Abstract
In light of the emergence of big data, I have advocated and argued for a paradigm shift from[...]
Highlights
In light of the emergence of big data, I have advocated and argued for a paradigm shift from Tobler’s law to scaling law; from Euclidean geometry to fractal geometry; from Gaussian statistics to Paretian statistics; and more importantly, from Descartes’ mechanistic thinking to Alexander’s organic thinking
The new fractal geometry leans more towards living geometry that “follows the rules, constraints, and contingent conditions that are, inevitably, encountered in the real world” ([3], p. 395)
In order to see far more smalls than large ones, we must consider a topological perspective on the meaningful geographic features, such as streets and cities, instead of the geometric primitives
Summary
In light of the emergence of big data, I have advocated and argued for a paradigm shift from Tobler’s law to scaling law; from Euclidean geometry to fractal geometry; from Gaussian statistics to Paretian statistics; and more importantly, from Descartes’ mechanistic thinking to Alexander’s organic thinking. A set or pattern is fractal if the scaling of far more small things than large ones recurs multiple times [1]. This notion of far more lows than highs or far more smalls than larges in general is what underlies the scaling law for characterizing spatial heterogeneity.
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