Environment and Planning B: Urban Analytics and City Science

In this paper we present a computational approach to the integration of mass customization into the design of novel solutions. We propose the use of entropy as a function of the diversity of solutions that can be generated within a design space. This work demonstrates that the potential of design systems to generate novel solutions can be estimated using complexity measures. This principle is implemented in an evolutionary system for the design of automotive instrument panels that display situation-relevant information in configurations that adapt to traffic conditions and driving actions. This sample application shows that the application of complexity maximization as a selection criterion in evolutionary design systems yields a large variety of solutions of high fitness. We also present guidelines for future developments.

This paper ventures an examination of the linkages among three worlds—those of land-use theorizing and modeling, and that of policy making and planning—which, despite historical and recent advances, remain comparatively poor and haunted by defective communication and problematic translation between them. It is motivated by shifts that have taken place since the late 1980s in all three worlds, away from ‘classical’ thinking (positivism, reductionism, and linear and static worldviews) and towards complex systems (CS) thinking (alternative epistemologies, holism, and nonlinear and dynamic worldviews). The principal question is whether or not CS thinking, compared to classical thinking, addresses more satisfactorily key policy and planning issues, thus holding the potential to improve communication and bridge the gaps between the three worlds. The issues examined are the representation of the sociospatial system, the land-use change process, and policy and planning intervention. After delimiting each world and the diffusion of CS thinking, the paper investigates how the classical approach and the CS approach fare in handling these issues. The analysis suggests that it is not yet possible to determine which approach is superior. The main points are summarized and CS specific and more general future research directions are indicated.

For decades the literature on the winter cities and on urban design has explored the implications of poorly designed urban spaces on pedestrian mobility during various seasons. In Canada, however, practice in using climate responsive design principles tends to be the exception. Using a case study methodology, this paper explores the application of climate responsive design principles in the commercial redevelopment process in Prince George, British Columbia. Findings indicate that, despite expressed interest in winter city development, professionals and decision makers involved in the development permit process do not possess sufficient knowledge about climate responsive design to apply these principles to everyday practice. More importantly, knowledge about climate responsive design did not appear to be a major consideration in creating or evaluating commercial redevelopment projects. A range of educational, attitudinal, regulatory, structural, and political barriers impede the development of an institutional framework to support the implementation of climate responsive design.

Measuring urban sprawl is a controversial topic among scholars who investigate the urban landscape. This study attempts to measure sprawl from a landscape perspective. The measures and indices used are derived from various research disciplines, such as urban research, ecological research, and fractal geometry. The examination was based on an urban land-use survey performed in seventy-eight urban settlements in Israel over the course of fifteen years. Measures of sprawl were calculated at each settlement and were then weighted into one integrated sprawl index through factor analysis, thus enabling a description of sprawl rates and their dynamics over a time period of approximately two decades. The results reveal that urban sprawl is a multidimensional phenomenon that is best quantified by various measures.

Activity bundle (AB) simulation is a method for obtaining a specific contact network (specific to target infectious disease) from the space–time dynamics of individuals constrained both by their social activity and by the physical condition of the space. Taking advantage of AB simulation, an individual space–time activity-based model (ISTAM) is presented which integrates the infectious-disease evolution process, individual activity patterns, and stochastic infection model. ISTAM was applied to the University of Southampton in order to simulate a hypothetical influenza epidemic. The results show that the model behaviour is approximately consistent with expectations.

Recent institutional changes, marketization, and globalization have combined to bring about rapid economic growth in contemporary China. One of the direct outcomes is the rapid expansion of large cities and the recurring birth of new cities from small towns and rural villages. Clustered construction cranes are popular scenes in many Chinese cities. One of the noticeable city landmarks is the specialized economic development district, such as a hi-tech park, industrial park, commerce park, high-standard apartment complex, and designated port district. Along with the development of these new types of urban blocks, the Chinese policies and practices of urban planning and city design have been dramatically reshaped. This paper, on the basis of our participatory observation of the planning process of the Shenzhen Silicon Peak Software Ecological Park, examines site planning and design of hi-tech parks in China. The paper discusses the seven principles guiding the development of hi-tech parks, and the four implementation strategies directing planning and design practices. It also illustrates the adoption of GIS techniques, the new eco-community planning approach, and the classic Chinese cosmology—harmonious wind and water (feng shui)—through the case study. The paper concludes with discussion of the changes of Chinese values and practices of urban planning in the context of hi-tech parks in the transitional period.

This paper proposes an application of the fuzzy Delphi method, the analytic network process (ANP) and zero – one goal programming (ZOGP) for the urban renewal project selection problem in a redeveloping urban area in Taichung City, Taiwan. Urban renewal project selection means the identification of the most cost-beneficial projects (the projects that will produce most cost benefit) in order to maximize the net benefit to the public and to allocate resources most efficiently. In order to evaluate different urban renewal projects, a hierarchical network model based on various factors and the interactions of factors is presented. By incorporating experts' opinion, a priority index can be calculated for each urban renewal project studied, and a performance ranking of urban projects renewal can be generated. In this paper an improved urban renewal project selection methodology, which reflects interdependencies among evaluation criteria and candidate project using an integrated approach, is suggested. Finally, we introduce a method of solution through an empirical real-world urban renewal project selection example on an ongoing decision-making project in Taichung City, Taiwan using ANP – ZOGP. The results provide guidance to the government regarding strategies for accepting orders for redeveloping urban environments.

Corridor planning problems are challenging because their solution often requires the participation of multiple stakeholders with different interests and emphases. Though such problems fall into the domain of multiobjective evaluation, existing corridor location models often search for a single global optimum by collapsing multiple objectives into a single one using a weighting method. In multiobjective problems with competing objectives, however, optimality will often have different interpretations among decision makers, and, as a consequence, no single optimal solution will satisfy all participants. This paper describes the design and implementation of a multiobjective genetic algorithm for corridor selection problems (MOGADOR). This new approach generates a large set of Pareto-optimal and near-optimal solutions that can be evaluated with respect to the untargeted or imprecisely modeled characteristics of ill-structured corridor location problems. Experimental results suggest that the MOGADOR approach outperforms traditional shortest-path methods in both computation time and solution quality. An analytical and visualization tool is provided to help decision makers identify good candidates and evaluate trade-offs among alternatives.

Classification of geographic phenomena is often a black box to anyone outside the immediate group involved in the classification process. There is a growing need for compatibility between datasets to map, evaluate, and monitor areas in a consistent manner. The FAO (Food and Agriculture Organization of the United Nations) Land Cover Classification system (LCCS) is a proposed method to enable interoperability for land-cover data and an attempt to open the classification black box for scrutiny. The FAO LCCS is used to demonstrate some of the strengths and weaknesses of feature-based classification methods and how some important improvements, based on theoretical developments in geographic information science, can extend LCCS to become a ‘boundary object’ that supports representation, negotiation, and analysis of dynamic and heterogeneous classification systems. The suggested improvements also include an outline of how future classification activities could be developed into a distributed web-based ontology infrastructure.