Transportation and Urban Dynamics

Both land use and transportation are part of a dynamic system that is subject to external influences and internal changes. Each component of the system is continuously evolving due to changes in technology, policy, economics, demographics, and even culture or values. Since transportation infrastructure and real estate development require significant capital investments, understanding their dynamics is of high relevance for investors, developers, planners, and policymakers. As a result, the interactions between land use and transportation are played out as the outcome of the many decisions made by residents, businesses, and governments.

The field of urban dynamics has expanded the scope of conventional land use models, which tended to be descriptive, by trying to consider the relationships behind the evolution of the urban spatial structure. This focus has led to a complex modeling framework, including a wide variety of components such as the transportation network, housing locations, and workplaces. Among the concepts supporting urban dynamics are retroactions, whereby changes in one component will influence other associated components. As these related components change, there is a feedback effect on the initial component, which is either positive or negative. The most significant components of urban dynamics are:

·         Land use. The most stable component of urban dynamics, as changes are likely to modify the land use structure over a rather long period of time. This is to be expected since most real estate is built to last at least several decades, and there are vested interests to amortize its usage over that period with minimal changes outside repairs and maintenance. The main impact of land use on urban dynamics is its function of a generator and attractor of movements.

·         Transport networks. Networks are a rather stable component of urban dynamics, as transport infrastructures are built for the long term. This is particularly the case for large transport terminals and subway systems that can operate for decades. For instance, many railway stations and subway systems are more than one hundred years old and continue to influence the urban spatial structure. The main contribution of transport networks to urban dynamics is the provision of accessibility where changes will impact mobility.

·         Movements (flows). The most dynamic component of the system since the mobility of passengers and freight reflects almost immediately changes in the supply or demand. Mobility thus tends more to be an outcome of urban dynamics than a factor shaping it.

·         Employment and workplaces. They account for significant inducement effects over urban dynamics since many models often consider employment as an exogenous factor from which other aspects of the urban dynamics are derived. This is specifically the case for employment that is categorized as basic, or export-oriented, and which is linked with specific economic sectors such as manufacturing. Commuting is a direct outcome of the number of jobs and the location of workplaces.

·         Population and housing. They act as the generators of movements because residential areas are generators of commuting flows. Since there is a wide array of incomes, standards of living, and preferences, this socioeconomic diversity is reflected in the urban spatial structure.

·         For representing complex urban dynamics, a number of transportation land use models have been developed, with the Lowry model among the first (1964). Its core assumption is that regional and urban growth (or decline) is a function of the expansion (or contraction) of the basic sector, which is represented as export-based employment that meets non-local demand. An urban area produces goods and services, which are exported. This employment is, in turn, having impacts on the employment of two other sectors; retail and residential. Its premises were expended by several other models, known as “Lowry-type” models that were applied to various cities. The core of these models relies on a regional economic forecast that predicts and assigns the location of the basic employment sector. As such, they are dependent on the reliability and accuracy of macro-economic and micro-economic indicators and forecasting. Such forecasting tends not to be very accurate as it does not capture well the impacts of economic, social, and technological changes, which also change the relevance of indicators.

·         Another line of models emerged in the 1990s with the rise of computing power. Cellular automata are dynamic land use models developed on the principle that space can be represented as a grid where each cell is a discrete land use unit. Cell states thus symbolize land uses, and transition rules express the likelihood of a change from one land use state to another. Because cells are symbolically connected and interrelated (e.g. adjacency), models can be used to investigate the dynamics, evolution, and self-organization of cellar automata land use systems. The cellular approach allows achieving a high level of spatial detail (resolution) and realism, as well as to link the simulation directly to visible outcomes on the regional spatial structure. They are also readily implementable since Geographic Information Systems are designed to work effectively with grid-based (raster) spatial representations. Cellular automata improve upon most transportation – land use models that are essentially static as they explain land use patterns. Still, they do not explicitly consider the processes that are creating or changing them.

·         The issue about how to articulate transportation and land use interactions remains, particularly in the current context of interdependence between local, regional, and global processes. There is also the risk of unintended consequences (unaccounted feedback) where a change may not result in an expected outcome. For instance, improving road transportation infrastructure can have the potential to create even more congestion as new users are attracted by the additional capacity. Globalization has substantially blurred the relationships between transportation and land use, as well as its dynamics. The primary paradigm is concerned with some factors once endogenous to a regional setting have become exogenous.

·         Many economic activities that provide employment and multiplying effects, such as manufacturing, are driven by forces that are global in scope and may have little to do with regional dynamics. For instance, capital investment in infrastructures and facilities could come from external sources, and the bulk of the output could be bound to international markets. In such a context, it would be challenging to explain urban development processes taking place in coastal Chinese cities, such as the Pearl River Delta, since export-oriented strategies are among the most significant driving forces. Looking at the urban dynamics of such a system from an endogenous perspective would fail to capture driving forces that are dominantly exogenous.

·         The relationships between transportation and land use that have been the focus of a long line of geographical representations, including models, are mainly driven by economic and technological changes. It is expected that ongoing changes related to digitalization, such as e-commerce, and automation in manufacturing and distribution, will continue to shape the urban spatial structure in the 21st Century.