• Ep.3 Geospatial foundation model - Prithvi

  • 2025/04/24
  • 再生時間： 23 分
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Ep.3 Geospatial foundation model - Prithvi

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  • Today, we are featuring a geospatial foundation model Prithvi, produced by NASA and IBM, one of the first foundation model in this space.

    Trained on a large global dataset of NASA’s Harmonized Landsat and Sentinel-2 data, Prithvi-EO-2.0 demonstrates significant improvements over its predecessor by incorporating temporal and location embeddings. Through extensive benchmarking using GEO-Bench, it outperforms other prominent GFMs across various remote sensing tasks and resolutions, highlighting its versatility. Furthermore, the model has been successfully applied to real-world downstream tasks led by subject matter experts in areas such as disaster response, land use and crop mapping, and ecosystem dynamics monitoring, showcasing its practical utility. Emphasising a Trusted Open Science approach, Prithvi-EO-2.0 is made available on Hugging Face and IBM TerraTorch to facilitate community adoption and customization, aiming to overcome limitations of previous GFMs related to multi-temporality, validation, and ease of use for non-AI experts.
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あらすじ・解説

Today, we are featuring a geospatial foundation model Prithvi, produced by NASA and IBM, one of the first foundation model in this space.

Trained on a large global dataset of NASA’s Harmonized Landsat and Sentinel-2 data, Prithvi-EO-2.0 demonstrates significant improvements over its predecessor by incorporating temporal and location embeddings. Through extensive benchmarking using GEO-Bench, it outperforms other prominent GFMs across various remote sensing tasks and resolutions, highlighting its versatility. Furthermore, the model has been successfully applied to real-world downstream tasks led by subject matter experts in areas such as disaster response, land use and crop mapping, and ecosystem dynamics monitoring, showcasing its practical utility. Emphasising a Trusted Open Science approach, Prithvi-EO-2.0 is made available on Hugging Face and IBM TerraTorch to facilitate community adoption and customization, aiming to overcome limitations of previous GFMs related to multi-temporality, validation, and ease of use for non-AI experts.
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