Journal of Urban Planning and Development

Significant private motorization to meet increased mobility requirements has resulted in severe congestion and parking problems in urban areas. In such a scenario, Park-and-Ride (P&R) has been a potential and established travel demand management strategy that efficiently improves urban mobility by significantly reducing traffic congestion and parking burden in city centers. Thus, it is essential that urban planners and policy makers establish P&R facilities at appropriate locations. The current manuscript presents a state-of-the-art review of past and present practices in selecting appropriate locations for establishing P&R facilities. The present study provides useful insights into the critical factors influencing the identification of potential P&R locations, establishment of P&R facilities at optimal locations, and development of commuters’ P&R location choice behavior models. The study findings could help researchers, planners, and policy makers collate basic ideas of P&R facility planning and develop context-specific guidelines to suitably locate P&R facilities as potential urban travel demand management solutions in the context of developing countries.

Despite the unprecedentedly growing discussion of big data generated in urban environments and the widespread use of so-called urban big data (UBD) in recent years, there has been no consensus or widely accepted definition of UBD. Existing UBD studies have been either case-specific or applied in specific planning domains, such as transportation or tourism planning. A comprehensive exploration of the definitions of UBD in urban planning and related fields is timely and vital. This study is a systematic review of recent literature, consolidating 49 UBD definitions from 48 published articles in 39 journals, and classifying them into four themes: characteristics, sources, analytics, and impact. We found that most definitions are not given in an urban context and do not differentiate UBD from big data in a general sense. It is difficult to arrive at a one-size-fits-all definition of what constitutes UBD. Instead, the fourfold classification of UBD definitions allows us to identify three essential qualities of UBD that differentiate UBD from general big data and benefit urban studies: refinement of both spatiotemporal features and individual attributes at the microlevel, and the capacity and impact to depict, predict, and manage cities. We also identified three categories of challenges imposed on urban planning. This study serves as a starting point for a comprehensive understanding of UBD and contributes to expanding the discussion of UBD definitions and opportunities that UBD opens up in urban planning, facilitating better city management in the future.

This research captures the complex interaction between land use and transportation in an urban context. Even though several land use–transport interaction models at both micro and macro levels are available, there is a necessity to address the intermediate-level model with acceptable accuracy and without intensive data requirement. Further, consideration of road networks and land use in the traffic analysis zone demarcation is a significant requirement to enhance accuracy in estimating passenger flow distribution. This research provides a methodology to identify modified traffic analysis zones (MTAZs) based on traffic flow distribution and to redistribute macrolevel trip origins and destinations into MTAZs considering the road network and land-use character of the area. The core objective of the research is to develop a methodology to demonstrate the relationship between trip production/attraction and land use, to propose a method to redistribute macrolevel origin-destination data into MTAZs based on the identified relationship and to propose a method to assign estimated traffic flows to the road links. The methodology intends to guide the land use and transportation decision making. The methodology is developed based on both spatial and statistical analysis utilizing software and tools, such as ArcMAP, SPSS, and MS Excel. A case study covering the Colombo Municipal Council area, which is located within Colombo District, Western Province, Sri Lanka, is presented to demonstrate the application of the proposed methodology. According to the validation results, the proposed methodology has increased the accuracy of passenger flow estimation compared with the administrative zone-based conventional passenger flow estimation methodologies.

The development and expansion of 20th-century urbanization have led to large-scale populated regions that did not exist prior to this era. City-region is a kind of 20-century large-scale concept recognized as the most advanced stage of urban development. Regardless of its long history, the concept of city-region does not enjoy a standard definition. In this vein, the present paper seeks to provide a suitable framework for the primary argument determining the city-region boundary. Indeed, understanding the boundary allows planners to study a precise area, resulting in refining the concept and meticulously planning. Therefore, as applied research, it is aimed to respond to the practical problem in spatial planning by expanding and developing the city-region’s knowledge base. The paper has a mixed-method, using content analysis, the Structural Equation Model techniques, and Hot spot analysis. The results introduce six factors for determining the city-region’s boundary, including economic self-sufficiency, community relation, regional competitiveness, balanced management, services and infrastructure capacities, and the space of flows. The research’s flexible model allows planners to adjust it based on their field of study, inferring that the proposed model is utterly comprehensive; however, having access to different databases, scholars may encounter a challenge to adapt indicators. Accordingly, indicators should be customized based on general ones. In this study, the indicators are customized according to Iran’s data sources, and the output framework is tested on the Tehran region that deals with inefficiencies in urban and regional planning.

Abstract

Urban transportation is viewed as the second leading source of carbon dioxide emissions. The growing number of vehicles and road infrastructure-based supply in Indian cities is viewed as the essential driver of climate change and relevant consequences affecting the sustainability of cities. In this study, sustainable transport measures were analyzed to understand the emission mitigation potential of the Bengaluru Metropolitan Region’s transport sector in Karnataka, India. Relevant policies were identified under the planning, regulatory, economic, and technological instruments and grouped under four policy bundles. The mitigation potential of the policy bundles was quantitatively evaluated in terms of vehicle kilometers traveled (VKT), exhaust emissions, and greenhouse gas emissions. The study also estimated the carbon emission intensity and consumer surplus for different mode users across all policy bundles. The findings from this showed that Policy bundle 4, a comprehensive mix of various policies, demonstrated a critical decrease in VKT and emissions compared with the other policy bundles and, thus, provided good scientific decision support for transport policymakers.

