GPT Image 2

Aerial Photo to Land-Cover Map

This prompt converts a reference aerial photograph into a false-color land-cover classification map for urban analysis or map-style visualization.

Prompt text

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Using REFERENCE_0 as the source geography and urban layout, transform the monochrome historical aerial photo into a clean land-cover classification map using the false-color visual language implied by REFERENCE_1. Keep the same top-down viewpoint and street/block structure, but replace photographic texture with flat segmented regions and crisp boundaries. Classify the scene into exactly 6 visual categories: 1) buildings as red, 2) roads and major paved corridors as white, 3) water bodies and canals as blue, 4) dense vegetation/parks as dark green, 5) open grass or sparse green areas as light green, and 6) industrial or large paved/open facility areas as gray. Produce a dense urban thematic map with strong contrast, minimal shading, and no labels, legends, borders, or photographic film markings.

Source & attribution

まぬある · Awesome GPT Image 2

Source-listed license: CC-BY-4.0. Prompt text is preserved; titles and previews may be shortened for display. Source examples are not NexGateHub test results.

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