Environment and Planning B: Urban Analytics and City Science

Gated communities have grown in importance in the United States in recent years and they are also common in many other countries. Relatively little is known about the factors and tradeoffs associated with the preferences of households to live in such communities. There is a popular perception of gated communities being refuges for higher income and higher status predominantly white households in the United States but this appears to be largely incorrect. The profile of those who live in gated communities is the focus of this study. Homeowners living in gated communities are analyzed separately from renters, and are compared with those living in nongated communities, with special attention to location within the metropolitan statistical area and housing features. The factors that affect their respective decisions appear to be different. Residence in gated communities is ‘purchased’ both in the form of higher prices and rents, but also in the form of trading off some housing features, such as settling for smaller units with fewer bedrooms, for ‘gatedness’. The role of other factors in affecting likelihood of living in gated communities, including income, education, and some other factors associated with socioeconomic status, is explored using logit analysis. Those living in the urban subregions of the metropolitan statistical areas (the central city and secondary cities) have the highest likelihood of choosing gated communities, other things being equal. Somewhat surprisingly, people do not seem to be choosing gated communities in order to shorten their commuting distances. Despite the media stereotypes, racial minorities are often over-represented in gated communities for all minority groups for both forms of housing tenure (ownership and renting). Income disparities between whites and blacks are generally narrower within gated communities than they are outside of them. Within racial groups, income diversity, as measured by standard deviations, is greater in gated communities than outside of them, indicating greater heterogeneity.

This paper takes a visual approach to flow-data analysis within geographical information systems, and uses spatial interaction data from the United Kingdom for illustrative purposes. As a subfield within GIS, flow mapping is something of a disciplinary laggard, despite significant advances elsewhere in the field. Therefore, the paper has three main aims. First, the intention is to show how complex spatial interaction data—frequently underutilised—can be converted into meaningful information using a GIS-based, visual approach. Second, it is hoped that the contribution will help popularise the subject and stimulate new research within spatial interaction studies and planning more broadly. The third aspect is to demonstrate that we can gain a better understanding, and knowledge of, complex spatial networks through a visual analytics approach to information generation. The paper begins by exploring some key developments in the presentation of flow data. The main body of the paper is comprised of five key geovisualisations which focus on identifying the various patterns of spatial interaction in the United Kingdom. Finally, some conclusions are drawn and direction for future development are highlighted.

Psychometric approaches to measuring sense-of-place variables have focused primarily on the strength of association between individuals and some researcher-defined spatial object. Environmental psychology also has a long tradition of mapping spatial settings and developing methods in natural resource management for measuring the spatial component of sense of place. Our work describes these methods and integrates them with an atittudinal approach that captures individual-level spatial variation and its meaning. We present and demonstrate a complementary data-analysis approach that uses structural equation modelling to integrate the spatial and physical features of places with attitude and behavioural variables. We identify relationships between variables coded from mapping data and attitudes, and demonstrate that this type of spatial data can be modelled using structural equation techniques.

Although references to fractals in architecture are made frequently, to date a systematic, encompassing, scholarly treatment of the use and presence of this geometrical language in architecture is missing. Often such references are made only cursorily and give a limited view on the possible cross-fertilizations between fractal geometry and architecture. In this paper an attempt is made to remedy this, aiming to present a systematic review of the use and presence of fractal geometry in architecture. The paper starts off with a short introductory section. In section 2 some of the theoretical basics about fractal geometry are reviewed. On the basis of this, possible interpretations of the concept ‘fractal architecture’ and the problems associated with them are made explicit and discussed. In section 3 a review of the different ways in which fractal geometry has been related to architecture is presented. Section 4 touches upon quantitative methods to analyze the fractal aspects of architecture. The fifth section is a discussion of a number of methods and heuristics based on fractal geometry to create architectural work. In the final section, possible explanations for the (apparent) perennial interest in fractal form in architecture are discussed.

Urban growth models have been used for decades to forecast urban development in metropolitan areas. Since the 1990s cellular automata, with simple computational rules and an explicitly spatial architecture, have been heavily utilized in this endeavor. One such cellular-automata-based model, SLEUTH, has been successfully applied around the world to better understand and forecast not only urban growth but also other forms of land-use and land-cover change, but like other models must be fed important information about which particular lands in the modeled area are available for development. Some of these lands are in categories for the purpose of excluding urban growth that are difficult to quantify since their function is dictated by policy. One such category includes voluntary differential assessment programs, whereby farmers agree not to develop their lands in exchange for significant tax breaks. Since they are voluntary, today's excluded lands may be available for development at some point in the future. Mapping the shifting mosaic of parcels that are enrolled in such programs allows this information to be used in modeling and forecasting. In this study, we added information about California's Williamson Act into SLEUTH's excluded layer for Tulare County. Assumptions about the voluntary differential assessments were used to create a sophisticated excluded layer that was fed into SLEUTH's urban growth forecasting routine. The results demonstrate not only a successful execution of this method but also yielded high goodness-of-fit metrics for both the calibration of enrollment termination as well as the urban growth modeling itself.