Practical Applications

The study helps Bengaluru’s transport planning authorities in designing comprehensive mobility plans in a much more sophisticated way. The inclusion of public participation in the planning process helps improve sustainability. The consumer surplus provides a better understanding of social benefits derived from the policies, and emissions intensity estimates help understand whether the emissions have decoupled from the economic growth. The study also presents that public transportation plays a major role in solving congestion problems. Thus, it helps the planning authorities to prioritize their investments to make cities more liveable.

Abstract

This paper aims to investigate the impact of different parameters on promoting the role of cycling as a daily mode of transport. In the first step of the analyses, binary logistic regression was used to examine the impact of different parameters on using or not using the bicycle as a transportation mode in weekly trips. Then by text mining, the main reasons for not using a bicycle in weekly trips are outlined. Finally, for those who use bicycles for at least one utilitarian trip a week, the effect of different factors on the popularity of this mode is investigated by structural equation modeling. Tehran, as a big city in the Middle East and North Africa (MENA) region, was considered as the case study. The results suggest that it is necessary to work on social norms about cycling, especially among those with higher education levels and income. Women use bicycles less than men and it is also necessary to rethink attitudes and regulations in relation to women cycling in Islamic countries. Bicycle promotion should aim to facilitate more positive attitudes among women. Providing more facilities such as safe bicycle paths, bicycle parking, and bike-sharing facilities have significant impacts on using this mode and its popularity. In highly congested cities, alongside facilitating cycling, it is important to set restrictions on private car use.

Practical Applications

The United Nations has outlined sustainable development goals (SDGs), which among other important aspects focus on transportation systems in the cities. Attracting citizens to bicycles can be an effective step to establish a more sustainable future transport system. To contribute toward this objective, the current study aims to investigate the impact of different parameters on increasing the popularity of cycling and proposing countermeasures to attract more people to this mode. Tehran, the capital of Iran as a big Middle East and North Africa (MENA) city in a developing country with substantial sustainability challenges, was considered as the case study and 1,074 people in different districts of the city were surveyed. The practical results suggest that it is necessary to work on social norms about cycling, especially among those with higher education levels and income. Women use bicycles less than men and it is necessary to rethink attitudes and regulations in relation to women cycling in Islamic countries. Bicycle promotion should aim to facilitate more positive attitudes among females. Providing more facilities such as safe bicycle paths, bicycle parking, and bike-sharing facilities have significant impacts on using this mode and its popularity. In highly congested cities, alongside facilitating cycling, it is important to set restrictions on private car use.

Reasonable ecological function zoning is conducive to balancing ecological security and social development. Previous studies of evaluation for urban ecosystem services (ESs) have great progress. However, there is a lack of integrating ES stable hotspots into urban planning and refined management. In this research, we are interested in how hotspot identification can help promote ecological refined management. To achieve this, Chengdu-Chongqing urban agglomeration (CY) was chosen as a case study. First, we employed coefficient of variation and linear regression to analyze ESs temporal and spatial evolution trend from 2000 to 2017. Then, the stable ES hotspots were identified in the time dimension, and the results were superimposed on the dominant function zoning map obtained by a self-organizing feature map (SOFM). Finally, the refined zoning results were obtained, and we added corresponding control measures and policy guidance. The results showed the following: (1) from 2000 to 2017, water conservation (WR) and biodiversity conservation (S_bio) in the study area fluctuated greatly and showed a significant improvement trend on the whole; soil erosion protection (S_pro), carbon sequestration and oxygen production (CSOP) showed a degradation trend in a few areas; (2) the area with at least one kind of ES stable hotspot accounted for 35.22% in the study area, and only 0.8% covered the four kinds of ES hotspots; and (3) the two-level zoning system of CY-refined management was designed. Eighteen cells have been designed within five main functional zones: urban agglomeration zone, modern agricultural development zone, ecological farming zone, ecological transition zone, and core ecological protection zone. Overall, the research based on natural ecological zoning management can provide a decision-making basis for urban planning, policy making, and sustainable development.

Limited transport access contributes to social exclusion, which negatively influences individual health. However, with the rapidly growing aging population, the problems related to public transport accessibility are becoming increasingly prominent. Therefore, understanding the psychological factors related to public transportation use is critical given that this could lead to greater mobility and social inclusion, particularly for older adults who require special attention. This study utilizes an extended Theory of Planned Behavior (TPB) and identifies which psychosocial factors of public transportation use better predict and explain social exclusion. It is unique because it combines perceived ability and social support with the TPB framework to explore the factors that influence social exclusion behavior. Partial least squares structural equation modeling validated a sample of 264 older adults (aged 60 and above) living in selected zones of metropolitan Lahore, Pakistan. The results showed that social norms, attitudes, perceived ability, and social support significantly negatively correlated with social exclusion, whereas perceived behavioral control did not. This study highlights the importance of psychosocial aspects in examining social exclusion and provides recommendations for urban policy makers and transportation planners. The research findings could be equally valuable for developing socially sustainable and healthy urban communities.

