Monochrome aerial to false-color land cover map AI Image Prompt
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.
Content: Subject: classification map derived from REFERENCE_0 urban layout; Scene: top-down dense urban aerial view; Style: false-color land-cover classification map; Composition: keep same viewpoint and street/block structure; Lighting: strong contrast, minimal shading; Color: 6 fixed color mappings; Material: flat segmented regions with crisp boundaries; Reference: relies on REFERENCE_0 and REFERENCE_1.
Pros: Clear color category definitions for easy post-processing; explicit structural requirements preserving original layout.
Cons: Limited flexibility due to multiple references; fixed classification categories may not generalize to other scenes.
Reference image: Observable reference-image dependency (REFERENCE_0 and REFERENCE_1)
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