Environment and Planning B: Urban Analytics and City Science

Most planning research seeks to understand how current planning practices influence (and are influenced by) the processes and institutional contexts of decision making and the transformation of spaces. Typically, analytical methods borrowed from other social sciences are employed for this purpose. However, if one wants to know how new planning practices can be generated, a different research approach seems to be needed. Relevant innovations do not originate in an academic vacuum, but have to be developed in coproduction with intended users and in the context of their intended use. Only then can a reciprocal learning process between research and practice be activated in which original hypotheses about possible planning innovations are developed through iterative testing, reflection, and adaptation. In our opinion, carrying out research into possible planning innovations thus requires a different type of research methodology from the one typically applied. Because of its static nature, a traditional comparative case-study analysis—as often used in planning research—does not allow for such an iterative, evolutionary process. In this paper we propose a new methodology, which we have labelled ‘experiential case-study analysis’. In this approach each case study provides learning experiences that fuel theory building, but also serve as input for the next case study. We have used this approach to develop and test different planning innovations in three case studies in the field of transport and urban planning in The Netherlands.

Data on human movement are valuable input data for building-simulation tools such as indoor-climate simulation and working-condition assessment. However, reliable data on human movement in buildings are scarcely available. Existing human-movement models are, typically, developed for (semi)public spaces and lack applicability to indoor spaces. The research presented here focuses on indoor office-building spaces and normal working conditions. The simulation model was developed in conjunction with a validation method. Web-based diaries and radio frequency identification technology were used to collect data on human behaviour in a real-life situation. The performance of the model was tested against a set of newly developed criterion variables (for example, the usage of facilities or the movement behaviour of employees) related to human movement in building spaces. Observed and predicted movement patterns were compared for these criteria. Results indicate close correspondence between simulated and observed behaviour, providing evidence of the validity of the model. The model can be used to accurately predict the space utilisation of an organisation.

Sprawl opponents have blamed sprawl for weakening linkages among the residents and social capital but there is a lack of empirical evidence to support their argument. This study examines the relationship between the county sprawl index and social-capital factors from the 2000 Social Capital Community Benchmark Survey data. Using 3-level hierarchical models, this study shows that for the US, urban sprawl may support some types of social capital while negatively impacting the others. Furthermore, changing urban form via population density and street accessibility at the county level may not be ideal to improve social capital.

In this paper we define a computational method for measuring walking distances within buildings based on a length-weighted graph structure for a given building model. We name it the universal circulation network (UCN) and it has been implemented as plug-in software in Solibri Model Checker using building information modeling technologies. It provides a new explicitly defined method for representing circulation paths on top of building models supporting further circulation-related analysis as a network application. We define the computing algorithms and how we realize them. We focus not only on the implementation issues, but also on other intrinsic aspects that need to be considered while dealing with pedestrian circulation within buildings. The UCN is determined mainly by the spatial topology and geometry of a given building, and it returns consistent and accurate scalar quantities. It takes into consideration people-movement patterns, reflecting that people tend to walk along the shortest, easiest, and most visible paths. In several actual-design review projects, the UCN has proved that it is of practical benefit, not only to the distance measurement but also the visualization of pedestrian circulation, especially in reviewing building circulation.

A primary goal of the US Disaster Mitigation Act of 2000 is to slow the increase in disaster losses by emphasizing a proactive approach focusing on predisaster hazard mitigation, rather than postdisaster relief. The legislation requires local communities to produce hazard-mitigation plans that include multihazard maps, signifying a de facto prioritization of mitigation dollars on the basis of areas with the greatest vulnerability. However, there is little formal or practical guidance for communities on how to produce such maps. We propose a methodology for hazard-vulnerability assessments using multihazard mapping, where hazard frequency is a measure of risk, historical dollar losses are a proxy for infrastructure impact or exposure, and the Social Vulnerability Index (SoVI) evaluates human vulnerability. Using a test case of one county, Charleston, South Carolina, a geographic information system spatially combined these dimensions of vulnerability across multiple hazards. The resulting maps provide a tool for hazard-mitigation planning, which contains an initial screening element to highlight zones of highest multihazard vulnerability. The approach helps to generate a view of not just what is at risk, but who is at risk, and where, thus enhancing the implementation of targeted impact-reduction strategies.

