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Do any of the known synergies existing between either geography and art or mathematics and art bridge all three of these disciplines? The geo-humanities and the math-humanities literatures describe only these two individual synergies. A new quantitative geography methodology exploits a sophisticated mathematical concept to analyze remotely sensed satellite images, which, when extended to artistic paintings, indeed spans all three disciplines. The organizing concept is spatial autocorrelation, or the tendency for dis/similar colors and their intensities to cluster in paintings. This article summarizes demonstrations of this contention, with specific applications to da Vinci, Monet, and Rembrandt paintings. Its principal contribution is that, for high geographic resolution digital versions of paintings, a replication constructed with judiciously selected and combined spatial autocorrelation components remarkably closely corresponds with a digital copy of its original source, further generalizing certain recent findings reported in the literature.
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