In 1933, Walter Christaller introduced Central Place Theory (CPT) as a way to explain the location, number, and size of settlements, where these locations acted as central places that provided services to surrounding areas.
Central Place Theory sought to explain the economic relationships of cities with smaller settlements. It also seeks to explain why cities are located where they are geographically and how they serve the surrounding smaller settlements with speciality goods and services.
The theory was used to explain a generally isotropic landscape, in other words a flat and homogeneous surface, and how varied urban locations dispersed on such surfaces. The population was seen as generally evenly distributed with settlements being generally equidistant.
In the standard view, consumers and sellers also have generally equal economic and purchasing power, which affects markets and placement of services. Given these assumptions, then a number of results are observed.
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First, as settlements get bigger, then fewer large settlements emerge. The larger settlements grow the further larger settlements are from each other. As settlements grow, its range and functions that it provides also grow. As settlements grow, they tend to specialize more and provide greater services.
Central Place Theory can be visualized is a pattern of hexagons and networks that form when setting up the arrangements of the different order of settlements. Over a homogenous landscape in terms of population distribution, soil fertility, and transportation systems, lower order settlements (villages and hamlets) form a hexagon pattern around intermediate order settlements (towns) which in turn form a hexagon around higher order settlements (cities).
Distribution of goods and services is then served to the settlements closest to the central place. High order settlements offer specialized goods and services that requirement a higher threshold of demand.
Christaller, however, did see that these results could vary depending environmental and social factors that vary the landscape, population, and services. In effect, the theory can be used to see how well regions conformed or varied from CPT’s ideal view.
While CPT has been used for decades as an important concept to explaining modern and even more ancient settlement patterns and services, there have been much criticism of this approach. For modern industrial and post-industrial cities in particular, global-scale factors prove to be more of a factor than local, regional factors.
Other Approaches to Defining Settlements
Methods have varied as to how scholars have tried to evolve or define different theories in explaining urbanism or the spread of settlements. One approach has been to use more dynamic methods, such as entropy maximization, to effectively use interaction flows and system-level changes, similar to system dynamic models, to look at how cities or towns change. This includes incorporating both local and international factors that cause systems to change.
Cities can grow based on advantages and enhancements to improved flow of people and goods, while reductions in this can diminish their populations.[1]
Spatial interaction models have been a class of models that have attempted to extend and adjust classical CPT to explain the role of distance in affecting spatial relationships and growth of urban places or even to explain the location of economic services.
For instance, places with greater services and that are near consumers can be shown to have greater attractive pull for consumers using gravity models. Distance decay forms an important concept, where the effect and power of a service is based on the role of distance. However, not all services are distance dependent, meaning the role of distance can be made to vary from high to low depending on the type of service.[2]
Studies on recent urban system patterns have shown, on the one hand, CPT can be used to explain some urban growth, but, on the other hand, it does fail to explain all or even a lot of urban growth in countries such as modern China.
Once again, a lot of this appears to be because of varied, dynamic factors that lead urban spaces to evolve differently than what CPT’s classical approach can easily explain. For instance, explaining how mega-urban regions are forming is not easily done in CPT, where large urban regions should be more distant from each other.
However, in the case of China and other countries, large cities are emerging near each other. This is particularly in regions where agriculture and even industry are not the only factors in economic growth.[3]
What more recent research has shown is that CPT needs to be integrated with other dynamic approaches, such as spatial interaction models, entropy models, and related work in order to better explain dynamic growth and change in urban regions. This is particularly the case when the factors that affect urban growth vary from region to region, particularly in a globalized economy. Nevertheless, CPT continues to be influential and is often the starting point that is used to explain how well or how poorly cities reflect CPT and its influences in regions.
References
[1] For more on maximum entropy and how it can incorporate more dynamic concepts in explaining urban growth, see: Purvis, B., Mao, Y., Robinson, D., 2019. Entropy and its Application to Urban Systems. Entropy 21, 56. https://doi.org/10.3390/e21010056.
[2] For more on spatial interaction models, see: Horner, M.W., 2009. Location Analysis, in: International Encyclopedia of Human Geography. Elsevier, pp. 263–269. https://doi.org/10.1016/B978-008044910-4.00467-3.
[3] For more on how well CPT fits in explaining modern cities, see: Shi, L., Wurm, M., Huang, X., Zhong, T., Taubenböck, H., 2020. Measuring the spatial hierarchical urban system in China in reference to the Central Place Theory. Habitat International 105, 102264. https://doi.org/10.1016/j.habitatint.2020.102264.
