Journal of Urban Planning and Development

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

The urban form and transportation cycle are common yet crucial factors for urban managers and transportation planners to devise effective transportation management strategies. This paper considers the effects of transit subsidy policy on households’ travel behaviors in a computable general equilibrium model of a monocentric city with two income classes. The proposed model explicitly formulates the interrelationship among three parts of agents, namely the government, the agencies providing transportation services, and the households of different income levels. The government is intended by the transit subsidy policy to encourage households to travel by bus and maximize social welfare. Meanwhile, the households choose their residential locations and travel mode to maximize the household’s utility under a limited budget. Furthermore, the agencies providing transportation services, as part of the urban transport system, will endeavor to maximize their criteria (utility or profit) since they are determined by the economic conditions. Besides, the model demonstrates that government subsidies for bus travel affect not only the residence location and travel mode of households but also the supply agencies that provide transportation service. The effects are manufactured by applying a numerical general equilibrium approach calibrated revealing a significant relationship between the degree of exposure to the transit subsidy policy and the economic identity of the agencies. The transit subsidy policy is not necessarily beneficial to low-income households. Therefore, it also indicates that the proposed model responds to the impact of transit subsidy policy on household travel behavior, particularly in terms of revealing the relationship between households and internal other agencies.

The Guangdong–Hong Kong–Macao Greater Bay Area urban agglomeration, one of the world’s four largest bay area urban agglomerations, occupies an important position in China’s national development. In this paper, the expansion hotspot model, an urbanization index, a gravitation model, and a socioeconomic location model are used to explore changes in the characteristics of the urban agglomeration in the Guangdong–Hong Kong–Macao Greater Bay Area. The research results can provide decision support for government urban agglomeration planning. The research reveals the following. (1) In the skeleton maps of the expansion hotspots in the Guangdong–Hong Kong–Macao Greater Bay Area, Jiangmen shows an irregular shape, Shenzhen shows an irregular H-shape, Dongguan and Hong Kong show a shape somewhat between a circle and a star, Zhongshan shows a gourd-shape, and Guangzhou, Foshan, Huizhou, Zhaoqing, and Zhuhai show a polygon shape. (2) In 2000, 2010, and 2018, the urbanization index for the urban agglomerations were 41.78%, 50.87%, and 54.41%, respectively. The level of economic development, household registration policy, and urban planning are important factors affecting the development of urbanization. (3) The city quality and spatial connection strength of urban agglomeration have significant spatial nonequilibrium distribution characteristics. The total city quality of Shenzhen, Hong Kong, and Guangzhou accounted for more than 41.5% of the total city quality of the city cluster at the same time, and that of the east coast of the Pearl River is much stronger than the west coast. (4) There are “faults” in the socioeconomic location of the 11 cities in the urban agglomeration, with significant polarization. The socioeconomic locations of Jiangmen, Huizhou, and Zhaoqing have been below the reasonable socioeconomic location range in the past 20 years.

One important research question related to walking for transportation is whether people like to walk more or not. Past research on walking-related travel behavior has mainly considered objective measures of walking, quantifying trips that were actually taken. This paper emphasized tendency to walk more (TWM) as a subjective measure of walking in traveling to/from work. Data was collected in 2015 in the urban area of Rasht, Iran from 432 working commuters. A full-scale structural equation model was applied to explore relationships between the TWM and variables measuring the current amount of walking, attitudes, individual personality, and built-environment characteristics. Results showed that the current amount of walking was the highest determinant of TWM. Results demonstrated that positive attitudes toward walking affect the TWM both directly and indirectly and its effects were even greater than having a walkable environment. Considering the indirect effect of positive attitudes on the TWM increased the total effect of this variable by 13.8% relative to the model with the direct effect only while keeping all other relationships in the two models the same.

Hosting large conferences and events often facilitates the transformation of a city by the government. Before the 9th BRICS Summit, the local government launched a systematic urban renovation project, providing a feasible way for the government to increase accessibility for elderly residents by covering the necessary and additional costs. We aimed to present an economical and effective method for obtaining evidence-based reports that will encourage policymakers to increase their input and implement the policy of age-friendly cities. The data were derived from seven waves of regular follow-up investigations that were conducted before and after the 9th BRICS Summit. Residents over 18 years of age were sampled from the family planning system using the multistage stratified sampling method and were interviewed via telephone. The scenario method was used to simulate the effect of promoting the age-friendly city strategy on residents’ subjective well-being (SWB). Each respondent was randomly interviewed with one of the parallel versions of the questionnaire (positive or negative scenarios) to ensure intrainterviewer randomness. The paired-sample t-test was used to analyze the changes in residents’ attitudes given urban construction. Hierarchical regression analysis was then employed to test how the scenarios affected participants’ SWB to estimate the influence of the future implementation of age-friendly city policies. Residents’ levels of satisfaction with the city’s popularity, transportation, development, appearance, and competitiveness improved significantly after the BRICS Summit compared with that at baseline. Promoting the construction of age-related cities has the potential to significantly improve residents’ SWB, and residents of all age groups can benefit from this strategy. Urban renewal during the BRICS Summit improved the quality of life of local residents. The SWB of residents can be improved through urban transformation, such as the promotion of the construction of age-friendly cities. Moreover, the scenario method has application value and prospects for providing evidence-based urban planning advice to policymakers.

