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Friction of distance

Principle of geographic thought

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  • 4 chapters

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Through Geography, Motion and Cost

History

It is not known who first coined the term "friction of distance," but the effect of distance-based costs on geographic activity and geographic patterns has been a core element of academic geography since its initial rise in the 19th Century. von Thünen's isolated state model of exurban land use (1826), possibly the earliest geographic theory, directly incorporated the cost of transportation of different agricultural products as one of the determinants for how far from a town each type of goods could be produced profitably. The industrial location theory of Alfred Weber (1909) and the central place theory of Walter Christaller (1933) were also basically optimizations of space to minimize travel costs.

By the 1920s, social scientists began to incorporate principles of physics (more precisely, some of its mathematical formalizations), such as gravity, specifically the inverse square law found in Newton's law of universal gravitation. Geographers quickly identified a number of situations in which the interaction between places, whether migration between cities or the distribution of residences willing to patronize a shop, exhibited this distance decay due to the advantages of minimizing distance traveled. Gravity models and other Distance optimization models became widespread during the quantitative revolution of the 1950s and the subsequent rise of spatial analysis. Gerald Carrothers (1956) was one of the first to explicitly use the analogy of "friction" to conceptualize the effect of distance, suggesting that these distance optimizations needed to acknowledge that the effect varies according to localized factors. Ian McHarg, as published in Design with Nature (1969), was among those who developed the multifaceted nature of distance costs, although he did not initially employ mathematical or computational methods to optimize them.

In the era of geographic information systems, starting in the 1970s, many of the existing proximity models and new algorithms were automated as analysis tools, making them significantly easier to use by a wider set of professionals. These tools have tended to focus on problems that could be solved deterministically, such as buffers, Cost distance analysis, interpolation and network routing. Other problems that apply the friction of distance are much more difficult (i.e., NP-hard), such as the traveling salesman problem and cluster analysis, and automated tools to solve them (usually using heuristic algorithms such as k-means clustering) are less widely available, or only recently available, in GIS software.

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