Environment and Planning B: Urban Analytics and City Science

Migration has become a prominent research theme in geography and regional science and it has been approached from various methodological angles. Nonetheless, a common missing element in most migration studies is the lack of awareness of the overall network topology, which characterizes migration flows. Although gravity models focus on spatial interaction—in this case migration—between pairs of origins and destinations, they do not provide insights into the topology of a migration network. We employ network analysis to address such systemic research questions, in particular: How centralized or dispersed are migration flows and how does this structure evolve over time? And, how is migration activity clustered between specific countries, and if it is clustered, do such patterns change over time? Going a step further than exploratory network analysis, in this paper we estimate international migration models for OECD countries based on a dual approach: gravity models estimated using conventional econometric approaches such as panel data regressions and network-based regression techniques such as multivariate regression quadratic assignment procedures. The empirical results reveal not only the determinants of international migration among OECD countries, but also the value of blending network analysis with more conventional analytic methods.

This study tackles the description of the size distribution of urban employment centers or, in other words, the size of areas within cities with significantly high densities of workers. Certainly, there exists a branch of urban economics that has paid substantial attention to urban employment centers, but the efforts have been focused on identification methodologies. In this paper we build on such body of research and combine it with insights from the latest contributions in the sister subfield of city size distributions to push the agenda forward in terms of the understanding of these phenomena. We consider the 359 Metropolitan Statistical Areas (MSAs) in the United States in the year 2000 and reach three main conclusions: First, employment center sizes are more unevenly distributed than city sizes; second, the two functions that best describe city size distributions, namely the lognormal and the double Pareto-lognormal, also offer a good fit for the case of centers, particularly the latter; and third, several interesting statistically significant relationships (correlations) between variables related to centers and MSAs are deduced. Further experiments with a different technique of center identification suggest that the results are fairly robust to the method of choice.

Supply chains provide the critical infrastructure for the production and distribution of goods and services in our network economy and serve as the conduits for the manufacturing, transportation, and consumption of products ranging from food, clothing, automobiles, and high-technology products, to healthcare products. Cities as major population centers serve not only as the principal demand points but also as the locations of many of the distribution and storage facilities, transportation providers, and even manufacturers. In this paper a new model is developed for the design of sustainable supply chains with a focus on cities that captures the frequency of network link operations, which is especially relevant to cities due to frequent freight deliveries. The model is also related to recent literature on this subject. The goal is to demonstrate how, through the proper design (and operation) of these complex networks, waste can be reduced, along with the environmental impacts, while minimizing operational and frequency costs, and meeting demand.

Urban construction activities are subject to periods of fast expansion followed by periods of slow growth. Some of these expansions are limited in size, while others are huge. Therefore, it is not surprising that equilibrium-oriented classical models of urban spatial structure are hard pressed to explain the formation of modern cities with polycentric structure and births of subcenters in particular. To understand the development of cities' spatial patterns we present a model of urban spatial dynamics that is driven by two types of real-estate entrepreneurs that differ in their degree of risk aversion. The developers act in the shadow of the city planning board that formulates urban development policy and defines the boundaries of future residential expansions. The model's salient feature is the time lag between the time of purchase of property rights by land developers and the time of the realization of revenues. We assume that this lag varies in space, being much larger in locations that are not zoned for building. It can be reduced by the planning board in cases of high demand for dwellings. We use the model to demonstrate how the interaction between demand for dwellings, the choices taken by each type of developer, and planning policies leads to the creation of new urban subcenters. The model dynamics are characterized by long out-of-equilibrium periods followed by sudden bursts of construction activity that resembles self-organized criticality.

In this article we introduce the method of sequence alignment and its uses for creating tourist typologies based on temporal and spatial movements through a destination. The sequence alignment method was first developed in the 1980s by biochemists who wished to analyse DNA sequences; it was adapted for use in the social sciences towards the end of the 1990s. Unlike traditional quantitative methods, sequence alignment is concerned with the order (or sequence) of events. Thus, it is well suited for tourism research, as tourism involves the mobility of tourists through time and space. In this study, a database composed of 305 space-time sequences of visitors to Hong Kong was analysed. Data were obtained using global positioning system devices which were distributed among participants. The sequences were aligned using ClustalG, a sequence alignment computer program. The analysis resulted in the identification of various classifications of tourists in Hong Kong based on their time-space patterns.

