Journal of Urban Planning and Development

Where urban planning is used to promote environmental sustainability, it has traditionally focused on reducing emissions from housing and traffic. However, cities are increasingly being recognized as consumption centers of the global economy, as the origin of demand, and as the point of termination for complex economic supply chains. Based on results produced by a hybrid life-cycle assessment model, which attributed the end-to-end emissions of supply chains to end users, consumption that is not related to housing or ground transportation was found to account for 30% of regional greenhouse gas emissions on average. In highly urbanized areas, the figure was even higher, at 45%. Furthermore, a literature review indicated that most environmental assessment tools for local city-level and subcity-level urban planning are neither able to identify the environmental impacts of personal consumption nor the relationships between urban structures and personal consumption. Thus, this study concludes that there is an apparent gap between the needs and the means of the regional environmental management of urban areas.

Human population distribution represents critical information used for urban planning, sustainable development, and human–environment interaction studies. A number of models for the mapping of population distribution have been developed at different scales (e.g., global, regional, and urban), but their respective performance may not be satisfactory for all applications, and methods that provide high accuracy at the scale of a built-up urban area are still rare for cities in developing world. This paper proposes a new method known as the modified inverse distance weighted model (M_IDW) for disaggregation of the population in a built-up urban area using only the geometrical information from ground-level houses as ancillary information. In particular, the method considers the population distribution in the target area as synthesized and mosaicked with a homogeneous density of houses and their associated land patches in addition to an inhomogeneous density for the outdoor areas. The authors chose the built-up area of Shanghai as the case study area, and geographic information system and remote sensing images processing software were used to derive the ancillary information. Subsequently, an interpolation routine was developed using the interface definition language (IDL) 8.0, and the resulting performance of the new method was compared against that of two other approaches. The results indicate that: (1) the proposed M_IDW is able to represent a detailed distribution of information from a population in a built-up urban area and yields good performance when applied to a single-type auxiliary data; (2) the traditional inverse distance weighted model interpolation (T_IDW) cannot be directly applied for population interpolation at the scale of a built-up urban area; (3) the inverse of the national population aggregation (INPA) method and the M_IDW interpolation can obtain detailed spatial information from a population distribution on a highly refined grid scale, and both methods produce a considerable and equivalent accuracy; however, the M_IDW has a greater ability to depict the details of the population distribution than the INPA. This novel method can substantially improve the disaggregation accuracy and spatial details that are important in this context.

The population and economic activities encompassed by megaregions are ever expanding. As this occurs, investments are often recommended to ensure the regions are globally competitive from an economic standpoint. However, although such investment may accelerate growth in megaregions, that growth may have an uneven impact on the national economy. To date there has been very little empirical research on the relationship between the internal growth characteristics of megaregions and their effects on surrounding areas and the national economy. This paper examines the growth of megaregions within the context of regional convergence and divergence theory. U.S. counties are reorganized by megaregion to compare the inequality of counties and the extent to convergence in each megaregion. In particular, it uses the Theil index and conditional $\beta$ convergence for measuring the relationship between growth, inequality, mobility, and social welfare. The results show a process of conditional $\beta$ convergence at the national level but divergence among some megaregions. The core areas of megaregions, their socioeconomic characteristics, and their transportation infrastructure are identified as major forces of regional growth.