As one of the key factors of urban development, cultural space plays a crucial role in highlighting urban characteristics and inheriting urban culture. A comparative study of the core built-up areas in Xi’an and New York is conducted using a systematic mathematical method. The cultural spaces in Xi’an 2nd Ring Road Area (XSA) and Manhattan Borough (MB) are comprehensively quantified in terms of fractal dimension, compactness index, average nearest neighbor ratio, and kernel density. Results show that significant differences exist between the cultural spaces in XSA and MB in terms of composition, quantity, density, and area at macro- and microlevels. The cultural spaces in Xi’an are more uneven, discrete, and randomly distributed than those of Manhattan. This research can provide a reference for future studies on the cultural space characteristics between eastern and western cities.

Mobility is a critical factor in promoting social sustainability. Previous studies have confirmed the critical psychological determinants that influence individual mobility. However, these studies rarely considered the relationships among different psychological factors of public transport users and social inclusion. The present study addresses this gap by examining the impact of three crucial psychosocial factors, namely, perceived social norms, perceived social support, and perceived neighborhood social environment on social inclusion. Moreover, we also investigated a mediating role of perceived accessibility among these psychosocial factors and social inclusion. Data was collected from a sample of 243 older women (aged 60 years and above) residing in Lahore, Pakistan, through face-to-face close-ended questionnaires. SPSS statistical software and SmartPLS were used for data analysis. The critical argument that develops from our investigations is that perceived social norms, social support, and neighborhood social environment are essential drivers of social inclusion. The results further reveal that addressing these psychosocial factors can enhance the perceived public transport accessibility and, thus, social inclusion among older women. This study provides useful findings for urban planning and transportation researchers to consider the psychosocial aspects of public transport users that could improve older women's social inclusion.

Traditionally, urban land use planning belongs to urban planning and transportation infrastructure construction belongs to transportation planning. However, it is widely recognized that the integrated optimization of urban and transportation planning is the development trend in the future. This paper will develop a methodology to model the integrated transportation and land use planning problem that will consider the stochastic characteristic of link capacity and travel demand. The integrated planning problem will be formulated as a bilevel programming model. In this programming, the upper-level decision makers are urban planners and transportation engineers that aim to maximize network performance by making integrated planning schemes. Specifically, the planners should determine how to allocate limited resources between the development of residential and working locations, and improvement of the traffic network. The lower-level decision maker is the heterogenous traveler that makes residential and working location decisions, and the choice of travel path. The land use pattern is indicated by the spatial distribution of residential and working locations. Finally, the particle swarm optimization (PSO) algorithm will be used to solve the bilevel model. A set of numerical experiments will be carried out to illustrate the application of this model.

The aim of this work is to investigate the interaction between mixed land use patterns and urban road structures based on the balance theory of complex networks. An approach for extracting a signed network from a weighted road network is proposed, and a walk-based balance index for urban road networks is developed. A probability matrix is adopted for the conversion between various land use types. Then a bi-level integrated mixed land-use transportation (IML–T) model is established, where the balance index is used as a parameter to correct the degree of mixed use. The upper-level is a multi-objective problem that considers total travel time, wider economic benefits, and a balanced internal capture rate, while the lower level involves the problem of user equilibrium (UE). The proposed method was validated through a sample network and the application to Handan City in China. The results indicate that the structure of the road network can be accurately measured by using a balance index. The local traffic property can be improved by choosing a mixed-use pattern given by the IML–T model. Moreover, the IML–T model is more efficient than traditional network design models at reducing the congestion caused by the distribution of the aggregated population.

Land-use allocation (LUA) is a spatial optimization problem for urban planning in the future. The solution to this problem could be enhancing the effectiveness of optimization algorithms that create a balance between urban needs and efficient LUAs. This study will improve the performance of conventional genetic algorithms (cGAs) to address future LUAs. The enhancements will include improved initialization and mutation operators and a modification in the fitness function by the introduction of the area size deviation (ASD). The study will consider four objective functions to be maximized that include suitability, compatibility, conversion cost, and spatial compactness. The improved algorithm will be tested and applied to Taiz, Taiz Governorate, Yemen, to acquire the optimal LUA based on their 2035 plan. The findings produced three scenarios that were objectively weighted. The experimental results revealed that the improved genetic algorithms (GAs) were superior to the cGA for convergence speed, solution efficiency, optimality, and fulfillment of all constraints that included the LUA area size. The study exhibited the impact of weight variations on optimum LUAs for decision makers. This optimization resulted in a significant radial plan that featured green wedges and a smart arrangement of land-uses (LUs).