Recent studies have confirmed that store layout influences a shopper's movement, purchasing behavior, and preference. However, the systematic and quantitative description of the layout of retail stores has been discussed in few studies. The analytic method for describing a layout presented in this study, with other refined analysis capabilities, is based on a prespecified set of visual targets rather than each occupiable location such as a room. The systematic visibility description of a layout enables quantitative comparison of multiple locations within one layout and across multiple physical layouts. An observation exercise took place in a bookstore and the target-based systematic analysis showed, while nontarget-based systematic analysis did not show, that a product with high visibility from major paths, where shoppers tended to have more visual contact, had more product engagement. The research not only confirmed the impact of store layout but also showed how the layout affected shoppers' behavior.

Landscape-preference theories such as prospect-refuge theory and Kaplan and Kaplan's landscape-preference matrix and theories of visual perception propose that the physical structure of the landscape has a direct psychological effect on people due to evolved sensitivity to particular defining characteristics. Efforts to identify consistent quantitative relationships between metrics of these characteristics and human preference have had some success. However, the field has also faced some criticisms due to low explanatory power in the results reducing confidence that relationships found can be applied to other contexts. In this paper we argue that dependence on generalised planar maps for the derivation of the metrics but on viewpoint-specific perspective photographs for the preference data is a potential cause of low explanatory power. How viewpoint change may affect scene characteristics needs to be better understood if representative viewpoints are to be chosen to allow results which are general to an area, in particular the difference between discreet (topological) changes and continuous changes. This paper presents the results of an experiment to test whether the topological complexity of a view, as measured by the Euler character of the horizon graph, has perceptual significance. We investigate if images with higher horizon-graph complexity were considered more interesting than those with lower graph complexity via a forced-choice Internet survey.

The objective of this study was to investigate the impact of political history on the dynamics of the interrelationship between land use and road networks within cities. Political history, in this study, is defined as the combination of the regional-level government programs and political events that affect the pattern of urbanization in a region. The study focused on urbanization in the cities of Pordenone and Gorizia, both situated in the Friuli-Venezia Giulia region of northeastern Italy, over the period 1950–2000. Being located adjacent to an international boundary, the city of Gorizia has a long history of political instability dating back to the beginning of the 20th century. It is assumed that this political instability has led to the application of differential socioeconomic policies which have affected the process of urbanization in the city. The aim of the study was to capture this effect by investigating the structural changes over the period of fifty years in both land use and the road network. In order to understand the extent of the effect Pordenone was used for comparison, since it has experienced a relatively peaceful past and regular growth. MOLAND (monitoring land-use/cover dynamics) data for land use and the road network were used for the study. Graph theory measures were used for a comparative analysis of the structural properties of road networks in both cities and their development over time. In order to understand the spatial relationship between change in land use and the road network, a nonparametric test of the spatial correspondence of areal distribution was used and tested at multiple spatial scales. The results suggest that political history does affect the land-use and road-network changes individually, but it did not affect the type of spatial relationship that exists between the two for those particular cities. This research makes a unique attempt to analyze the impact of policy on land-use and road-network change by using spatial data and methods of analysis which can help to understand their overall dynamics and that can be used as an alternative to data-intensive and time-intensive simulation models.

Transferable development rights (TDR) are discussed or applied in various countries for a wide variety of purposes: Notably to increase building densities, preserve natural areas, compensate reduced development possibilities, and control land use in rural areas. In Switzerland, TDR, a market-oriented planning instrument, might be used to reduce the land-use problems related to the unsustainable development of the settlement areas and to manage problems with the spatially imbalanced supply and demand of existing undeveloped building zones. Our aim is to briefly introduce a TDR market concept for Switzerland, present an empirically calibrated agent-based TDR market simulation, and finally analyze the detailed simulation results. We ran the simulation with four different settings which allowed an analysis of relevant political and economic questions for Switzerland. The results show that the TDR prices were comparable with existing land prices in Switzerland. In addition, we are able to show that with the trade of TDR it would be possible to downzone 11.4 km² of building zone land for which there is no demand and to develop 7.4 km² of new building zone land up to the year 2018. Consequently, the defined building zone area would decrease, which would be in line with political objectives.