GPT Image 2 | Aerial Photo to Land Cover Map
AI商业视觉与画布生成案例
This prompt converts a reference aerial photo into a false-color land cover classification map suitable for urban analysis or map-style visualization.
Using REFERENCE_0 as the source of reference for geographic and urban layout, and leveraging the false-color visual language implied by REFERENCE_1, convert the monochrome historical aerial photo into a clear land cover classification map. Maintain the same top-down perspective and street/block structure, but replace the photographic textures with flat segmented areas and clear boundaries. Precisely divide the scene into 6 visual categories: 1) buildings in red, 2) roads and major paved corridors in white, 3) bodies of water and canals in blue, 4) dense vegetation/parks in dark green, 5) open grassland or sparse green areas in light green, and 6) industrial zones or large paved/open facility areas in gray. Generate a dense urban thematic map with strong contrast, minimal shadows, and no labels, legends, borders, or film marks.
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