The relocation of logistics facilities toward the periphery of urban areas—that is, logistics sprawl—is a major challenge for policymakers due to the impacts on the economic geography of suburban areas and associated changes in truck traffic pattern. The logistics sprawl considerably affects the vehicle kilometers traveled (VKT) since logistics facilities are the origin or destination nodes for urban freight transport. The effect of logistics sprawl, coupled with industry category, employment size, fleet ownership, and cohort on the VKT, is an unaddressed research area that requires significant research attention. To quantify the effects of logistics sprawl on the VKT, this paper utilizes establishment-based freight survey (EBFS) data to perform a cross-sectional analysis of urban and suburban logistics facilities. The distinct variations in the effects of logistics sprawl across multiple industry types are investigated using the EBFS data. The combined model indicated that the VKT generally increases as an establishment is located away from a city center. Compared with the establishments’ VKT in Sprawl 1, the VKT for establishments in Sprawl 2, 3, and 4 increases by 6.39, 4.12, and 6.06 km, respectively. Classified industry model results demonstrated that the sprawl effect on the VKT is industry specific. Establishments dealing with food products demonstrated a positive relation between the average VKT and the distance of an establishment from a city center. However, the sprawl effect was not consistent for establishments dealing with wood products, plastic and rubber products, mineral products, and metal and metal-related products. Moreover, the developed cohort model indicated an average VKT increase by 29.42 and 46.43 km for establishments that started operations in the postindustrialization and postliberalization periods, respectively, compared with the establishments being operational from the postindependence period. This investigation’s tangible outcome is to present the influencing factors of the VKT, which will be beneficial for policymakers to develop industry-specific guidelines on land use, employment restructuring, and subsidies on owning different types of commercial vehicles.

This study assessed the dynamic variations in ecosystem service value (ESV) in response to land-use changes under rapid urbanization and evaluated the coordinated relationship between economic development and ecological conservation by establishing the eco-economic harmony (EEH) index evaluation model. Taiyuan, the resource-based city in China, was selected as a study area. The results show that the total ESV in Taiyuan increased from 8.95 billion Yuan in 2005 to 9.31 billion Yuan in 2016. The ESVs of all land-use types experienced a decrease except for woodland and grassland. Climate regulation and hydrology adjustment were the dominant two ecosystem service functions in the study area. The ESV of climate regulation increased the most (382.62 million Yuan) but water supply decreased the most (−47.91 million yuan). The relationships between economic development and ecological conservation have experienced the evolution process of low conflict–potential crisis–low conflict from 2005 to 2016, indicating that the contradiction between economic development and ecological conservation is becoming increasingly serious over time. Therefore, scientific land-use policies and environmental protection strategies are urgently needed for achieving a sustainable development. This study provides valuable guidance for sustainable urban planning decision-making on maintaining the balance between economic development and ecological conservation under rapid urbanization.

Superblocks are city blocks whose size is significantly larger than average for a city block. They are considered to be close if they only have a few gates connecting the pedestrian and car traffic inside with that outside of the block. The gate setting of superblocks, namely the number and location of gates, despite playing a very important role in the overall traffic performance, has attracted limited attention in research. This paper narrows this gap by proposing a bilevel optimization model to calculate the optimal gate setting for superblocks. The lower-level model involves the traffic assignment, paying attention to travelers' mode and route choice behavior. The upper-level model computes the optimal number and location of gates to minimize the total cost, considering both travelers' cost and infrastructure cost. To solve this model efficiently, we also develop a solution algorithm, whose output is the optimized gate setting. A case study is used to illustrate the impact of the gate-setting problem on the performance of the transportation network, and the applicability of the proposed algorithm. Results indicate that the number and location of gates significantly impact traffic performance. For example, it is possible to have a lower cost with three gates that are well located than with nine gates that are poorly located. Furthermore, for the specific network studied, the optimal gate setting solution reduces the total cost by 17% and leads to a 3% mode shift from private car to metro when compared with the existing conditions.

This study aims to determine and analyze the factors that are associated with urban resilience and sustainability for the slum inhabitants of Islamabad, Pakistan. This study will adopt a quantitative design to study the significance of factors that affect urban resilience and sustainability in Islamabad’s slums, Pakistan. The research method in this study will be a survey questionnaire that was filled by 365 respondents using simple random sampling techniques. To conduct structural equation modeling (SEM), this study will use SmartPLS 3.0 through which all the important results will be gathered that include convergent validity, reliability, factor loading, composite reliability, discriminant validity, R square, and path coefficients. The findings show that the factors that significantly influence urban resilience are geographic size (B = 0.395; p-value = 0.000 < 0.01), preparedness and foresight (B = 0.144; p-value = 0.019 < 0.05), and resource and financing (B = 0.213; p-value = 0.000 < 0.01). In addition, the results highlight that geographic size (B = 0.232; p-value = 0.000 < 0.01) and resource and financing (B = 0.096; p-value = 0.097 < 0.1) are significant to urban sustainability for the slum inhabitants in Islamabad, Pakistan. This study is limited to the geographical bounds of Islamabad, Pakistan, and specifically the slums. Therefore, it could be improved in the future by considering other cities in Pakistan, such as Karachi or conducting a comparative analysis between cities. This study considered a limited number of factors; therefore, further research could explore additional factors that affect urban resilience and urban sustainability.

