Journal of Urban Planning and Development

Brownfields are potential development opportunities for the communities in which these old industrial sites sit. The Western Pennsylvania Brownfields Center at Carnegie Mellon University has developed and tested a multiattribute decision-making process for complex brownfield development selection. Local community organizers (in this case, Main and Elm Street managers) collected data on site attributes related to environmental conditions, demographics, development potential, infrastructure conditions, and market realities. Concurrently, decision makers [in this case, the Board of Directors of Keystone Community Oriented Real Estate (CORE) Services (KCS), a subsidiary of the Pennsylvania Downtown Center, with a mission to promote real estate development in Main and Elm Street neighborhoods and business districts] weighted the attributes consistent with their priorities and the availability of resources. Then, weights are applied to the attributes collected by the community organizers to estimate a total score for each property of interest. The result is a ranking of properties that can be used to guide investment decisions or public funding. This paper describes the process used and provides a guide for application elsewhere.

Land use (LU) information is of significant value for various urban studies and is needed for a wide variety of decision-making initiatives in the range of global, regional, and urban areas. However, it has been difficult to collect LU information in an efficient and cost-effective way in the past, which forces planners and engineers to use other information (e.g., population and employment) as proxy in their modeling practice. This paper intends to establish a hybrid geographic information and remote sensing (GI/RS) expert system to extract LU at a very detailed subzonal level. Three LU classification algorithms including fuzzy-decision tree (FDT), logistic-decision tree (LDT), and artificial neural network (ANN) are designed to classify urban subzones, dissemination blocks (DBs), the smallest census zone, into single LUs using very high resolution (VHR) aerial imagery and geographic vector data. A novel, hybrid pixel- and object-based land-cover classification system is developed to extract the information of parking lot, bare soil, and vegetation from aerial imagery. Morphological properties at the zonal level are derived from the geographic data and the land-cover classification results. Statistical analyses, such as scatter graph and nonparametric Kruskal-Wallis test, are used to examine the separability of each pair LUs with respect to the derived DB properties. Selected morphological properties are then used as either independent or input variables of the designed FDT, LDT, and ANN classification algorithms. FDT and LDT are used in a five-level decision tree system and ANN is used directly for LU recognition. The performances of the three designed classification systems are then compared through accuracy assessments; the logistic-decision tree has the best performance with an overall accuracy of 97.05%. In addition, spatial arrangement analysis is used to study the interrelationships of buildings within zones (DB) based on nearest neighbor and Gabriel graph analysis, which show a significant potential of extracting different LUs from mixed-LU zones.

The decades of economic boom have brought about intensive spatial transformation and restructuring since market-oriented reforms in China. Such spatial adjustments have generated the manifestation of spatial mismatch in Chinese large cities. The writers, taking Shanghai for example, aim to investigate the mechanisms contributing to spatial mismatch in the transitional period of Chinese cities. It finds that the mechanisms are generalized as follows: (1) urban regeneration, village requisition, and affordable housing programs resettle a large number of socially disadvantaged people into urban fringes; (2) transaction restrictions, housing resources shortages, unavailability of housing finance, and unaffordable moving costs make disadvantaged people less able to move closer to employment centers in inner cities; and (3) insufficient transport services in urban fringes aggravate the geographical disconnection of disadvantaged people with employment centers.

A mileage-based toll scheme will soon be adopted by Taiwan’s freeway system to replace the current toll station–based model. This new policy will increase the travel cost to some short-range drivers, and they may therefore choose to switch to alternate routes, depending on their perception of the equity and acceptability of the new toll scheme. This study attempts to utilize structural equations and the discrete-choice model to analyze the perceived attitudes of highway drivers toward the mileage-based toll scheme, as well as the effects of the perceived attitudes on route choice behaviors. The results show that perceived equity as well as perceived effectiveness and efficiency have positive effects on the acceptability of toll schemes and the utility to highway users, while switching barriers have negative effects on the utility to highway drivers. In addition, we have established a binary Logit model that incorporates perceived latent variables, the results of which show that a switching behavior model that has included perceived latent variables contributes a more reasonable explanation of the actual decision-making behaviors of drivers and enhances the explanatory capability of the model. Finally, the analysis of the route choice model reveals that when the trip mileage of short-range drivers increases to 30 km or above, all the perceived latent variables do not appear to have any impact on their decision of route choice. Although drivers who decide to remain on the freeway will be required to pay the toll, they will also be compensated with improved driving speeds on the freeway.