Hard-to-access health infrastructure is likely to lead to increased morbidity and mortality. The optimal layout of health facilities is significant for disease control and prevention. This study aims to propose a method to provide equitable access to capacitated preventive health facilities, which captures the key features of the effect of congestion in a competitive choice environment. The problem is formulated as a bilevel nonlinear integer programming model. The upper level is a biobjective programming model subject to investment budget (B) constraint, and the lower level is a user equilibrium analogous model resulting from the users’ choice of facility location. An efficient and operable heuristic algorithm was designed according to the bilevel decision structure where a genetic algorithm (GA) with elite strategy is developed to solve the upper-level problem and the method of successive averages (MSA) is adopted to solve the lower-level problem. A case study is employed to validate the performance of the proposed method. The results show that the method is robust and could reach an equal service quality in a reasonable computation time. However, the sensitivity analysis indicated that the marginal benefit of the investment decreased. There is an optimal B beyond which further increments in investment would not offset the benefits. In addition, the proposed method could be beneficial for other congested public service facilities that users are free to choose from.

The continuous improvement of urban accessibility has had an increasingly prominent impact on the housing market, especially on urban housing prices. In this process, high speed rail (HSR) can play a key role. Based on urban panel data relating to the Yangtze River Delta in China (2010–2018), this paper discusses the direct impact and spatial spillover effect of HSR on urban housing prices, using a spatial econometric model. The results show that improvements in the HSR services not only significantly increased urban housing prices but also had a positive spatial spillover effect. Morover, due to the space–time compression consequence of HSR, the extant “ripple effect” of housing prices has been further strengthened, and improvements in the service frequency of HSR has brought about a stronger spatial spillover effect on housing prices. This study fills a gap in previous spatial perspective research on the impact of HSR on urban housing prices and offers significant theoretical explanations and empirical evidence. Our research provides valuable inputs for the planning and implementing of stratgies aiming to promote urban development and create economic growth through HSR construction.

Rapid urbanization is intensifying land use transitions in China by shrinking cropland and increasing land development, exacerbating land abuse, and causing environmental degradation. There are clear needs to improve land use and address these problems; however, most previous studies focused on either structural or layout optimization. In contrast, this paper proposed a method for comprehensive optimization of land use areas, layout, and structure. This involved coupling multiobjective dynamic planning (MODP), Conversion of Land Use and its Effects at Small regional extent (CLUE-S), and minimal cumulative resistance (MCR) models. In this approach, the MODP model predicted future changes that were based on areas of current land use, and the CLUE-S model simulated various future types that were based on the analysis of geographic land use and economic data. In addition, the MODP and CLUE-S models optimized the amounts and spatial distributions of land use types, respectively. The MCR model could then partition the simulation results for ecological optimization. In this paper, an illustrative application was presented that partitioned Changchun City, Jilin Province, China into construction-prohibited, restricted construction, suitable for construction, and key construction areas (which accounted for 17.41%, 30.24%, 25.32%, and 27.04%, respectively of the total area). The optimization result met expectations and provided potentially valuable reference data for spatial land use planning and ecological protection in the focal region. The proposed method to optimize the ecological layout of land use that was based on multimodel coupling considered operability and objectivity; therefore, facilitating practical applications of the results in Changchun and the presented methodology elsewhere.

Limiting individual transportation and increasing the share of public transportation has an important place in planning a sustainable transportation system in the urban environments of today. The most important goals for city governments include the ability to attract automobile users to public transportation. At this stage, there is a need for a public transportation system that aims to optimize the criteria of cost, safety, organization, and comfort. It is highly important to measure, assess, and improve the satisfaction of those who use public transportation for sustainable transportation. This study used an integrated quality function deployment (QFD) and multichoice goal programming approach to assess the satisfaction of people who use public transportation and to improve the transportation systems quality. The proposed approach was implemented for the tram system that is currently operational in Eskişehir in Turkey. According to the results that were obtained, with a low cost, it was seen that customer priorities could be met to a great extent as 93.1%. The results of the study are helpful for the decision makers to develop incentive policies regarding public transportation systems.

Abstract

Urban governmental environmental attention allocation (UGEAA) is an important issue for sustainable urban development. This study analyzes the spatial characteristics of the UGEAA and its driving factors across 255 Chinese cities from 2009 to 2018. The results show that (1) the UGEAA has spatial clustering and a spatial spillover effect, (2) factors such as governmental administrative distance, neighbors’ UGEAA, public attention to environmental pollution, and economic growth exert influences on the UGEAA, and (3) the driving forces of UGEAA exhibit differentiation for different regions. Text analysis is applied to measure the index of UGEAA. The analysis framework of the drivers of UGEAA is built. It contributes to the political geography theory by study of the spatial characteristics of UGEAA and fills the research gap in urban political geography study. It also contributes to the attention-based theory by expanding the research object to UGEAA. It unearths UGEAA’s driving factors, characteristics, and regional disparities, and proposes policy recommendations.