Partitioning development sites into gridded networks for slope/gradient analysis is one of the most important steps for housing development on hillsides. In concept, different housing development alternatives can be created by fusing various gridded networks and slope calculation methods. This study proposes a grid-geometry sampling technique (${\mathrm{G}}^2\mathrm{ST}$) and an optimal model of housing development (OMHD) as an assistant tool for solving the problem of housing development on hillsides. Applying the ${\mathrm{G}}^2\mathrm{ST}$, enormous gridded networks can be generated by altering the origin shift and axis rotation. Each gridded network represents a feasible alternative of the OMHD. Based on slope analysis, the OMHD has two objectives: the area of permitted housing development (APHD) and the floor area of housing unit (FAHU). By calculating the objective value of all gridded networks for a housing development side, the optimal alternatives can be identified from the gridded networks. Results obtained in experiments using field-survey contours show that the APHD and FAHU are dependent not only the gridded network, but also the slope calculation method. With the aid of the ${\mathrm{G}}^2\mathrm{ST}$ and OMHD, governments and developers can easily and quickly obtain diverse gridded networks and slope analysis results for hillside development applications, despite the fact that the generation of gridded networks is highly complex and difficult to solve manually. Integrating the ${\mathrm{G}}^2\mathrm{ST}$ and OMHD enables identifying approximately optimal alternatives and provides diverse alternatives and flexible ways to review the problem of housing development on hillsides. If authorities want to mitigate the effect of disasters for housing development on hillsides, they can adopt the minimum APHD or OMHD alternatives as the basis for housing development. Because of the efficient and diverse characteristics, the ${\mathrm{G}}^2\mathrm{ST}$ is applicable to any analysis based on gridded networks, including terrain analysis, flow routing analysis, and the analysis of landscape metrics.

Urban growth can present distinct geometric forms, the patterns and determinants of which remain little understood. The aim of this study is to explore the spatial patterns of different urban growth forms (UGFs) in relation to roads and pregrowth urban areas (PUAs) in the Nanjing metropolitan region of China. Three basic UGFs—infilling, edge-expansion, and spontaneous growth—were distinguished using a topological quantitativecriterion. Results from the UGF composition showed the growth of Nanjing City, China, tended to be less compact during the accelerated urbanization. The three UGFs generally showed exponential attenuation with increasing distance to roads and PUAs, while spontaneous form showed a lognormal relationship with PUAs. Results from the logistic regression suggested that PUAs had a stronger tendency to attract infilling and edge-expansion growth than roads, whereas roads were a stronger attractor of spontaneous growth. Overall, this study can provide better understandings on the evolution of urban morphology at the landscape scale as well as useful implications for urban planning.An alert of exacerbated urban sprawl in Nanjing, China, was raised and the importance of road planning in the effort to control sprawl was highlighted.

The energy efficiency of urban infrastructure is in large part influenced by the efficient utilization of transportation and building systems. Opportunities for more efficient utilization of transportation and building systems are available in the context of commercial office building/site selection. Office location decision makers have an opportunity to select buildings and locations that potentially minimize building and transportation energy consumption within a given urban context. The objective of the research presented in this paper was to apply a calculation framework for estimating the potential transportation energy and building energy consumption of commercial office building/site alternatives. The calculation framework was applied to case studies of commercial office buildings/sites that represent typical developments found in the transportation and land-use context of the Atlanta, Georgia, metropolitan region. The framework leverages building energy simulation models and regional travel demand model data to estimate energy performance under uncertainty. Importantly, the calculation results indicate that transportation is a major determinant of commercial office building/site energy performance. Incorporation of the framework into sustainable development policy or market transformation tools (e.g., green building rating systems) could accommodate more performance-based planning of efficient infrastructure utilization.

Recent debates in urban planning have centered on whether the cul-de-sac street form should be eliminated from the United States’ topography. Critics argue that these closed-off streets force residents into their automobiles, reduce communal interaction, are difficult for emergency vehicles to traverse, and are not environmentally friendly. Developers, realtors, and homebuyers, on the other hand, clamor for these streets, which are private, quiet, and safe for raising children. Lacking from debates over the future of the cul-de-sac are systematic analyses assessing the social consequences of living on these streets. This study utilized a quasi-experimental design to assess differences in residential social cohesion for residents of “bulb” cul-de-sacs, “dead-end” cul-de-sacs, and through streets. My data reveal that bulb residents experience the highest levels of attitudinal and behavioral cohesion, followed by dead-ends, then through streets. With planning debates about the future of the cul-de-sac currently taking place across the country, this study provides timely insight into the relationship between street design and neighborly bonds.