Continuously high housing prices in large and medium-sized cities in China indicate that the urban housing provision system (HPS) has some drawbacks. One reason is that the housing rental market has long been ignored by authorities. In this paper, we divided the development process of HPSs into five stages from the view of housing purchases and rentals. Then, we analyzed the possible housing demand change of citizens based on changed migration distribution, demographic trends, and housing affordability. Subsequently, we established a distance coordination model to determine the coordination level between the housing purchase market and the housing rental market and found that the western region in China has the highest degree of coordinated development, followed by the eastern region, and the central region has the lowest. Finally, we proposed six preliminary strategies to optimize the HPS in the new era, and they can be summarized as (i) realizing virtuous interactions between the policies of the central government and the local government on two housing markets, (ii) reducing the development gap between the housing purchase market and the housing rental market, and (iii) establishing a Housing with Joint Property Rights system.

This research explored different types of intervention and designation in the creation and management of cultural agglomeration in an urban context. Accordingly, as a result of carrying out an in-depth literature study on the subject of cultural agglomeration, the research clarified the process of development approaches in respect of creation and management strategies of cultural agglomeration, considering both their positive and negative aspects and interdependence. The study moved beyond the generalized insights of the development approaches through examining changes in the modes of intervention and designation that can lead to multifold contributions of culture to sustainable development. The study further suggests that the evolutionary type of cultural agglomeration enhances long-term, realistic goal setting for urban development.

The origin–destination (OD) demand matrix plays an essential role in travel modeling and transport planning. Traditional OD matrices are estimated from expensive and laborious traffic counts and surveys. Accordingly, this study proposes a new combined methodology to estimate or update OD matrices (urban mobility) directly from easy-to-obtain and free-of-charge socioeconomic variables. The Málaga region, Spain, was used as a case study. The proposed methodology involves two stages. First, an automatic feature selection procedure was developed to determine the most relevant socioeconomic variables, discarding the irrelevant ones. Several feature selection techniques were studied and combined. Second, machine learning (ML) models were used to estimate mobility between predefined zones. Artificial neural networks (ANNs) and support vector regression (SVR) were tested and compared using the most relevant variables as inputs. The experimental results show that the proposed combined model can be more accurate than traditional methods and ML models without the feature selection procedure. In particular, SVR with feature selection slightly outperformed the combined model using ANNs. The proposed methodology can be a promising and affordable alternative method for estimating OD matrices, reducing costs and lead time significantly, and assisting and improving urban transport planning.

Schools are some of the most critical public facilities in urban and metropolitan areas. The location of schools not only affects the costs of construction and travel but also significantly affects the social welfare of the residents through its impact on education quality among other factors. The impact of school location on education quality and social welfare in general is controlled mainly by the impact of location on the balance between supply and demand, which directly affects the access of students to quality education. Therefore, selecting the location of new schools by considering the impact of location on both social and economic factors is a critical town planning decision as billions of dollars are spent every year to build new schools in major metropolitan areas across the world. However, despite the significant efforts made in previous studies, the existing school location optimization models are focused mainly on costs and efficiency as key decision objectives and little attention has been made to the impact of location on maintaining and improving the education quality by considering the balance between supply and demand. In this paper, we formulate a school facility location selection model as a multiperiod facility location problem, where the objective function attempts to optimize the location of new schools to minimize the excess demand in the school network by building schools at strategic locations, subject to budget constraints and zoning restrictions. This formulation incorporates real-life parameters, including the availability of land in different areas of a city, the fluctuation of land prices from one location to another, and the possibility of building different sizes of facilities in a certain location. The proposed model is formulated using mixed-integer linear programming and can be solved by off-the-shelf optimization solvers. An illustrative case study is presented, using a meshed grid made up of 400 zones, where the network characteristics are assumed known. The proposed model provides strategic planners with an original approach and a new perspective to model school location optimization problems. This approach contributes to the advancement of the provision in locating new schools over a planning period, by optimizing their supply-to-demand ratio, to improve social welfare.

Distance between a student residence and their school is as a major barrier for active commuting while trends in school siting and residential development have increased this distance. This study conducted a cost–benefit analysis of increased thoroughfare connectivity around schools in a representative US school system. A novel metric for organizations to rank schools by their walkability is introduced, and then network optimization techniques located the new thoroughfare connections that maximized student walking and minimized the length of the new connection. The increased time of physical activity from student walking and the cost savings from busing fewer students were compared to the financial construction costs of the new thoroughfares. Results from this case study show that recent development trends are antithetical to student active commuting, that short and inexpensive new thoroughfares can increase the number of student walkers and their physical activity and reduce busing costs, traffic, accidents, and pollution. This work calls for a collaboration between planners, school officials, and developers to design neighborhoods around schools that improve the health of the community and its children.

