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Aerial Photo to Land-Cover Map 的 GPT Image 2 提示词示例图:This prompt converts a reference aerial photograph into a false-color land-cover classification map for urban analysis or...
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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.

适合做图解、清单、路线图和知识长图:先锁定信息层级,再把文字量控制在模型能稳定处理的范围里。

拿去生成

画幅建议

16:9 或 4:3

细节策略

先快速出图,再细节精修

生成流程

需要贴合参考图或既有版式时,用图生图;其他情况先用文字生成定方向。

完整 GPT Image 2 提示词

English 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.

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