This paper analyses trends in evolution of the urban spatial structure (or urban form) of the city of Ahmedabad, with two key objectives in mind: to generate a quantitative understanding of the evolution of the spatial structure and use such a quantitative understanding to inform the formulation of alternative planning policies for the future. Time-series population data from the Census of India over three decades have been used, which are usually available in most developing countries. In the case of Ahmedabad, the city exhibits a gradual tendency of dispersal, although compared with some other mid-sized metropolitan areas of the world, it is relatively compact. A discussion on the application of the spatial structure analysis to the formulation of alternative planning policies is included. Such analyses for similar cities in India and the developing world in general could be carried out to produce a useful catalogue of cities. However, this is not the objective of the paper, but in due course such literature could be built up.

The movement of visitors in nature areas is influenced by a variety of factors that consist of aggregated characteristics such as the average number of visitors to a park, different types of visitors, and their typical destinations, as well as individual characteristics of an individual vistor's expectations, motivations, activities, duration of stay, and trip itineraries. Therefore, it is important to simulate an overall picture of a visitor movement (macroscopic level) according to his individual physical mobility and cognitive capabilities (microscopic level). Most recreational simulation models have been developed to deal with one specific level in particular. In this paper we describe an integrated multilevel modelling approach for the prediction of visitor movement in nature areas. At the macroscopic level, a visitor movement is represented by a movement surface which follows the analogy of the flow of water in gravity models. In contrast, our model also belongs to the microscopic category, where visitors interact with their movement surface by making a sequence of decisions according to utility measures, which in turn generates their individual trajectories. The model was implemented for the simulation of the visitor movements within the Dwingelderveld National Park, which is located in the northern part of the Netherlands. Finally, the main outcomes and limitations of such a modelling approach are discussed.

Traditional urban plans use definitive design systems, without the flexibility required to deal with the complexity and change that characterize contemporary urban societies. To conceive urban plans with increased flexibility, a shape grammar-based design methodology is proposed which is capable of producing various design solutions instead of a single rigid layout. In this approach the plan is a design system encoding a set of alternative solutions, rather than a single, specific solution. This methodology was developed on the basis of the analysis of existing plans and on a series of experiments undertaken within the controlled environment of design studios. Results show that shape grammars produce urban plans with nondefinitive formal solutions, while keeping a consistent design language. They also provide plans with explicit and implicit flexibility, thereby giving future designers a wider degree of freedom. As a result, they are particularly appropriate for dealing with complexity and change throughout the legal lifespan of the plan. Finally, they provide students with a concrete methodology for approaching urban design, fostering the development of additional design skills.

This study proposes a fuzzy cellular automata model based on the subpixel fractions extracted from multitemporal satellite images and discusses the relationship between sophisticated remote sensing techniques and an urban process model within the socioeconomic dimension. Accordingly, the major objectives of the present research are: (1) to incorporate the subpixel membership derived from remote sensing images into a fuzzy cellular automata model to simulate urban landscape change; (2) to standardize the quantitative method to incorporate subpixel information into a subcell cellular automata model and to find a better way to determine the parameters in the model's development, calibration, and validation. The comparison between the traditional cell-based model and subcell model suggests that the subpixel technique improves the accuracy of both urban mapping and modeling using medium resolution satellite images.

Communication and information are central aspects in participatory spatial planning. This study analyzes the effectiveness of current 3D landscape visualizations in communicating the required spatial information. The focus was on measuring 3D visualizations' effectiveness in participatory planning processes according to the level of various supporting functions for, for example, information processing or achieving the objectives of different planning phases. The effectiveness of abstract and realistic 3D visualization types was tested in case studies using qualitative social – empirical research methods. In order to provide a systematic overview of the results, a portfolio analysis was carried out. The benefit of the visualization types for different planning tasks and their quality of representing the required planning content were evaluated. The results show that the different strengths of both abstract and realistic 3D visualization types are required in participatory workshops. They are especially efficient at motivating stakeholders and enlarging the information base. However, until now they have proved to be less suitable for the development of new ideas and decision making. In particular, the realistic visualization type was ranked as very attractive for the purpose of evaluation, but the representation of the required spatial information needed enhancement. On the basis of the portfolio, focusing further research on optimizing the 3D visualization types for analysis and evaluation tasks is suggested.