Environment and Planning B: Urban Analytics and City Science

Children's school travel mode is changing, especially away from walking and bicycling and towards private automobiles. Simultaneously we see warning signs from a public health standpoint as children are becoming less active. It has been suggested that walking and bicycling to or from school could help shift this trend, moving it towards greater activity, and researchers are therefore exploring choices of school-trip mode in relation to the pedestrian friendliness of the built environment. Mode-choice models are generally framed as multinomial logit (MNL) models. However, the limitations of MNL models can cause unrealistic effects when walking and bicycling are included with motorized modes. In this paper the focus is on accounting for individual-specific heterogeneity, since different children or families may have very different tastes or tolerances, such as travel time, when it comes to choosing between driving a private automobile, taking the school bus, bicycling, or walking to or from school. The results show that such heterogeneity exists, and that it is more important for nonmotorized modes than for the motorized modes. The results show that accounting for correlation across modes leads to more realistic marginal rates of substitution (cross-elasticities) across modes—in particular, an increase in the walking distance negatively affects the probability both of walking and of bicycling.

This paper is an original attempt to explore the inner logic of and apply the Coase Theorem—specifically the corollary of the invariant version of the Coase Theorem (CIT) and the extension of the corollary of the optimality version of the Coase Theorem (COTE)—to empirical planning research. This attempt hinges critically upon seven theoretical propositions developed on the basis of seven law and policy relevant determining variables that are manifestations of ways of ‘assignment of rights and liabilities’ for the application of CIT (COTE). This is preceded by an examination of the meaning of seven allocative outcomes or determined variables pertaining to the theorem component ‘resource allocation would (under CIT not) be identical’. A 7 × 7 matrix (with forty-nine cells, each defining a specific research arena) is constructed, and relevant literature is surveyed to map the landscape of Coasian planning research as a step to building a transaction-cost-based research agenda. An example of empirically refutable planning hypotheses is given to demonstrate the usefulness of the propositions and to obtain a glimpse of the applicability of the agenda.

The complexity of the sustainable-development policy goal is such that policy makers are searching for tools to enable them to evaluate and develop policy directions. To date, ecological footprinting has been used mainly for raising awareness of environmental impacts but it also has considerable potential as a policy tool, enabling policy makers in their strategic work. The paper presents an application of a specific ecological footprinting development, the REAP (Resource and Energy Analysis Programme) tool, to a current policy issue, the promotion of sustainable construction. Using the London Plan of the Greater London Authority as a case study, it considers the strengths and weaknesses of this approach and how it can contribute to policy development.

Many behavioral and nonbehavioral models have been proposed to model pedestrian behavior. Among these, pedestrians' decision processes have not been explicitly modeled. Utility-maximizing models have been prominently used, but these models may be misspecified owing to their unrealistic assumptions. As an alternative, this paper proposes cut-off models based on the satisficing heuristic founded in bounded rationality theory. The go-home decision of pedestrians in Wang Fujing Street, Beijing, is taken as an example. Results of a multinomial logit model and three cut-off models with increasing complexity are compared. The results show that the cut-off models can fit the data equally as well as the multinomial logit model, suggesting that satisficing heuristics not only have theoretical advantages but also statistical power. Introducing a decision engagement module before the satisficing decision module significantly improves the cut-off model and supports the hypothesis of a hierarchical decision process.

This article illustrates how a parcel-based geographic information system can be used to identify and quantify land-use changes within subareas of individual planning jurisdictions as the basis for evaluating the implementation of local land-use policies. We describe a method for using property-parcel polygons and property-appraiser tax-roll data to analyze the effects of changes in land use on the exposure of people and property to hurricane flooding in coastal communities in Florida. This method allows us to test the conformity of local government growth-management practices to a state mandate which calls for the limiting of development in hurricane hazard zones. We apply this method to analyze hurricane hazard exposure in Okaloosa County, which is a coastal county located in the Panhandle of Florida.

