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Assessing the value of Geo-Foundational Models for Flood Inundation Mapping: Benchmarking models for Sentinel-1, Sentinel-2, and Planetscope for end-users

arXiv — cs.CV•Wednesday, November 5, 2025 at 5:00:00 AM
NeutralArtificial Intelligence

Assessing the value of Geo-Foundational Models for Flood Inundation Mapping: Benchmarking models for Sentinel-1, Sentinel-2, and Planetscope for end-users

The article titled "Assessing the value of Geo-Foundational Models for Flood Inundation Mapping: Benchmarking models for Sentinel-1, Sentinel-2, and Planetscope for end-users" explores the application of Geo-Foundational Models (GFMs) in improving flood inundation mapping using satellite imagery. It emphasizes the importance of systematically comparing GFMs with traditional models such as U-Net to evaluate their relative performance. Additionally, the study considers different satellite sensors, including Sentinel-1, Sentinel-2, and Planetscope, to assess how sensor choice and data availability impact model effectiveness. This benchmarking approach aims to provide clearer guidance for end-users in selecting the most appropriate model for their specific flood mapping needs. By addressing these factors, the research contributes to enhancing decision-making processes in flood risk management. The article was published on November 5, 2025, in the AI category on arXiv.

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