Generate Your Own Scotland: Satellite Image Generation Conditioned on Maps

Miguel Espinosa, Elliot J. Crowley
8/31/2023
cs.CVcs.LG

Official code: miquel-espinosa/map-sat (79 stars, last commit 2025-10-07). 1 more implementation below.

Abstract

Despite recent advancements in image generation, diffusion models still remain largely underexplored in Earth Observation. In this paper we show that state-of-the-art pretrained diffusion models can be conditioned on cartographic data to generate realistic satellite images. We provide two large datasets of paired OpenStreetMap images and satellite views over the region of Mainland Scotland and the Central Belt. We train a ControlNet model and qualitatively evaluate the results, demonstrating that both image quality and map fidelity are possible. Finally, we provide some insights on the opportunities and challenges of applying these models for remote sensing. Our model weights and code for creating the dataset are publicly available at https://github.com/miquel-espinosa/map-sat.

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Code Implementations(2)

[NeurIPS'23 Workshop Diffusion Models] Generate Your Own Scotland: Satellite Image Generation Conditioned on Maps

795Shell, PythonAug 31, 20231 years ago

ControlEarth. Generate your own satellite images conditioned on maps.

80Shell, PythonAug 13, 20232 years ago

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Cite this paper

@article{espinosa2023generate,
  title  = {Generate Your Own Scotland: Satellite Image Generation Conditioned on Maps},
  author = {Miguel Espinosa and Elliot J. Crowley},
  year   = {2023},
  eprint = {2308.16648},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.16648v1}
}

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