As a new low-carbon travel mode, bike sharing has become an important tool for urban residents to travel short distances. However, dockless bike-share trips could be influenced by weather conditions, temporal factors, and land use characteristics. This study analyzes the effect of meteorological, temporal, and spatial elements on the use of the Shanghai bike-share system, utilizing a dataset of all trips derived from the Mobike system. Hourly weather data, including rainfall, wind speed, visibility, humidity, temperature, and air quality index (AQI) were linked to hourly bike-share trip data, as well as temporal information. The impact of land use was investigated at the township level. Further, the bike-share user preference on the alternative transportation modes was explored when weather conditions are not suitable for cycling. Results show that rain, high humidity, and high temperatures are likely to reduce the usage of bike-share systems. The density of company, residential building, and metro station in a township-level division has a predominantly positive impact on bike-share flows. Even though adverse weather conditions would lead to the decrease of bike-share trips to both metro and bus stations, people are more likely to ride to a metro station than to a bus station. These findings could provide useful reference for transport agencies and bike-share operators to understand dockless bike-share user behavior and optimize the bike-share systems.

Safety is an indispensable condition of livable cities. Increasing fine-scaled understanding of the relationship between physical characteristics and perceived safety can provide reliable evidence to guide safety design, which in turn contributes to the livability of cities. To reach this goal, 30 sample sites were selected to represent the diversity of urban green spaces in Xuzhou, eastern China. The environment-related and crime-related perceived safety of these sites during the daytime and evening were evaluated by 717 participants who were invited through a snowballing method. The value of overall perceived safety was decided by the mean score of the two types of perceived safety. The main results include: (1) good maintenance of vegetation, open view, low locomotive accessibility of water, and more aquatic plants can predict a higher overall perceived safety during the daytime; (2) higher illumination and lighting sources in the distance of vision indicate a higher overall perceived safety during the evening; (3) females are more worried about the crime-related perceived safety than males during the daytime or evening.

This study proposed to explore real estate trends in the high-rise housing market in Belém, Northern Brazil. We based the theoretical approach on the macroeconomic, territorial, and social elements of the high-rise segment both in national and international contexts. The sample comprised 137 high-rise projects launched throughout the 2005–2017 period. A quadratic regression model confirmed real estate susceptibility to macroeconomic oscillation. A geographically weighted regression model revealed that larger dwellings were launched more in upper-income, lower formal employment rate, and lower infrastructure coverage regions of Belém. A multinomial logit regression model established differences in the launching likelihood between different categories of housing size projects. The outcomes were compared with worldwide tendencies, seeking both common and unique patterns of real estate exploitation. The methodological forms of exploring real estate trends in developing countries—which are scarcer—add significant scientific value for the urban planning community, as they assist public policy by identifying the susceptibility of urban areas to land exploitation, in addition to enabling replication of such real estate diagnostics in other cities of emerging countries.

The paper tackles a topic related to the use of prime material and recycled materials in construction, in the framework of the circular economy, where recycled aggregates can be considered, in part or even totally, as second prime materials for the construction sector. In particular, the authors describe the main phases of the MEISAR project, developing a circular cluster territorial model so that the quantity of recyclable materials can be estimated and geolocalized in the most appropriate processing plant, as well as assessing the potential market. In the study we combine spatial planning problems and industrial location factors of natural and recycled aggregates and concrete production plants through the geospatial representation of the MEISAR map. The closed market of Sardinia is analyzed and, in particular, the case study of the new soccer stadium in Cagliari, which involves the demolition of the existing stadium that will represent a source of “secondary” raw materials for the construction of the new stadium designed by the consortium Sportium.

Most cities experience growth periods, leading to a population boom and to stagnation periods followed by population decline. Russian scientific literature uses terms such as depressed, crisis, problematic, and waning cities to describe the processes inherent to the phenomenon of shrinkage. To this day, there is no unanimity in the terms and definitions used, so each study sets its own criterion to define shrinkage. The current study aims to elaborate a growth-shrinkage typology of Russian cities, outline major shrinkage features, and answer the question of what might have initiated shrinking processes in the Russian Federation. The authors applied cluster analysis to 883 cities to study growth trajectories and decline over the last 30 years. Six types of cities were revealed: constantly growing, growing with stumbling, parabolic type, inverse parabolic type, continuous shrinkage after the year 1998, and continuous shrinkage after the year 1991. The main findings are that 73% of Russian cities have been experiencing shrinkage to various degrees, and only 27% are growing or have stood on the path of stable development recently. This study provides a better understanding of urban shrinkage in Russia, brings additional insights into the types of shrinkage of Russian cities, and fills the scientific literature gap. Current typology covers a broad range of Russian cities and could provide a new perspective on shrinkage problems in Russia.

The physical structure and the identity of the city are formed over a long period of time. The best examples reflecting the spatial and structural characters are, without doubt, the historical city centers. Today, these historical areas, which are under rapid construction and population pressure, are becoming less perceptible and their relationship with the whole city is gradually decreasing. This research aims to reveal the value of accessibility by examining the change in Trabzon Kaleiçi and its immediate surroundings in the process since its establishment. In this respect, the present maps containing different periods of the city were used as a base, and maps showing integration levels and topological accessibility were created. By comparing these maps, the change in the accessibility level of the historical city center over time was revealed. At the end of the study, it was determined that the relation of the historical city center to the whole city decreased and the street network formed over the years negatively affected the access to the historical city center.