For a practical computer implementation of part embedding in shapes that is also true to their continuous character and the shape grammar formalism, shapes and their boundaries are handled together in composite shape and label algebras. Temporary representations of shapes, termed ‘overcomplete graphs’, comprise boundary elements of shapes and how they are assembled, and are utilized in a two-phase algorithm that systematically searches for embedded parts. The associated implementation is developed to receive user-defined constraints for an interactive search. In particular, the user-defined reference shape extends the search to nondeterministic cases.

Within the framework of Web 2.0 mapping applications, the most striking example of a geographical application is the OpenStreetMap (OSM) project. OSM aims to create a free digital map of the world and is implemented through the engagement of participants in a mode similar to software development in Open Source projects. The information is collected by many participants, collated on a central database, and distributed in multiple digital formats through the World Wide Web. This type of information was termed ‘Volunteered Geographical Information’ (VGI) by Goodchild, 2007. However, to date there has been no systematic analysis of the quality of VGI. This study aims to fill this gap by analysing OSM information. The examination focuses on analysis of its quality through a comparison with Ordnance Survey (OS) datasets. The analysis focuses on London and England, since OSM started in London in August 2004 and therefore the study of these geographies provides the best understanding of the achievements and difficulties of VGI. The analysis shows that OSM information can be fairly accurate: on average within about 6 m of the position recorded by the OS, and with approximately 80% overlap of motorway objects between the two datasets. In the space of four years, OSM has captured about 29% of the area of England, of which approximately 24% are digitised lines without a complete set of attributes. The paper concludes with a discussion of the implications of the findings to the study of VGI as well as suggesting future research directions.

This paper addresses the question of how to create environments that people will want to explore. Four environmental properties (slines, entropy, floor area, and shape) were tested for exploration time in three experiments that included thirty-eight virtual environments and sixty participants. Slines had the strongest effect on exploration time (r = 0.36), followed by entropy (r = 0.34). Floor area and shape had much smaller effects on exploration time (r = 0.10 and r = 0.09, respectively). Possibilities for future research are discussed.

Walking has long been neglected in urban-mobility research, but it is now making its way into numerous studies using various approaches. Empirical data are often processed in well-known models of flow allocation to study the behaviour of pedestrians and to identify their preferences. However, these models assume that route choices are predetermined at the start of each trip and do not admit any possible intervening decision along these trips. We propose to overcome this limitation through a new method for the analysis of pedestrian behaviour. This method, which we call ‘deviation analysis’ consists of (1) identifying the intersections from which a pedestrian has chosen a route longer than the shortest path; (2) defining the segments of the network which diverge from each deviation; (3) testing the influence of the environmental variables of these segments on the choice of route by using a discrete choice model. Deviations are compared with the cases where pedestrians follow the shortest path (called ‘continuations’), which are assumed to be less strongly linked to environmental variables due to the ‘natural’ choice for minimising the distance travelled. This method is applied to a series of pedestrian trips recorded in the French city of Lille. Results show that the environmental variables used in this study contribute to explaining the route choices with more strength when the deviations involve a trip lengthening of at least 50 m. They also show that the influence of variables describing the visual aspect of urban landscape may influence the route choices and outline the positive role of the urban atmosphere linked to the commercial function of streets.

Despite calls for performance-oriented and evidence-based planning, the outcomes of land use and environmental plans are rarely monitored or assessed ex post facto (that is, post implementation). As a result, planners cannot know whether or why plans achieve their goals, or learn from the results of past interventions to improve planning practice. This evaluation gap is caused by a lack of methodology to evaluate the outcomes of plans and the difficulty of attributing changes to planning activities. We address this gap by proposing and testing a plan-outcome evaluation (POE) methodology. We demonstrate its broad applicability and usefulness in the context of local plans in New Zealand. The POE methodology will be useful to practitioners and academics seeking to assess the outcomes of plans in countries with western planning traditions.