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--- |
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language: en |
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license: mit |
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library_name: pytorch |
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--- |
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# Cloudcasting |
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## Model Description |
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<!-- Provide a longer summary of what this model is/does. --> |
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This model is trained to predict future frames of satellite data from past frames. It takes 3 hours |
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of recent satellkite imagery at 15 minute intervals and predicts 3 hours into the future also at |
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15 minute intervals. The satellite inputs and predictions are multispectral with 11 channels. |
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See [1] for the repo used to train the model. |
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- **Developed by:** Open Climate Fix and the Alan Turing Institute |
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- **License:** mit |
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# Training Details |
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## Data |
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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This was trained on EUMETSAT satellite imagery derived from the data stored in [this google public |
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dataset](https://console.cloud.google.com/marketplace/product/bigquery-public-data/eumetsat-seviri-rss?hl=en-GB&inv=1&invt=AbniZA&project=solar-pv-nowcasting&pli=1). |
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The data was processed using the protocol in [2] |
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### Software |
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- [1] https://github.com/alan-turing-institute/ocf-iam4vp |
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- [2] https://github.com/alan-turing-institute/cloudcasting |