Recent reforms in the distribution of incremental land revenue in China aimed to establish an optimal scheme for the rational and equitable allocation of appreciation revenue from land that has been expropriated from peasant collectives, which effectively enables development and protects the interests of the peasants. First, the Shapley value method will be used to formulate a preliminary scheme for the equitable distribution of incremental land revenue between the government and peasant collectives, then a risk assessment procedure will be applied to adjust the allocations following both stakeholders' risks and contributions. The rationality of the resulting allocation scheme will be verified by comparing the theoretical results with the actual allocation of benefits accrued from transfers of rural collectives' operational construction land over 3 years in Jiutai District, Changchun City, Jilin Province, China. A questionnaire survey will be used to clarify peasants' opinions of land expropriation. The results obtained with the Shapley value method indicated that the government and relevant peasant collective were entitled to 93.19% and 6.81%, respectively, of the incremental land revenue based on their contributions. However, the corresponding allocations following risk adjustment were 90.83% and 9.17%, because the peasants have higher risks than the government. The peasants could generate CNY 38.38 × 10⁴/ha by directly marketing their rural collectives' operational construction land. This is similar to the amount (CNY 37.99 × 10⁴/ha) that they could obtain from the modified land expropriation system proposed in this study, which includes a share of the incremental land revenue. In addition, it agrees with the results of two pilot studies and meets the objectives of the reform. However, the questionnaire results showed that the peasants were in a weak position following land expropriation, and the current land expropriation system should include measures that safeguard their long-term well-being, which includes the dissemination of land expropriation information, strengthening of capital supervision, and the establishment of diversified, long-term security mechanisms.

The lack of transportation planning in cities of developing countries is causing significant problems due to rapid urbanization and exponential population growth. For transportation planning and policy-making, mode choice model is an essential element. There is a notable difference between the travel behaviors of children and adults, but the mode choice for school-going children trips remains unacknowledged. This study aims to develop a model for educational trips in Abbottabad city, Pakistan, and identify the significant factors influencing the mode choice of educational trips. Using Slovin’s sampling method, 370 samples were collected, from which 310 were used for model calibration and 60 samples for validation purposes. The multinomial logit model was developed in SPSS. The analysis shows that gender, age, household income, total travel time, cost, and distance are the influential factors that affect students’ mode choice. It was also found that travel time by school bus and public transport significantly affected mode choice. Urban and transport planners can use this study for developing transportation policies for addressing the issues faced by students.

Cycling is a climate-friendly, cost-effective, and greenhouse gas-efficient transport mode that produces relevant positive aspects to: urban innovation (new technology and services, that is, e-mobility and public bike-sharing systems), environment (reducing emissions, traffic congestion easing, increasing energy efficiency), public health (road safety, psycho-physical wellbeing, noise reduction), urban economy (infrastructure cost saving, low service and vehicle expenditures, energy saving, creation of sustainable green jobs), and inclusive society (improving inclusion of the local population, quality of life, wellbeing). Considering the 2014 Paris Declaration of the Transport, Health and Environment Pan-European Programme (THE PEP) for “the development of a pan-European Master Plan for cycling promotion,” it is necessary to implement support tools for urban planners and designers, who, simultaneously, provide a cognitive framework able to direct urban policymaking toward active mobility models/options and sustainable urban development processes. After highlighting the good practices of European cities related to the promotion of soft active mobility and modal split that contrast the use of private cars, this study presents a “morpho-syntactic” approach-based methodology apt at analyzing the city of Potenza (county seat of the Basilicata region, southern Italy) with the intention of producing a design scenario to develop urban cycling as an alternative urban development strategy. Geomorphological analysis-based techniques have been integrated with graph theory-based space–morphological analyses using the Space Syntax Analysis and the Place Syntax Analysis. The results obtained are useful to support a decision-making process for the development of an urban cycling infrastructure scheme that integrates Potenza's active transport infrastructures (mechanized pedestrian mobility) according to a multimodal approach. With the current national cycling supportive policy framework, local authorities are in a position to adopt strategies and actions aimed at promoting cycle-tourism and urban cycling, thus improving sustainable mobility policies as a component of urban planning.

The study of urban and regional impacts of high-speed rail (HSR) has drawn much attention in the research literature over the last few years. Previous studies have mostly used traditional tools (cost–benefit analysis, hedonic models, discrete choice modeling, and so on) to conduct ex ante analyses of potential HSR impacts. However, little attention has been paid to know the views of representatives from different economic sectors and their potential contribution to the participatory phase of the planning process. To address this limitation, this paper developed an ex ante participatory approach for analyzing HSR’s urban and regional impacts, which fed into and complement other traditional assessment tools. This approach was applied to the case study of San Sebastian and its province in Spain, which should be linked to the Spanish HSR network by 2025. The research found that different economic sectors agree on some economic impacts triggered by HSR but disagree on many social and regional equity impacts. The paper discussed the potential of this approach for policymaking, highlighting its value in complementing traditional impact assessment methodologies.