Practical Applications

Under the spatial interaction, the high-level UGEAA agglomeration area is conducive to the formation of a positive driving mechanism, which promotes the raising of the overall level of the UGEAA in the agglomeration area. Hence, the interaction of UGEAA should be maintained to provide a good policy environment and platform support for improving urban environmental quality. The low-level agglomeration areas of UGEAA should be the focus of management to implement effective external intervention and put in place the necessary leadership policies to reverse their negative dilatory mechanism. In addition, for that obvious spatial correlation exists in different UGEAA, policy-makers should consider setting up a joint action of environmental protection across departments and regions, as well as consider the mechanism of supervision, protection, and accountability with specific powers and responsibilities. UGEAA increases without necessarily resulting in policy formulation or governance action, but steady attention is at least a vital element of ecological environmental governance. Following that, the next focus should be on how to keep the governmental policy-makers’ attention steady and growing on this public issue. Different factors that drive UGEAA should be properly considered in government policies. First, governments should be encouraged to create more public participation platforms to enhance the effectiveness of the bottom-up supervision, especially for western China. Second, some local governments still face difficulties in resolving the dilemmas of “harmonious coexistence” of the economy and the environment in the region they govern. Therefore, it is meaningful to more deeply implement the strategy from extensive development to refined development. Third, governments should also note the adverse effect of GS in the eastern regions, perhaps limiting the GS without impairing its ability. It may be possible, for example, for the government to reduce redundant departments and personnel and increase availability of “internet +” services to increase their service efficiency. For the central regions, attention should also be paid to the significant impact of industrialization. The negative environmental effects caused by the industrial transfer from eastern regions to central regions have attracted the attention of governments. As a next step, the central government should assist the central region to perform well in the renewal of industrial equipment, and in the innovation and transformation of technological processes, in the upgrading of industry, and so on, to achieve a green transformation. Finally, the shortage of financial resources is still the main reason that governments cannot pay attention to the environment, due primarily to the economic development in the western regions. The central government has an urgent task of guiding the western regions out of the “poverty trap” and moving them from left to right along the environmental Kuznets curve.

With the changing paradigm of the State’s functions and the increasing private sector participation in urban planning, public–private partnership (PPP) arrangements gain prominence in the development of cities, whether in the construction and operation of new infrastructures or in interventions in urbanized areas. Regarding urbanized areas, urban regeneration practices constitute an important response in the face of urban degradation observed in different cities, as well as an alternative to the consumption of new land. Despite their use in different contexts, the PPP option in urban regeneration projects encounters many obstacles related to high investment risk, low financial and social return, and the numerous sources of uncertainty generated by these projects. The present work consists of a systematic literature review of papers on PPP in urban regeneration projects, seeking to identify the main research topics addressed so far and what gaps can be identified. It uses a hybrid methodology considering a systematic quantitative review, a semantic analysis, and a narrative analysis. The findings show that the literature on the topic is recent and has been increasing in recent years, with emphasis on Europe, followed by North America and Asia. The literature presents a high variety in terms of journals, authors, and institutions. As for the methodology adopted in the articles, it highlights the use of quantitative methodologies. Five main topics were found: policy, projects, governance, financial and economic issues, and management and contract issues. The topics found show the complexity of PPPs in urban regeneration projects. The gaps observed refer mainly to financial and economic issues, as well as management and contract issues.

Sustainable buildings can save 36% of total energy use, 65% of electricity consumption, 30% of greenhouse gas emissions, 30% of raw materials use, 30% of waste output, and 12% of potable water consumption. Several sustainable building assessment tools were used by both developed and developing countries. However, Ethiopia’s buildings were not critically assessed and evaluated from a sustainability point of view because there was no such type of study conducted so far. This paper aims to explore the most significant and widely used tools as well as the basis for other sustainable building assessment tools, such as Building Research Establishment Environmental Assessment Methodology (BREEAM), Leadership in Energy and Environmental Design (LEED), Comprehensive Assessment System for Built Environment Efficiency (CASBEE), Sustainable Building Tool (SBTool), Comprehensive Environmental Performance Assessment Scheme (CEPAS), Deutsche Gesellschaft für Nachhaltiges Bauen (DGNB), and Green Mark and Green Star. The methodology employed is the selection of the 10 most commonly and widely utilized sustainable building assessment tools (SBATs) from the 57 SBATs based on desk review and document analysis. The results of the study identified that all 10 SBATs have their own assessment categories and criteria based on many factors, such as climatic conditions and availability of resources, plus methods employing demographic dynamics and legal aspects of the sector for assessing the sustainable/green buildings. It distinguishes the most commonly and repeatedly used assessment categories and criteria and uses a consensus-based approach with experts in the building sectors, a four-quadrant model, and a circular and helical flow model, to develop a new sustainable building assessment tool suitable for Ethiopia.