Land use and land use change have been proven to be leading causes of local climate change. In cities that undergo rapid urbanization, the urban heat island (UHI) can generate serious problems for the urban living environment. An appropriate overall land use plan can mitigate the detrimental effects of an UHI because it can reduce its development. However, land use decisions are driven by social and economic factors that cannot be made on the basis of moderating an UHI alone. To make a sound land use plan for Shenzhen in 2020, a rapidly urbanizing city in China suffering from UHI due to its fast land development, a genetic algorithm-based multiobjective optimization (MOO) approach was develped that addresses the objectives for future land use. The MOO provides a set of Pareto solutions and then the decision maker or planner can choose from the set of solutions. Recognizing the definite development of certain nonurban land for the local economy, three objectives were considered: (1) minimizing the increase of surface temperature, (2) minimizing the incompatibility between land uses, and (3) minimizing the cost of land use changes from the status quo. To quantify the effects of land use patterns on the UHI in Shenzhen, a self-organizing maps (SOM) method and linear regression model were used to establish the interactive relation. The relation thus obtained was then used in the MOO to help evaluate the effects of alternative land use patterns on the development of the UHI. Four scenarios were examined. The first scenario took all three objectives into account, and one optimal plan was selected randomly from the Pareto set as the first scenario, whereas the other three scenarios considered one objective each. Results showed that MOO can make tradeoffs among the conflicting objectives, indicating that the optimized land use plans can minimize the increasing UHI effects and at the same time attempt to achieve other objectives in the process of land development.

Zoning regulations are largely represented by land use, the floor area ratio (FAR), and building coverage ratio (BCR). Changes in the FAR and BCR directly affect the formation of urban space, making it likely that volumes of building space will be regulated. Volume regulation becomes a significant factor influencing the planning of urban space. Also, it is currently being utilized as one of the most powerful means of regulating zoning, which also affects the formation of urban space. This paper analyzes the characteristics of volume regulation and how volume regulation and changes in regulations, are influencing urban space in terms of a unit of land, suggesting several ways for government to use volume regulation as a means of spatial management. To do this, this study uses a vector autoregressive (VAR) model to analyze the effect of volume regulations on urban spatial factors in residential and commercial areas. The fields to be studied are the Seoul area and five individual life zones. The results show that the impacts are differentiated in an each individual zone. Intensity of regulation and degree of influence, used to represent urban density indicators, are found to be oversimplified, necessitating a conceptualization of the classification of volume regulation and use. In addition, the FAR, which is a useful means of controlling urban space, more strongly affects volume.

Urban construction land-use expansion is an important topic in the field of land-use change research. In the present study, the temporal and spatial changes of urban construction land use in the Chongqing urban area are analyzed, based on land-use maps from 1975, 1987, 1995, 2000, and 2010. Using gradient analysis, the study area was divided into nine buffer zones and eight quadrants. The study analyzed the compactness of the urban construction land in different buffer ranges and different directions, and further fitted the compactness degrees and different gradients. The results indicated that there was a rapid growth of urban construction land use in the Chongqing urban area in the period of 2000–2010, and the land use for urban construction sharply increased at an average annual rate of 5.69%. The expansion pattern showed a spatial mode of one center and multiple subcenters. Furthermore, although the key regions (the fastest-growing regions of urban construction land) of urban expansion showed higher compactness degree than the nonkey regions (the slowest-growing regions of urban construction land) of urban expansion, the compactness degrees were decreasing in the key regions but increasing in the nonkey regions. Specifically, the urban construction land had three highly compact zones in the buffer radius gradient—zones of radius 5, 25, and 40 km—and the compactness degrees gradually increased. When analyzed by the quadrant gradient of buffers, quadrants 45–90° (WNW), 90–135° (WSW), and 315–360° (NNE) were the key regions of urban expansion, and quadrants 225–270° (ESE) and 270–315° (ENE) were the nonkey regions. In addition, the change in compactness degree was highly correlated with changes in the buffer radius and quadrant azimuth.