Environment and Planning B: Urban Analytics and City Science

Human spatial behavior and experience cannot be investigated independently from the shape and configuration of environments. Therefore, comparative studies in architectural psychology and spatial cognition would clearly benefit from operationalizations of space that provide a common denominator for capturing its behavioral and psychologically relevant properties. This paper presents theoretical and methodological issues arising from the practical application of isovist-based graphs for the analysis of architectural spaces. Based on recent studies exploring the influence of spatial form and structure on behavior and experience in virtual environments, the following topics are discussed: (1) the derivation and empirical verification of meaningful descriptor variables on the basis of classic qualitative theories of environmental psychology relating behavior and experience to spatial properties; (2) methods to select reference points for the analysis of architectural spaces at a local level; furthermore, based on two experiments exploring the phenomenal conception of the spatial structure of architectural environments, formalized strategies for (3) the selection of reference points at a global level, and for (4), their integration into a sparse yet plausible comprehensive graph structure, are proposed. Taken together, a well formalized and psychologically oriented methodology for the efficient description of spatial properties of environments at the architectural scale level is outlined. This method appears useful for a wide range of applications, ranging from abstract architectural analysis over behavioral experiments to studies on mental representations in cognitive science.

This paper introduces a novel algorithm for delineating mutually exclusive service areas of shelters which have finite capabilities to accommodate residents who are unevenly distributed in space. Minimizing the travel cost and keeping spatial continuity with capability constraint are the convergent objectives of this algorithm. The algorithm partitions an entire residential area into a number of spatial units to handle the unevenness of demand, and employs a shift insertion mechanism to reduce travel cost and to improve the spatial continuity of service areas. A series of experiments and scenarios has been conducted for the city of Memphis, USA, to validate the proposed algorithm. Comparative experiments under different constraints show that the proposed algorithm is a feasible solution for delineating service areas. Various application circumstances (for example, travel-cost calculation methods and the granularity of available demographic data) are discussed to evaluate the algorithm's feasibility. The proposed algorithm can be applied not only to delineating service areas of existing shelters but also to optimizing location allocation of new shelters or other facilities with similar characteristics.

A range of forecasts of global oil production made between 1956 and the present day are listed. For the majority of these the methodology used to generate the forecast is described. The paper distinguishes between three types of forecast: group 1—quantitative analyses which predict that global oil production will reach a resource-limited peak in the near term, and certainly before the year 2020; group 2—forecasts that use quantitative methods, but which see no production peak within the forecast's time horizon (typically 2020 or 2030); group 3—nonquantitative analyses that rule out a resource-limited oil peak within the foreseeable future. The paper analyses these forecast types and suggests that group 1 forecasts are the most realistic.

This study analyzes a longitudinal series of Ankara apartment houses using space syntax methodology to uncover the underlying genotype and its transformation over time. The results indicate that transition-space-centred organization is the underlying spatial structure for 20th-century Ankara apartments. Diachronic examination of the sample in terms of sectoral differentiation—that is, clustering of spaces based on functional and social requirements, and in relation to the exterior— has identified three groups: (a) the houses from the 1920s with no sector differentiation and one entrance; (b) the houses from the 1930s, 1940s, 1950s, and 1960s with different sectors and multiple entrances; (c) the houses from the 1970s, 1980s, and 1990s with different sectors and one entrance. Viewing these results in relation to an analysis of the history of domestic culture demonstrates that there exists a schism between the historical periods representing social changes and the spatial periods representing the transformation of the Ankara house genotype.

Cellular automata (CA) can reproduce global patterns and behavior from local interactions of cells and they are used increasingly to simulate complex natural and human systems. Among their attributes are their computational simplicity and their explicit representation of space and time. However, the classic definition of CA limits their application to problems that involve a discrete space, and similar rules and neighborhoods for all cells. In addition, the standard raster-based CA model is sensitive to spatial scale. This paper presents a new vector-based geographic cellular automata model, called the VecGCA model, which defines space as a collection of irregular geographic objects. Each object has a geometric representation (a polygon) that evolves through time according to a transition function that depends on the influence of neighboring polygons. In this model, the neighborhood is defined as the region of influence on each geographic object, and the neighbors are all geographic objects located within the region of influence. An innovative aspect of the VecGCA model is that the procedure allows geometric transformation of objects. The area of a polygon (representing an object) is reduced in the region that is nearest to the neighbor that exerts an influence on it, and the area of that neighbor is increased accordingly. The proposed model was tested with real data and compared with a raster-based CA model to simulate land-use changes in an agroforested area in southern Quebec, Canada. The model was validated using two land-use maps, produced from satellite Landsat Thematic Mapper imagery, which were acquired in 1999 and 2002. The results obtained show that VecGCA can represent well the dynamics in the study area through an adequate evolution of the geometry of the geographic objects which are independent of the cell size, whereas, to generate similar outcomes in the raster-based CA model, a sensitivity analysis must be conducted to determine which cell size is needed. The geometric transformation procedure introduced in the VecGCA model executes the change of shape of a geographic object by changing its state in a portion of its surface, allowing a more realistic representation of the evolution of the landscape.