This paper aims to determine the potential of the bicycle as a sustainable mode of transport in a medium-sized Spanish city (Santander, in northern Spain) with strong inclines and relatively inclement weather. For this purpose, a general methodology has been designed that could serve as an example for other areas. First, potential bicycle users in the city are characterized and identified through a household survey, which included a complete travel diary. Then they were asked to participate in a stated preference survey designed to find out the relative importance of certain key variables, previously identified, associated with making bicycle journeys. These data were used to estimate mixed logit models allowing to correctly treat the pseudopanel nature of the data. The results indicate that the most important variables among potential users are the cost and the climate, followed by the availability of infrastructure such as cycle paths and an extensive network of both public and private bicycle docking stations. Finally, the willingness to change from traditional modes of transport, such as car and bus, to bicycle has been examined according to various policies designed to encourage more sustainable mobility (such as bicycle and bus lanes and a city center congestion charge for private cars). The main finding of this research has been the identification of the conditions under which the bicycle could increase its market share from its current 0.30% up to 5.52% in a city with the characteristics of Santander (i.e., not in principle conducive to expect high bicycle use).

Urban land-use planning is becoming increasingly complex in China because it requires estimating the future urban extent and balancing its various aspects, e.g., provision of enough housing and employment opportunities and preservation of the environment. This paper presents an integrative approach to the problem of sustainable land-use planning. Specifically, an urban growth simulation tool, a cellular automata model, was used to determine the extent of the urban area, and a neural network approach was used to quantitatively predict the land-use structure in the projected year. A multiobjective optimization genetic algorithm was then developed to search for Pareto-optimal urban land-use plans within the urban extent determined by the urban growth model. To search for a sustainable urban land-use plan, social, economic, and environmental objectives were defined that reflect the multiple objectives of the urban system. In addition to these nonspatial goals, objectives concerning the spatial distribution of land usages were proposed. These are classified as local and global spatial objectives. A case study of the Donghu Lake watershed was conducted. Donghu Lake is one of the largest downtown lakes in central China, and the watershed area is undergoing rapid urbanization and suffering from nonpoint source water pollution. The study was carried out to validate the proposed method, and it demonstrated that the models are appropriate for areas undergoing urban expansion.

Current scientific literature reinforces the observation that there has been an increase in frequent occurrences of floods in urban areas and emphasizes that the main reason for the increase of flooding is the reaction of the environment to the effects of anthropic action. Considering this scenario of flooding caused by man, this study aims to present a review of the literature on the influence of soil sealing, define sustainable allotment (SA) in line with the local behavior of the hydrological cycle, and propose the establishment of a technical requirement on the part of Brazilian municipalities of a minimum permeable area soil that should be left in each plot (plot territorial) of allotments that fits the sustainable concept. The research method was based on the observation of the behavior of some Brazilian cities [Antonio Carlos (SC), Biguaçu (SC), Criciúma (SC), Curitiba (PR), Ribeirão Preto (SP), São José (SC), and São José dos Campos (SP)] as well as other countries [Lisbon and Sintra (Portugal), Kitchener, Quebec, and Vancouver (Canada), and Liverpool (England)], especially in the areas of the infiltration minimum required to obtain a building permit. Research was also conducted to verify the respective regulations of maximum rates of land occupation and the minimum size defined for each lot, to avoid and/or minimize the occurrences of urban flooding. After a survey of normative data, six distinct simulations (minimum areas and average urban residential lots), were taken to verify the impact of the requirement of minimum area considered permeable. Finally, it is clear that for implementing a sustainable allotment, it is necessary to leave at least 25% of the area of permeable soil batch, resulting in a reduction of up to twice the volume of rainwater when compared with land in urban areas where the requirement does not apply.

