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3.0 The Nature of Spatial Proxies for Cognition

Spatial proxies, simply put, are measurable spatial variables which 'stand-in' for those which are not measurable. In this sense their referential nature is alterable and they might not always represent the same 'raw' values. For example, a simple transformation of slope and aspect surfaces could be used to estimate exposure to sunlight (Figure 2). Sunlight is not actually measured at each location on the ground, but a certain degree of sunlight is assumed for each aspect and slope value combination, given the location of the sun at a particular time of day and season, moderated by the obstructions and their shadows. For that matter, aspect itself is derived from a slope surface which is in turn derived from an elevation surface.

Spatial proxy
Figure 2: An example of a spatial proxy

Each point on the ground might have one originally measured value (such as elevation) which, through mathematical transformations, has come to represent other environmental variables. Complex variables might require more complex transformations, or conversely combinations of several different variables. Creating proxies for cognitive behaviours only requires understanding what variables are measurable and how they might be transformed to represent those which are either no longer measurable or cannot be measured. In relation to cognitive behaviour we might differentiate between three forms of referential variables: Direct Causal, Indirect Causal, and Non-Causal.

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