The assessment of design creativity is a fundamental issue in the educational curriculum in schools of architecture. Assessment in the form of criticism is carried out in the design studio, where students acquire skills and knowledge, forge judgments about their design outcomes, and get feedback from their instructors. This study focuses on the assessment of creativity in design problem solving. The major objective of this research was to test to what extent architects and design students share the same conceptions of creativity, and how similar they are. Contrasting differences were found between the two groups. While architects focused on innovation aspects, students paid more attention to operational aspects, such as dealing with design requirements. It is maintained that handling these differences by means of intervention programs in the design studio may promote the acquisition of design processes and procedures by the students, and also that, it will contribute to bridging the gap between the way teachers and students perceive and evaluate design creativity.

Councils of governments create regional comprehensive plans to shape the future development of their regions. However, actual implementation often depends on local governments that control land use. How, if at all, did two Atlanta Regional Development Plans (RDPs) influence local government policies? Interviews and comparisons of regional and local policies reveal that the RDP planning process clearly and causally influenced voluntary local comprehensive plans, but not subsequent local land-use regulations. However, the RDPs served other functions, such as data provision. Thus, it is useful to incorporate a communicative evaluation approach to examine the broader functions of the planning process, rather than strictly examining the conformance outcomes of the plan policies.

This paper develops and applies neural network (NN) models to forecast regional employment patterns in Germany. Computer-aided optimization tools that imitate natural biological evolution to find the solution that best fits the given case (namely, genetic algorithms, GAs) are also used to detect the best NN structure. GA techniques are compared with more ‘traditional’ techniques which require the supervision of experienced analysts. We test the performance of these techniques on a panel of 439 districts in West and East Germany. Since the West and East datasets have different time spans, the models are estimated separately for West and East Germany. The results show that the West and East NN models perform with different degrees of precision, mainly because of the different time spans of the two datasets. Automatic techniques for the choice of the NN architecture do not seem to outperform selection procedures based on the supervision of expert analysts.

A new modelling framework for the study of the dynamics of urban systems is proposed. We generalize the notion of cellular automaton, using continuous variables to describe the state of a cell. The time evolution is given by Poisson-distributed stochastic jumps corresponding to urban interactions, with intensities depending on the configuration of the system in a suitable set of neighbourhoods. These interactions result from decision processes of populations of cognitive agents modelled in the framework of fuzzy decision theory. The behaviour of agents is driven by goals and constraints, partially defined using a fuzzy logic formalization of a real estate appraisal method based on the evaluation of the attractiveness of a terrain for different land uses. Randomness of the dynamics is a consequence of the fuzziness of these decisions. Hence the model can be seen as a multiagent system with sound mathematical foundation. For example, the use of a continuum-valued state space enables us to prove that the expectation of state variables verify a system of differential equations, and thus to study the system from a dynamical systems theory perspective. In this paper we present the theoretical setting, leaving the applications to a second paper.

The overall objective of this paper is to show how a formal decision support method can be used effectively to support a land-use planning problem. Central to our approach is a heuristic algorithm based on a goal-programming/reference-point approach. The algorithm is tested on a small region in the Netherlands. To demonstrate the potential use of the algorithm, a planning problem is defined for this region. An interactive session with a land-use planner is then simulated, to show how feedback from the planner is used to generate a plan in a number of rounds. It is concluded that the approach has potential for the support of land-use problems especially in the first rounds of policy design as long as maps are used to interface between planner and algorithm. It is also shown that computational problems still hinder the achievement of realistic detail in the representation of the plan area.