Rapid urbanization has brought along with it many environmental and social problems such as ecosystem damage and traffic congestion. Therefore, forecasting the trend of urban expansion and providing a reasonable urban planning basis for government departments have become the focus of researchers. An artificial neural network (ANN) can be used to consider spatial nonstationarity when obtaining the changing characteristics of urban land types. Therefore, in this study, we use cellular automata (CA) based on ANN (ANN-CA) to simulate and forecast urban expansion and discuss the parameter sensitivity of the model in detail. In addition, we propose a new Urban Expansion Early Warning Indicator system to warn about the deterioration of future land distribution patterns. Chengdu is selected as the study area, and the study period is from 2000 to 2020. The results showed the following: (1) The best accuracy was achieved when the neighborhood size is 7 × 7 and the number of model iterations is 250, and overall accuracy (OA), Kappa coefficient, and figure of merit (FOM) are 91.47%, 0.855, and 0.354, respectively; (2) ANN-CA is more suitable for predicting the urban expansion of Chengdu than CA based on logistic regression (LR-CA) and CA based on decision tree (DT-CA). Compared with the worst performance model, the score of OA increased by 6.23%, that of kappa increased by 0.062, and that of FOM increased by 0.056. (3) According to the current development trend, artificial built-up areas will increase substantially. The comprehensive evaluation results of the morphology effect, ecological effect, and intensity effect of urban expansion predict severe early warning for Jinniu District, Qingyang District, and Wuhou District by 2030.

During the past decade, the rapid construction of rail transit in developing countries has had a great impact on bus transport, resulting in the waste of public transport resources and ineffective competition between bus and rail transit. Therefore, it is particularly important to explore ways to promote the integrated development of bus and rail transit by combining both the effects of the built environment and their competition. Using Wuhan city in China as a case study, this study develops gradient boosting decision trees (GBDTs) to examine the quantified threshold range of the built environment impacts on bus transit trip rates and to further explore the competitive impacts of rail transit on bus transit within these threshold ranges. The threshold range results show that when the number of service point of interests (POIs) within a 500-m radius of the bus stop reaches 350 and the distance to the destination is 5 km, the model split of bus transit is the highest. The competition impact analysis shows that rail transit promotes bus transit trip rates in urban fringe areas and locations, including a high proportion of 3- to 5-km middle-distance trips, but restricts bus transit trip rates in high-density central areas and the regions dominated by short-distance trips of less than 3 km or long-distance trips of more than 5 km. Strategies are proposed to optimize land use and the layout of bus and rail transit stations to mitigate ineffective competition and improve the efficiency of public transit to provide theoretical and technical support for optimizing urban spatial layouts through transit-oriented development.

Science and technology and skills have increasingly become the driving force to lead the development of knowledge economy. With the changes in the demand for knowledge workers and the location of enterprises, a new type of innovation space—innovation districts—has emerged. Countries have begun to identify and nurture innovation districts. Therefore, how to accurately identify innovation districts in cities has become an important research topic. The existing research on identifying innovation districts is mainly based on a qualitative description method at the element level. However, whether there are other potential innovation districts in urban space can be identified by quantitative identification. Therefore, the purpose of this paper is to establish an innovation district identification framework and a case study of the framework. The identification framework includes spatial identification and factor identification. In spatial identification, the identification index system is constructed based on the spatial location, range limit, and the surrounding area of innovative assets. In factor identification, the identification index system is constructed based on innovative assets, physical assets, and network assets, and Kendall Square and Boston innovation districts are used as the reference basis to determine whether the identified districts meet the standards of the constructed innovation districts. In empirical case research, spatial identification identified the Gaoxin South District (GXSD) spatial range. In factor identification, it was found that GXSD does not fully meet the standard of innovation district identification. This paper argues that the framework is essential for urban managers, planners, and urban designers to identify and evaluate high-quality innovation districts.

Land systems are those that most closely interact with human beings in terms of natural resources. The relationship between the simulation of their dynamic evolution and their microscopic and macroscopic elements is complex and nonlinear. In this study, we aimed to design a scientific model that could unify the macroscopic statistical distribution with microscopic individual movements, in order to simplify the model structure and definition of transformation rules. Taking Yucheng District, City, China, as a study site, we constructed an artificial neural network cellular automata (ANN-CA) model that uses neural network algorithms to predict the land area required to restrict the number of cellular automat (CA) space simulations. First, we took the raster data of the current land-use map of Yucheng District for the years 2001 and 2009, and the effect coefficients of slope, the river system, and other elements were used as initial data for the ANN-CA model. We then analyzed the superimposed land-use evolution law from 2001 to 2009. Next, within the error limits of the results for the 2017 neural network area prediction and the space center of gravity for each land type, we predicted the land-use changes for 2017 and determined the final land type for all grid units based on the set evolution rules and land conversion threshold. Finally, the land-use prediction simulation map for 2017 and actual land-use conditions were verified for quantitative and spatial accuracy. The results reveal that the model simulated the land-use changes for Yucheng District relatively accurately. It was also found that selecting the appropriate thresholds and random variable parameters improved the model’s simulation accuracy and that the land use in the study area exhibits a clear urbanization trend.