This study aims to propose a comprehensive evaluation index for the economy and integrated transportation system of metropolitan areas to analyze the interactive correlations between them and, thus, determine their developmental trends and characteristics, as well as the developed and developing metropolitan areas in China from 1998 to 2017. Moreover, a combination of a time-domain analysis and frequency-domain analysis was adopted to explore the interactive evolution correlation and spatial differences between both methods for 1998–2017. The sustainable developments of both metropolitan areas and China’s integrated transportation exhibited a steady upward trend, and the gap between the developed and the developing metropolitan areas showed an expanding trend. While long-term equilibrium interactions were noted between both, some variances were present in different regions at different times. While China and its developed metropolitan areas were of a pulling type, the developing metropolitan areas were of a promoting type. Besides, the impact of integrated transportation development on the economy of the metropolitan areas was more significant, and the degree of impact exhibited a high trend in the developed metropolitan areas but a common trend in the developing metropolitan areas.

Throughout history, natural hazards and disasters have always caused disturbance in the dynamics of urban systems, which represents a lack of adequate resilience in communities against natural disasters. Meanwhile, poverty seems to play a significant role in resilience in communities. Thus simultaneous examination of a community’s resilience against natural disasters and its poverty produces a better means by which to formulate new urban policies to improve a community’s resilience. This study, therefore, aims to explore the relationship between urban resilience and urban poverty. The resilience and poverty in the case study was measured by a disaster resilience of place model using the factor analysis and analytic network process method and Likert scale questions in the frame of a questionnaire, respectively. The study demonstrates that higher resilience in low-income communities can be justified with reliance on intervening factors such as social capital, public participation, social learning, institutions, and good governance, which can be measured through subjective poverty instead of an objective one. In this regard, findings show that the urban resilience of some low-income neighborhoods in Tehran is high. Based on the investigation, it is revealed that these low-income neighborhoods are not subjectively poor. Thus, it can be concluded that the relationship between urban resilience and poverty is significant when the poverty measurement is done subjectively.

Scenario-based land-use planning depends on choosing from among a range of inputs to a calibrated model to explore the corresponding range of future outputs and impacts—but how are these inputs chosen? This case study examined how a landscape ecology approach could better shape scenario development for a SLEUTH (slope, land use, exclusion, urban, transportation, and hillshade) model application toward achieving possibly more ecologically sustainable scenarios and, therefore, future landscapes. Our methodology relied on two main steps––developing landscape-ecology-led growth scenarios and using SLEUTH to model their impacts on urban growth and land-use change. As a case study, we applied the model to Sariyer, Istanbul, for the year 2045, where transportation infrastructure changes portend significant implications for the future landscape. Even though there are many works on urban growth in the international literature, there has been only limited investigation of the effects of urban transportation systems in developing nations and their implications for urban landscapes. This study's novelty lies in including a landscape ecology approach in the scenario development to enable better integration with modeling and the use of landscape metrics to modify the scenarios and interpret the model outcomes. Our research question is: can a joint approach of scenario development using landscape ecology principles (associated with landscape metrics) and SLEUTH modeling accurately forecast the impacts of landscape ecology and ecosystem services on human and urban systems? We conclude that a landscape ecology approach does help illuminate future urban-growth behavior led by transportation system development. Landscape ecology can be a medium through which the SLEUTH model can articulate more-comprehensive ecological planning related to the implications of different growth scenarios.

The quality of urban settlement is an essential element of people's desire for a better life, which has been capitalized into housing prices of local cities. However, previous literature focuses overwhelmingly on the determinants of intracity housing prices. There is still a lack of research on the determinants of the spatial disparity in intercity housing prices, and there is even less research on the association between comprehensive urban settlement quality and housing prices. This paper uses principal component analysis to evaluate urban settlement quality for 294 cities in China and applies spatial econometric models to examine the impact of urban settlement quality on housing prices. The results show that urban settlement quality in China is composed of five principal components: social livelihood, service industry development, leisure-traffic, the ecological environment, and economic development. There is spatial correlation between urban settlement quality and housing prices in China, both of which show high values in eastern China and low values in western China. Spatial econometric modeling results indicate that social livelihood and the ecological environment have a significant positive impact on housing prices, while service industry development and the leisure-traffic factor have a significant impeding effect on housing prices. In addition, residential land prices and per capita real-estate development investment are significant factors affecting housing prices in China.

Escalating challenges in modern cities along with rapid urbanization, which emphasize the requirement to manage cities, means that sustainable urban development is necessary, and smart cities have been identified as an ideological solution to achieve this. In Sri Lanka, the smart city concept has had a significant influence on city development projects and one smart city development project has already started. Therefore, due to the novelty of the concept, the development of strategic plans when delivering smart cities is beneficial. In addition, since a smart city is a multistakeholder ecosystem, ensuring the effective engagement of the stakeholders is a key success factor when developing smart city projects and therefore was selected as the main research focus. Using the explanatory sequential mixed research approach, a comprehensive literature review, a desktop, and case study will be conducted to investigate the stakeholders and factors that ensure their engagement in smart city projects. The research findings could be utilized to ensure the effective engagement of the stakeholders in smart city projects, which could enable the application of the smart concept during the development of cities in Sri Lanka.

