Deep learning for spatiotemporal forecasting in Earth system science: a review
Deep learning (DL) has demonstrated strong potential in addressing key challenges in spatiotemporal forecasting across various Earth system science (ESS) domains. This review examines 69 studies applying DL to forecasting tasks within climate modeling and weather prediction, disaster management, air...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Taylor & Francis Group
2024-12-01
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| シリーズ: | International Journal of Digital Earth |
| 主題: | |
| オンライン･アクセス: | https://www.tandfonline.com/doi/10.1080/17538947.2024.2391952 |
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