposed, based on the theory of planned behavior and structural equation modeling, to identify changes in the modal split and in travelers' willingness to buy and use private cars after having the intention to use the i-PB&PT mode. Guangzhou City was used as the study case, and an stated preference (SP) surveys was conducted. (1) The density of i-PBs was increased and, accordingly, the reduced cost of i-PB use strengthened travelers' intentions to choose i-PB&PT. For example, when the bicycle search time decreased from 4 to 1 min, the i-PB&PT modal split increased from 38.21% to 41.28%, whereas, if the transfer time between PT and i-PB use decreased from 3.5 to 2 min, the modal split of the combined mode increased from 40.72% to 49.59%. (2) Car ownership decreased from 1,190,465 (for the case without bicycles) to 650,556 as the travelers' intention (endogenous latent variable) to choose the combined mode became stronger. In particular, the values of the three exogenous latent variables (E––emotional attitudes, O––satisfaction, and S––subjective norms) increased (E = 2 to E = 5; OS = 1 to O = 4; S = 2 to S = 4). Therefore, the large-scale implementation and widespread use of the i-PB&PT model should significantly decrease car travel and transport emissions.

The permanent settlement of rural migrants can greatly influence the city size distribution. Although there have been multiple theories about rural–urban migration, the different effects of determinants on the settlement intention of rural–urban migrants across different-sized cities lack studies and remain unclear. Based on the 2016 National Floating Population Dynamic Monitoring Survey Data of China, this study investigated the factors determining rural migrants’ urban settlement intention and compared different-sized cities. It was found that the settlement intention of rural–urban migrants across different-sized cities showed a U-shaped curve, which was largest in supersized cities, followed by megacities, large cities, and Type-II small cities, and it was the smallest in medium-sized cities and Type-I small cities. After controlling the other determinants, the relationship between city size and settlement intention was also a U-shaped curve, which may be explained by the Rosen–Roback model. Moreover, although personal income and urban social insurance suggested similar effects on settlement intention across different-sized cities, the effects of educational attainment, the length of migration, occupation, marital status, housing conditions, and interprovincial migration on settlement intention differed significantly between different-sized cities. Based on these findings, it was suggested that the citizenization of rural migrants should be promoted through multiple kinds of policies including hukou reform, social insurance policy and housing policy, and different-sized cities adopt differentiated urbanization strategies, with a focus on small towns and within-provincial rural migrants.

There are large heterogeneities in the logistics development of urban agglomerations in western China due to the low compactness and spatial stability of urban agglomerations. Using the statistical yearbook and logistics industry data of 135 cities in western China from 2003 to 2018, we analyzed the spatial distribution characteristics of logistics enterprises using kernel density and cold–hot spot analysis. Simultaneously, economic development level, industrial structure of circulation, and the logistics industry are identified as influencing factors of logistics industry evolution. The comparative and integration analysis of spatial autocorrelation models and geographically weighted regressing models are implemented on the influencing factors of logistics enterprises’ spatial-temporal evolution. Our study revealed that the number and density of logistics enterprises in western China have continually increased in the past 20 years, factors such as per capita gross domestic product, population quantity, population density, the proportion of the tertiary industry, and density of logistics enterprises are all key factors supporting the evolution of the logistics industry in western China. The logistics industry in the western provinces has had outstanding development in the past 20 years; however, there are still obvious regional inequalities due to factors such as infrastructure and policy.

Rapid urbanization adversely impacts urban air quality, impacting human health and the ecological environment. However, few studies have systematically explored air quality from the perspective of urban structural evolution. This can be done using two scales: one focusing on microscopic patches and one focusing on the macroscopic built-up area. Based on polycentricity at a city scale, urban growth patterns at a patch scale, and other natural and socioeconomic data for 362 cities in China, this study applied spatial regression models to quantify the impact of urban structure on PM_2.5. The PM_2.5 data were downloaded from the NASA Earth Observing System Data and Information System (EOSDIS) data center. The results show the following: (1) at a city scale, the polycentricity index had a significant and negative relationship with PM_2.5, the development of polycentric cities supports improvements in air quality; (2) at a patch scale, three urban growth patterns (edge-expansion, outlying, and infilling) all significantly and negatively impact PM_2.5. Urban growth continues to increase PM_2.5 pollution in China; and (3) road density, the built-up area, population density, land-use mix, and other control variables have an influence on the PM_2.5 concentration, and this study verified the existence of a scale effect. In addition, considering the different urban development trajectories of developed and developing countries, this study makes targeted recommendations for urban managers wanting to make reasonable development policies. In general, quantifying the relationship between urban structure and PM_2.5 helps provide a scientific basis for city planners and managers to optimize urban layouts.