Exponential growth and shrinkage of cities are two opposing trends in urban development. In this study, we analyze spatial growth and shrinkage at the regional level. We use the Guangzhou–Foshan region to identify the pattern and process of growth and shrinkage in the region with particular focus on cross-border areas. Specifically, we focus on how addressing shrinkage led to changes in urban planning with an in-depth discussion of its formation mechanism and the introduction of planning strategies. From the changes in light results during the period from 1985 to 2017 of the Guangzhou–Foshan region, stable areas are mainly concentrated in the old urban areas built before 2000, the largest urban area is of continuous growth type in line with the characteristics of urban expansion, and the area of shrinkage is small but concentrated in the cross-border areas. Particularly, since the 2008 financial crisis, extensive changes have been noted in the cross-border areas where such growing and shrinking areas coexist. Regional integration and the optimization of urban space would be effective methods to confront shrinkage. The findings may provide some reference for the urban shrinkage phenomenon that occurs in cross-border areas.

During the period of rapid urban growth worldwide, China’s urbanization process has soared. Based on China’s National New-Type Urbanization Plan (NNUP), this paper takes 11 national-level urban agglomerations (UAs) as the research area, aiming to conduct a dynamic quantitative analysis of the sustainable development (SD) level of UAs and reveal inherent laws and effective strategies about spatial planning of UAs. Different from the existing literature, this paper analyzes the SD level of China’s 11 major UAs during the urbanization process from a multidimensional perspective, including the comprehensive dynamic evolution of UAs, coupling coordinated development between the three subsystems, and internally coordinated distributions of UAs, which provides a crucial guarantee that the UAs’ SD will be analyzed comprehensively. First, the evaluation index system of a new-type urbanization SD is constructed. Then, two principal component analyses and time-series global factor analyses are performed to evaluate the SD of new-type urbanization in China’s 11 major UAs from the perspectives of the economy, society, and resources and environment. The characteristics of the SD levels of different UAs, the constraint factors of the SD levels, coupling coordinated development between the three subsystems, internally coordinated distribution characteristics of UAs, the relevant policy recommendations, and the reason why the Pearl River Delta UA has started to lag behind the Yangtze River Delta UA since 2010 are presented. Finally, we propose a plausible relation between the coupling coordinated degree (CCD) of UA subsystems and the internally coordinated development of UAs. Additionally, this paper provides a reference for policymakers to develop urban spatial planning policies to facilitate the SD level of relevant UAs by identifying the constraint factors of SD.

In recent years, significant changes have occurred in land usage and residential buildings due to population growth and urbanization. The residential location choice is a key component of the urban economics that ensures the dynamics of the settlements. Residential choice determination is a complex process that includes several indicators such as location and physical characteristics. These require perspectives from various disciplines. Presently, evaluation of residential buildings has become more important due to rapid urbanization, especially in metropolitan areas. This study aimed to identify the critical factors of residential location choice using the analytic hierarchy process, which is a multicriteria decision-making method. In this context, environmental quality, safety, and accessibility were determined as major factors in residential decisions. The study’s results can contribute to the development of a model for determining residential location choices. The present study can play a crucial role in urban development, urban policy, and its practical implications.

The demand for healthcare facilities in the world is growing daily, and this growth in demand exceeds general population growth. This situation has made hospital trips a vital issue during urban transportation planning. In this context, the aim of this study is twofold: (1) to investigate the hospital trip behavior as home-based hospital trips within the scope of trip production and attraction (trip generation) models and (2) to evaluate the predictive power of some robust and regularization methods in trip generation modeling. Within this scope, approximately 49,000 valid Household Survey Data (HSD) from 2001 (base year) and 2015 (target year) were used to develop comprehensive trip generation models for the home-based hospital trips. Multiple linear regression (MLR), ridge regression (RR), Liu, least trimmed squares (LTS), least trimmed squares–ridge (LTS–R), and least trimmed square–Liu (LTS–L) methods were used for the analysis, and results were evaluated in terms of specialized mean squared error (MSE) and root mean square error (RMSE). As a result, LTS–R and LTS–L increased future predictive power by approximately 55% compared with OLS. This study fills an important gap in the literature in terms of not only the use of regularization and robust methods in trip demand modeling but also examining characteristics that affect hospital trip behaviors. In addition, the paper proposes a “Hospital Mobility Coefficient” projection that could be useful in demand estimation for future hospital trips.

Owing to the influence of urbanization and globalization, many villages in China are transforming from traditional agricultural villages into postproductive villages. Changes in the industrial structures of these villages have caused corresponding environmental problems, which restrict rural sustainable development. Village planning is an important public policy instrument that is used to guide and regulate the construction and governance of villages and, therefore, it is an important tool to realize sustainable development in rural areas. Based on the problems that are experienced by these villages and the goal of rural sustainable development, this paper will use the village planning compilation as the framework, the Delphi method, and the analytic hierarchy process (AHP) to construct an operable and evaluable planning indicator system and uses Xufu village, which is a typical postproductive village in the Yangtze River Delta, China as an example for the analysis. The case study has proven that the indicator system has guiding significance for the compilation of village sustainable development planning, and the relative evaluation method objectively reflected the sustainable development trend of villages before and after the compilation and implementation of planning. This paper will create a tool for the quantitative evaluation of the compilation and implementation of village planning. The results could provide a reference for planning and developing strategies for sustainable village development.