The ratio of green areas belonging to residential areas and their location in the city is too important to ignore. However, when we look at urban planning, it is seen that green areas belonging to common public areas are generally evaluated within the scope of ecosystem services, while residential gardens that are within the scope of private property are ignored. In this context, the main purpose of the study is to examine the contribution of the residential gardens, in which the landscape value is kept to the forefront, to the ecosystem services. Within the scope of this main purpose, this study analyzes how the green areas of the residential gardens in Trabzon can be designed through a focus on green infrastructure (GI) within the axis of landscape value and how these designs will serve the ecosystem services in this perspective. Following the study, it has been determined that both spatial needs and ecosystem benefits can be met with the same GI elements, while, on the other hand, it has been conferred that the landscape value, as a significant factor in the design of residential gardens, is supported by several GI elements of an edible garden, pollinator garden, rain garden, biological pond, and green roof. It has been determined that GI elements, where vegetation and water landscape elements are used together, have a higher potential for ecosystem services. In addition, it has been concluded that the green areas of the residential gardens should not be planned and designed solely within their own areas. Based on these analyses, it has been determined that the benefits are considerably increased when the green areas of the residential gardens are planned and designed through a holistic GI-oriented design approach based on the total building parcel. Thus, it is very important to consider GI systems with a holistic approach in residential gardens throughout the city. This holistic approach will allow the benefits of GI to be spread throughout the city and will ensure that the benefits are homogenized within the city.

Abstract

As an important part of urban livable environment construction, urban streets are of great significance for daily social interaction and urban vitality. Enhancing walkability is considered an effective design measure to connect places and promote physical health. Compared with previous studies that focused on spatial physical characteristics or transportation infrastructure (such as zebra crossings) of streets, this study aims to identify and analyze walkability indicators that are closely related to subjective perception at the microscale. A questionnaire survey was conducted face to face to collect pedestrians’ perception of walkability indicators, and an exploratory factor analysis was used to extract the main influencing factors. Structural equation models were constructed to verify the stability of the dominating factors and further explore the disparities in different walking intentions and different gender groups. According to the results, Access Safety, Stop Friendliness, and Visual Richness have a great impact on walkability, and women generally have a stronger perception of traffic disturbance and traffic safety than men. Ultimately, based on the results, some useful strategies are proposed for future street renewal. However, the study is limited to the geographical scope of Shinan District of Qingdao. Therefore, the longitudinal comparative analysis of other urban areas of Qingdao or intercity comparative analysis can be carried out in the future so as to provide extensive improvement recommendations.

Practical Applications

Walking is a choice. In order to create an environment that encourages people to walk more, we need to understand how environmental factors affect people’s travel choice. In the context of ultrahigh-density Asian cities in particular, this paper is a scientific attempt to explore the relationship between walkability indicators to guide the construction of a livable neighborhood environment under the concept of Park City. The research results can be used as the basis for urban planning and managers to carry out urban renewal construction. Informed decisions in favor of a walkable environment will be made at a certain cost.

Abstract

An increasing number of disasters across the globe have prompted the creation of strategies for disaster risk reduction and resilience to save lives and property in line with the 2030 Agenda for Sustainable Development and the New Urban Agenda (NUA). The 2030 Agenda calls for all development planning to simultaneously tackle disaster risk reduction and inclusiveness. This paper aims to remold urban planning for upcoming new towns in developing countries so that planners can be able to include indigenous knowledge systems in urban planning. The study was conducted in a new town, Gokwe, Zimbabwe, with a population of 8,118 from which a sample size of 229 was drawn using Cochran’s sample size determination formula and the 30% rule. A mixed-methods analytic case study was conducted to evaluate the potential of the town’s planning processes in preventing natural and human-induced disasters. The study used questionnaires, semistructured interviews, desktop sources, focus group discussions, and remote sensing. It analyzed the strategies, scope, and relevance of Gokwe town disaster risk-reduction strategies and their integration into town planning and development using six wards, from 1992 to 2020. The Urban Disaster Reduction Index (UDRI) model was applied based on the Sendai Framework for Disaster Risk Reduction indicators to measure the extent to which the town council’s development planning can help to reduce disaster and foster sustainable development. The UDRI was calculated for the four Sendai Framework priority areas and proved that the council’s disaster management is weak. The chief cause was found to be the town’s development control regulations and the national urban councils act that excludes contributions from local communities and leadership, placing new town planning in the hands of bureaucrats, technicians, and politicians only. It was concluded that for disaster management to improve requires local DRR and national urban development policies reformulation.