We use remote sensing and GIS to map changes in land cover and to identify systematic land-cover transitions in Southwestern Ghana. Landsat Thematic Mapper satellite imagery of 1990 and 2000 is used to create two land-cover classifications, and the two maps are then compared to produce transition matrices both for protected and for unprotected areas. These matrices are analyzed according to their various components to identify systematic landscape transitions based on deviations between the transitions observed and the transitions expected owing to random processes of change. The results show that closed forest regions inside the protected area transition systematically to bare ground or bush fire, but closed forest outside the protected area transitions systematically to open cultivated woodland. These results are consistent with the hypothesis that logging is the main cause of the loss of closed forest inside the protected areas whereas farming is the main cause of the loss of closed forest outside the protected areas. The research highlights the need for the implementation of this methodological approach to landscape change. Identification of strong signals of forest transformation is particularly important in the light of efforts by policy makers to curb deforestation in Ghana.

Predicting patterns of urban growth will be a major challenge for policy makers and environmental scientists in the 21st century. How cities grow—their shape and size—will have enormous implications for environmental sustainability and infrastructure needs. This paper presents a spatiotemporal ART-MMAP neural method to simulate and predict urban growth. Factors that affect urban growth—that is, transportation routes, land use, and topography—were directly used as inputs to the neural network model for model calibration. The calibrated network was then applied to a study site—St Louis, Missouri—to predict future urban growth and to examine future land development scenarios. This paper also introduces an effective and straightforward method for model validation and accuracy assessment, the prediction error matrix, which has been used in the pattern recognition field for several decades. In order to assess the performance of the neural network model, an in-depth accuracy assessment was conducted in which the model results were compared against a null model, an alternative naïve model, and two random models. The neural network model consistently outperformed the naïve model and two random models, and produced similar or better results than the null model. Furthermore, we evaluated the models' performance at different spatial resolutions. The prediction accuracy increases when spatial resolution becomes coarser. One particularly interesting result is that when the results are aggregated to 1 km spatial resolution, there is 100% accuracy of urban growth predicted by the neural network model versus actual urban growth.

Two measures of floorplate shape, a measure of universal metric distance and a measure of convex fragmentation, are developed to study the effect of building shells upon the spatial structure of office layouts. Layouts are represented according to the fewest-lines map typically used in syntactic studies, with particular emphasis upon integration, a measure of the minimum directional distance from each line to all others. Integration is of special interest because previous case studies indicate that it has important effects upon space use, behaviors, and organizational functions. The study is not limited to examining how actual layouts relate to actual shells, because of the variety of programmatic and contextual factors that most likely influence such a relationship. To control for other variables, the effect of floorplate shape is assessed by inserting consistently generated theoretical layouts into theoretical, as well as actual, floorplates. The study concludes by showing that the integration of unbiased grids and fishbone layouts is affected by floorplate shape in opposite ways. Thus, the interaction between the spatial structure of layouts and the characteristics of shape is mediated by the principles used to generate the layouts. These findings can be used to evaluate building portfolios. They can also help designers to implement particular organizational programs by working around the constraints imposed by the floorplate shapes.

Old buildings may be easier to read than modern buildings because they possess visual depth. This is the finding of an experiment that analysed building elevations and newspapers looking for a connection between their character and the size – frequency distribution of their component parts. It was found that drawings of older buildings sometimes displayed 1/f scaling and thus resembled natural scenes, but that this was rarely the case for modern buildings. The same distribution was also found in newspaper pages. We hypothesise that this distribution allows buildings to appear interesting and changeful when approached from afar in the same way that it makes newspapers easy to read over a range of distances, on a newsstand, over a shoulder, and so forth.

Fractal analysis and the calculation of fractal dimension offer the potential for the numerical characterisation of places by providing a synthetic measurement of place complexity. This paper provides a fractal analysis of street vistas linking the calculation of fractal dimension to the perception of levels of visual variety present in everyday urban streets. A technique for calculating street vista fractal dimensions of textures extracted from greyscale images is presented, and correlations between the resultant fractal dimension and scores for perceived visual variety are discussed.

Conclusions in empirical studies of commuting and urban spatial structure depend on the selection of measures for the job-housing relationship. In order to help to develop urban growth strategies based on coherent empirical results, this paper presents a ‘commuting spectrum’ approach as an alternative to existing job–housing relationship measures. With this approach, two hypothetical and extreme commuting possibilities are conceptualized as measures for job–housing relationship and location-choice sets. Simulation in a stylized region and empirical results for Boston and Atlanta indicate that the proposed method can track local and regional aspects of job – housing relationship changes. The revealed association between commuting length and the job–housing relationship is consistent from the perspectives of neighborhood-level comparison, multiyear comparison, and interregion comparison.