Landscape emerging with dense vegetation from iterative reconstruction

This work explores how a machine might interpret and reconstruct a landscape through iterative computation.

Starting from an AI landscape dataset, a custom Python script repeatedly processes and transforms the image through an iterative system. With each pass, the algorithm reorganizes the visual information, gradually fragmenting mountains, terrain, vegetation, and sky into patterns, noise, and structural traces.