Practical Applications

This research exposed that the practice and scholarship of urban planning in most low-income countries such as Zimbabwe must be changed from mere physical design to a holistic process approach of community building. There is need to redefine sustainable development as a dynamic and continuous approach that brings together physical considerations, societal values, and technology in crafting solutions for urban development challenges. Environmentalists, planners, policymakers, engineers, economists, and society at large must combine forces to bring about the most sought-after urban sustainability that ensures environmental protection, spatial coordination, and economic and social development for the present and future generations. The paper calls for adoption of a dynamic multidisciplinary and cyclic rather than the current static and unidirectional planning advanced by traditional urban planning theories, such as the rational–comprehensive, incremental, and the transactive theories. Urban planning should not be viewed as a technical, empirical, and scientific activity that does not require any input from ordinary citizens. Planning processes should afford the public an active role, not only in planning but right from policy setting, planning, development, and management of the established town. Town development should be a mutual process in which leaders gather more information from the community and for the community.

In the era of globalization and informatization, urban development patterns need to be generated with the network structure between cities taken into account. The urban network constructed based on enterprise connections has recently garnered substantial research interest. However, most of the research efforts have been channeled toward constructing urban networks via the relationship between headquarters and branches within enterprises, with little attention paid to urban networks through the lens of financial connections between enterprises. In this study, the cross-regional investment data of enterprises are used to establish an urban network, revealing its spatial distribution and evolutionary dynamics. The main conclusions are as follows. First, corporate investment behavior somewhat fuels the structure and direction of the urban network. The correlation degree of the network is significantly enhanced, and the network relationship has an apparent economic focus, resource focus, and path dependence characteristics. Spatial connections show the dual characteristics of large-scale preferential connections (outside the region) and small- and medium-scale adjacent connections (inside the region). Second, from 2006 to 2016, cross-regional investment was further concentrated in core cities and hotspot cities, and the flow of funds between regions also changed from being within-region to primarily being inter-regional. However, the dominant role of traditional core cities or hotspot cities such as Shanghai, Shenzhen, Guangzhou, Hangzhou, and Ningbo are apparent, resulting in a network structure in line with a core–periphery model. Finally, compared with other dimensions of urban networks, in addition to the effective play of the investment function of the core cities or the hotspot cities, some small- and medium-sized cities with rich resources also play an important connecting role in the network. These research results provide a decision-making basis for urban spatial structure, functional integration, and collaborative planning; furthermore, they promote the research on urban networks based on actual economic activities among enterprises.

Abstract

The development of cities as products of human society is in line with cyclical law. This study applies the system dynamics model to construct a city development model for Beijing, China’s capital city, and analyzes the simulation results from an ecological perspective. The results suggest that Beijing is still in the process of transitioning from fast development to maturity. This trend will continue until the mid-2030s, and this transition process will be composed of several periods. The motivation for development in each period is different. The industry will be the main driving force in the foreseeable future, and the lifespan of each period is approximately 10 years. Major events such as the Olympic Games are the key to evolution. Therefore, Beijing should exploit each event as booster for growth in the next period.

Practical Applications

Beijing is the capital city of China. Based on our research, the city is in its maturity stage and facing metropolitan issues. In China, an urban plan text contains four parts: guiding ideology, development goal, key task, and implementation path. The findings of this research should make substantial contributions to the second and third parts. We have demonstrated that Beijing is transitioning from fast development to maturity in a cyclic curve. The key motivation for city evolution is industry. Big events such as the Olympic Games are key turning points, and these two findings steer goal-making in the planning process. Moreover, this study also highlighted the tendency of urban production, living, and environment in Beijing to contribute to key task selection.

Cities around the world are piloting projects to evaluate the feasibility and benefits of shared autonomous vehicles (SAVs), as their large-scale implementation and integration into public transit systems have the potential to improve individuals’ accessibility and transportation equity. To understand the full potential of SAVs and their likely adoption, it is important to identify how the services can be utilized most effectively and what determines the composition of the ridership. This research aims to explore the usage and adoption of SAVs, focusing on a project called RAPID (Rideshare, Automation, and Payment Integration Demonstration) that was launched in Arlington, Texas. We used real-time trip-level ridership data from the SAV platform, conducted a survey of SAV riders, and developed a study based on ordered logistic regression to estimate the determinants of ridership frequency. Data analysis of real-time ridership data revealed that spatial distribution of activities and service accessibility have crucial roles in forming the current users’ travel patterns. The findings from the logistic regression demonstrated that those with higher household incomes are less likely to be frequent riders of RAPID, while those who usually walk, bike, or utilize on-demand ridesharing services are likely to use SAVs often. Users with higher levels of safety perception are also more likely to be frequent users of the service. The findings of this study will provide planners with a better understanding of SAV ridership patterns and will guide decision-makers nationwide in establishing and adopting policies that will be appropriate for future SAV implementation projects.