China’s rapid urbanization has been attracting widespread interests of the economists, sociologists, and geographers all over the world in recent years. This study was conducted to analyze the network tendency of the urban system in China based on quantitative methods. In the theoretical analysis part, this paper reveals the transformation from a size-based to a network-based urban system in the urban system research and planning concept in China. Then, this paper established the network economy model and the linear model for quantitative analysis about network tendency of the urban system. The results were established based on the employment data for 18 major industry categories data and flow data of 35 cities from statistics on Chinese cities over the period 1999–2010. This paper reveals that urban networks have begun to affect the urban system increasingly more significantly, even more so than the size-based hierarchy. Further analysis shows that there will be a transition from size-based control to network-based control in the Chinese urban system in the coming decade (in 2018). The results of this study demonstrate that the methods applied here can facilitate an effective analysis of the change in urban hierarchy that has occurred in China. This research also provides lessons for urbanization studies in other developing countries.

The transformation of former industrial areas is important to urban redevelopment, although such activity is often limited by possible on-site pollution, complicated ownership, and legal constraints. Rather than treating these areas as a problem, many cities recognize the advantages of redeveloping them because of their often central locations. Some are transformed through a temporary city event with the participation and support of external organizations and planned as a part of the urban development. This paper is an in-depth case study on the planning perspectives of Expo 2010, Shanghai, China, a regeneration project on a former industrial site. By scrutinizing the case with the details based on compiling information, contextualizing the project, and comparing the expectation and reality during the preevent, event phase, and postevent phase of the project, it is found that (1) governmental participation plays a key role in the transformation of former industrial area with city event, especially on the site where it has not completely finished its industrial activities; (2) the main motivation and significance of regenerating the former industrial area is to boost city redevelopment in the long term; and (3) a successful transformation is determined by not only the first stage from preevent to event phase but also the second stage from event to postevent phase. All these features provide a deep insight into the redevelopment of a former industrial area.

Multifunctionality in urban ecosystems has received much attention in the last decade from researchers and policy makers. This paper provides research on urban multifunctional landscape clustering, using the city of Shenzhen, China, as a case study. Utilizing the self-organizing feature map (SOFM) neural network model, six different landscape functional indices were identified, and urban multifunctional landscape regionalization produced five major units. According to SOFM clustering results, each region had its respective primary function, such as gas regulation, water supply, human nature regulation, soil environmental regulation, economy, and cultural priority. The gas regulation ecological supporting region (Zone I) covers $490.5{\mathrm{km}}^2$, with long coastline form a nature-dominated, less human-influenced physical environment; the water supply ecological supporting region (Zone II) is $25.8{\mathrm{km}}^2$, and river network density reaches $0.986\mathrm{km}/{\mathrm{km}}^2$, supporting function of water conservation and water supply; the mountain forest environmental regulating region is Zone III, $377.7{\mathrm{km}}^2$ with substantial forest cover; covering the largest area of $547.8{\mathrm{km}}^2$, zone type (IV) represents soil regulation region; the fifth zone type (V), on the west coast, is definitely a human-dominated region. The results show that the human and nature interfaced peri-urban region is the most affected and threatened area in the city. Under the control of urban sprawling local regulation, the urban population growth would slow down, but there is no convincing evidence that the limitation of build up land have negative influence on the urban economy. Thereafter, the authors analyzed the functions of each unit and compared the SOFM clustering technique with the traditional K-means clustering method. The result revealed that both methods are effective and appropriate for regionalization of urban multifunctional landscapes, but SOFM has advantages in identifying spatial patterns. Finally, approaches to achieve sustainable urban development were illustrated and their importance highlighted for policymakers and stakeholders.