With the increasing aging and the accelerating urbanization of China, the layout of urban medical facilities should be adjusted to meet the needs of the elderly population. This paper takes Hefei, China, as the research object. A questionnaire survey was conducted on the elderly who went to different levels of medical facilities for daily medical treatment, and 2,271 valid questionnaires were collected. The survey found that an accessibility factor of medical facilities is a common concern for the elderly who go to facilities of different levels, which indicates that it is reasonable to optimize the layout of medical facilities at all levels from the perspective of accessibility. Results revealed that the elderly in Hefei considered living within 10 km from a tertiary hospital (referred to as a Grade A facility in this paper) was most ideal. Meanwhile, a primary or secondary hospital (a Grade B facility) was most accessible within 6 km, and within 1.5 km was the optimum accessibility distance for a community health service center (a Grade C facility). This study considered the aforementioned medical service radii suitable for the elderly. From this, the study evaluated the accessible service range of different levels of medical facilities suitable for the elderly through the network analysis in ArcGIS. Then, the scarce areas of medical services in the city could be determined. Through location–allocation models, it was found that to realize the ideal medical distance for the elderly, 2 additional facilities were needed for Grade A, 1 for Grade B, and 61 for Grade C. The results could provide references for subsequent urban medical construction and aging development in China.

Unequal relationships, division of cities to impoverished and wealthy areas, and the increasing distance between them are a part of the effects of neoliberalism on the face of cities. Now, on the one hand, with the discovery of oil, Iran has been closely connected with global capitalism, and on the other hand, the political economy of oil itself (as a background condition) contains unbalanced social policies. Accordingly, the present study aims to investigate the spatial effects of the unbalanced politics of globalization and the oil-based economy in Tehran as the capital of Iran. A quantitative approach and descriptive–explanative analysis were used for this purpose. The results indicate that in the spatial restructuring of Tehran, the upper and lower socio-occupational classes have been significantly concentrated in the north and south of Tehran, respectively, which can be called the spatial segregation of Tehran.

Housing is fundamental to livelihood. House prices are not only affected by house quality, but also closely related to the location. In order to recognize the urban real estate market, it is meaningful to quantitatively analyze the impact of location on house prices. This paper aims to investigate the relationship between house price and location. First, an inverse distance weighted (IDW) method is applied to recognize the spatial distribution of house prices. Second, spatial auto-correlation analysis is applied to uncover the spatial pattern of house prices. Finally, a geographic weighted regression (GWR) model is used to analyze the extent and spatial heterogeneity of the impacts of location elements on house prices quantitatively. The main area in Hangzhou is used as a case study area. Crawler and remote sensing technology are utilized to fetch the house prices and five public facilities revealing location, including subway stations, schools, hospitals, green space, and business centers. The study finds that house prices have evident spatial heterogeneity and spatially agglomerate. Ranking the five public facilities according to the impacts they have on house prices, we reveal that school > subway station > green space > business center > hospital. Schools and subway stations are the most important location factors on house prices. Schools, subway stations, and green space all have a positive effect on house prices in the study area, whereas business centers and hospitals have a negative effect. The research unfolds the relationship between public facilities and house prices and provides support for improving the distribution of spatial resource and sophisticated urban management.

Following the proclamation of the Republic of Turkey in 1923, one of the most important urban planning and architectural projects of Mustafa Kemal Atatürk’s national program was the establishment and development of a new capital city called Ankara. During these formative years, Ankara underwent a major program of architectural urbanism and modernism that visually set the young republic apart from its recent Ottoman past. This paper will attempt to examine historical precedents in capital city planning via a cross-country analysis to that of Ankara; however, it will also highlight the extant literature and contribute to the argument that Ankara provides a unique experience in modernism, urbanism, and especially nation-building in the 20th century. Although Turkey’s political and national direction has taken a new course in the early 21st century, the Kemalist strategy in communicating national identity and nation-building continues to be emulated and communicated in state-sponsored architecture in Ankara.

This study aimed to consider the street structure and the relationship between such structure and people’s route choices as well as people’s street structure concerns or preferences based on a common mapping tool. We used the map recording method to conduct a route choice experiment, captured the street structure–strolling route relationship, and performed a route choice experiment in actual space, preliminarily testing the results of the previous experiment. We also conducted interviews to determine how participant perceptions of street space on the map differed from perceptions of actual street space and how paths were chosen. The results show that the participants’ route choice tendencies change with street structure characteristics. Despite a rich built environment in real space, the participants give considerable attention to street structure. Based on the route choice strategies, the participants could recognize the streets on blank maps as real streets and imagine themselves walking on those streets. However, the map recording method has limitations, e.g., the influence of pedestrians’ physical strength on their route choices is not considered.