An increasing number of housing clusters have emerged because of the reconstitution of Turkish metropolitan municipalities, supported by the arrangements made in land development plans. Turkish metropolitans are determined by the administrative borders, while the world metropolitans are determined by their functional urban areas. Here, we aimed to evaluate the clustering capacity of metropolitan municipalities by focusing on the distribution of the residential occupation permits. Exploratory spatial data analysis was used to determine the core provinces of housing. The Moran Index was used to investigate the increase of clusters and this was cross-checked with the Spatial Lag results. We improved the recent land-use changes from rural plots to urban service parcels over the presence of the land development plans, including the transactions. Across the limited period studied, grifted patterns appeared. Clustering provinces enhanced the detection of construction that boosted urban development. Furthermore, a meshwork was revealed. In most developing countries, finding diverse and not tempered data sets in official sources is still a big problem. Moreover, open-data sources were limited in this study. In the search to prove uncontrolled urban growth fueled by construction activities, our research established an alternative way to read the metropolitan area network using occupancy permits, where the lack of data cannot be compensated.

The market-oriented real estate development model has occupied a leading position in the urban renewal activities in Shenzhen and the regeneration of the old city has shown serious stagnation under the intertwined interests of multiple subjects. This study took the Mutoulong Community (Shenzhen, China), Luohu District as an example to resolve and analyze the project promotion process and explore the core problems of the old city regeneration in Shenzhen. The results showed that the internal contradictions and conflicts between the owners of different factions were the core problem of stagnation in the old city regeneration. In addition, from the case study on the application of a third-party professional force in Hubei New Village (Shenzhen, China), Shenzhen and the project that funded the building in Macao Special Administrative Region (SAR), the results show that the third-party professional forces are professional, nonprofit, and prioritized public interests, which could effectively balance the cognitive differences between the owners of different factions in the planning policy, design scheme, and implementation, which helped to build trust between the owners and other subjects. In addition, the third-party professional forces with a resident composition will help to resolve the complex ownership relationships and effectively promote the development of the old city regeneration projects.

With the increase in the number of ride-hailing, traffic congestion and environmental pollution have been exacerbated. A new ride-hailing policy was formed as a means of administrative control to reduce the negative externalities. However, the improvement in air quality caused by the new ride-hailing policy has not been effectively verified. This study employed regression discontinuity design (RDD) to explore the causal relationship between the air quality in Beijing and the new ride-hailing policy to reduce the endogeneity problems. The main results show that the implementation of the new policy reduces air quality index (AQI), particulate matter 10 (PM₁₀), and ozone (O₃) by 14%, 12%, and 16%, respectively, in the ordinary least squares (OLS) regression analysis. After applying the RDD, this study finds that the implementation of the new policy reduces AQI, PM₁₀, and O₃ by 43%, 30%, and 42%, respectively. The regression value of RDD is higher than that of OLS regression. Additionally, the robustness test reveals that RDD is reasonable. The findings suggest that the implementation of the new ride-hailing policy exerts an improvement effect on air quality. Policy implications to further promote the new ride-hailing policy are hence discussed.

Sustainable rural planning is a continuous, multiparticipatory, large-scale process. Most rural areas in developing countries have sustainable characteristics. However, rural areas have been neglected due to the excessive focus on urban areas, resulting in an urban–rural gap that is difficult to overcome. Village planning is an important public policy instrument that is used to direct land-use planning and management. Therefore, it is an important tool for realizing sustainable development in rural areas. Based on the problems experienced by these villages and the goal of sustainable rural development, the study took An Nijād village, Yemen, as a case study. The study used a hybrid design approach, including qualitative and quantitative methods, such as questionnaire analysis along with GIS methods, and strengths, weaknesses, opportunities, and threats (SWOT). The research cycle was implemented in various phases, including data collection, coding, and analysis. The results of the change matrix (2010–2020) have indicated that land use/land covers (LULC) classified were arable land (47.9%), Built-up area (11.5%), barren/bare land (8.3%), water body (0.3%), slop land (6.4%), mountains (22.1%), and roads (3.5%). This paper will create a comprehensive framework for the implementation and planning of rural areas at the regional level, considering the constraints of each region in terms of its ability to achieve realistic results on the planning and development of sustainable rural development strategies.

In the wake of China’s rapid urbanization and higher education reform, a large number of new urban spaces have emerged, in particular, university towns. When promoting urbanization and stimulating economic growth, the isolation of the university town from the central city has become increasingly apparent. This article defined the islandization of the university town and analyzed it from the perspective of the behavior of the main actors of the university town, the students. Taking Jinan Changqing University Town, Jinan City, China as a case study, this article used a survey questionnaire and interviews to investigate the patterns of university town students' off-campus behavior. By constructing an analysis framework, this article discussed the characterization, influencing factors, and formation mechanism of the islandization of the university town. The results indicated that although the daily behavior of students was concentrated mainly in the university town, the student's needs could not be fully satisfied in the university town alone. Therefore, students needed to go to the central area of Jinan City, China for important activities, which included studying, working part-time jobs, shopping, recreation, and medical treatment. The main mode of transportation for the students that left the university town was public transport, which was considered inconvenient and costly in terms of time. Student behavioral characteristics indicated that the university town was spatially separated from society, which is a significant feature of islandization. The imperfection in the spatial factors was the basis of the islandization of the university town, which further triggered the behavior and psychological isolation of the students. In addition, spatial, student behavior, and psychological factors interacted and reinforced each other, which eventually formed a vicious circle and led to the increased isolation of the university town.