A.1 – Methods in Transport Geography

Author: Dr. Jean-Paul Rodrigue

In addition to providing a conceptual background to the analysis of the mobility of passengers and freight, transport geography is an applied science relying on quantitative and qualitative methods.

1. Transportation and Methodologies

Transportation is not a science but a field of inquiry and application. Two common traits of transportation studies, regardless of disciplinary affiliation, are their heavy reliance on empirical data and the intensive use of data analytic techniques, ranging from simple descriptive measures to more complex modeling structures. In some respects, transport geography stands out from many other fields of human geography by the nature and function of its quantitative analysis. Transport geography was one of the leading forces in the quantitative revolution that helped redefine geography in the 1960s using inferential statistics, abstract models, and new theories. Although this perspective provided much-needed rigor, it also favored a disconnection between empirical and theoretical approaches. Like in economics, the quantitative revolution led to a mechanistic perspective where concordance to reality became somewhat secondary; realities were made to fit into models. Even if contemporary transport geography has a more diversified approach, the quantitative dimension plays an important part in the discipline since transportation research is expected to be substantiated by data and methodological approaches.

The main goal of methods aims to improve mobility by identifying its spatial constraints. These constraints can be capacity, cost, time, regulatory, social, and environmental, but more often in combination. It is consequently possible to identify relevant strategies and policies and provide scenarios about their expected consequences.

There are various ways of classifying the methods that are used by transport geography:

  • Whether they are qualitative or quantitative.
  • Whether they deal with infrastructures (e.g. terminals) or flows.
  • Whether they provide interpolation or extrapolation.
  • Whether the technique provides description, explanation, or optimization.
  • According to the level of data aggregation, the nature of the assumptions, or the complexity of the calculations.

Like in geography, spatial and temporal processes cannot be considered separately. A basic taxonomy can divide into transport-related methods and multidisciplinary methods.

2. Transport-Related Methods

The first group of methods concerns those directly related to the study of transportation since most draw their origins from transport planning. The methods mainly used in transport geography include:

  • Network analysis (also referred to as graph theory) is used to study transport network forms and structures, particularly how they change over time. Network science has offered transport geography a whole set of mathematical tools. For example, network analysis can be used to assess the evolution of the hub-and-spoke configuration of airline services.
  • Transport geographers also play a key role in studying land use – transport interactions. Numerical models have been developed, which, over time, have become increasingly complex.
  • Transport geographers are also interested in flow and location-allocation models that can be used to define such things as school district boundaries or the location of a new retail outlet. These techniques are optimization procedures rather than methods for describing or understanding current transport systems.

Transport geography enables empirically-based representations of various dimensions of transportation systems. In addition, there are various methods of general use in transportation studies to are readily applicable to transport geography:

  • First, a diverse set of techniques is used in the urban transportation modeling exercise, the purpose of which is to understand and predict urban spatial patterns.
  • Second, traffic surveys gather empirical information about movements, such as their routing and frequency.

3. Multidisciplinary Methods

Include the range of methods not explicitly developed for transportation studies but readily applicable to its analysis. They are labeled as multidisciplinary since they can be applied to a wide range of issues irrespective of the discipline. First, some methods are central to geography but are not restricted to the study of transportation systems:

  • Cartography is the most obvious example of a geographic technique. Indeed, various types of maps are used to analyze transport systems, including land use maps, depictions of transport infrastructure, isoline maps of transportation costs, or schematics of transportation activity patterns.
  • Geographic information systems (GIS), an outgrowth of digital cartography, provide tools for storing, retrieving, analyzing, and displaying spatial data. GIS technology has been applied to large-scale transportation planning and engineering applications. However, they are applied in a prescriptive way to small-scale problems, for example, to plot optimal routes for buses, delivery trucks, or emergency vehicles.
  • Various statistics have been developed or modified by geographers to describe urban-economic systems. Examples include the Gini coefficient and indexes of concentration and specialization.

Second, various methods are used in many different applications, including transportation analysis. They underline that transportation analysts are not restricted to methods developed with transportation in mind but to whatever is relevant to a specific problem. In fact, many methods that were initially developed for other problems have widespread use in transportation studies:

  • Some methods are used to collect primary data (e.g. questionnaires and interviews), while others are used to analyze data. Some analytic techniques are straightforward to implement and interpret; graphs (e.g. scattergrams, distance-decay curves) and tables (e.g. origin-destination matrices) are two examples. Others are more complex, such as inferential statistics like the t-test, correlation, variance, regression, and chi-square.
  • Increasingly, transportation studies are concerned with economic impacts and public policy issues. They rely more on qualitative information such as policy statements, rules, and regulations, including their evolution. Various types of impacts are considered, including economic (e.g. community development), social (e.g. access to services), environmental (e.g. air or water pollution), and health (e.g. road accidents). The broad fields of environmental impact assessment, risk assessment, and policy analysis are relevant to these issues.

The development and application of methods to transport studies in general and transport geography, in particular, has been increasingly complex, particularly as improvements in information technologies made available more powerful analytical tools. For instance, a commercial geographic information system package has analytical and modeling capabilities well beyond what is undertaken by most researchers, analysts, or policymakers.

Therefore, future developments will likely focus on empirical data analysis using known methods but with more extensive datasets. Using what is known as “big data” shows the potential to automate data gathering using remote sensing, sensors, and mobile devices. This will lead to a more detailed and consequential analysis of real-world transport phenomena and help better connect theoretical knowledge and real-world applications. Transport geography is, therefore, more constrained by the availability of data than by methodological limitations.


Related Topics

Bibliography

  • Cliff, A.D. and J.K. Ord (1981) Spatial processes: models and applications, London: Pion.
  • Darmofal, D. (2015) Spatial analysis for the social sciences. Cambridge: Cambridge University Press.
  • Demsar, U., P. Harris, C. Brunsdon, A.S. Fotheringham, and S. McLoone (2013) “Principal Component Analysis on Spatial Data: An Overview”. Annals of the Association of American Geographers, Vol 103 (1): pp. 106-128.
  • Fischer, M.M. and J.F. Wang (2011) Spatial Data Analysis: Models, Methods and Techniques, Berlin: Springer Verlag.
  • International Transportation Forum (2015) Big Data and Transport: Understanding and Assessing Options. Paris: OECD.
  • Taaffe, E., H.L. Gauthier and M.E. O’Kelly (1998) Geography of Transportation, 2nd Edition, Upper Saddle River, NJ: Prentice-Hall.
  • Wilson, A. G (1974) Urban and Regional Models in Geography and Planning. London: Wiley.