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--- |
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license: openrail |
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task_categories: |
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- image-segmentation |
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tags: |
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- climate |
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size_categories: |
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- n<1K |
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--- |
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# Dataset Card for South Africa Crop Type Clouds |
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<!-- Provide a quick summary of the dataset. --> |
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This dataset contains the cloud masks generated and used for the paper [KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation](https://arxiv.org/abs/2408.07040). |
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- **Curated by:** Daniele Rege Cambrin |
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- **License:** OpenRAIL |
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## Uses |
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<!-- Address questions around how the dataset is intended to be used. --> |
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The dataset will provide a quality assessment for Sentinel-2 images of the South Africa Crop Type dataset. |
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Since MSI is ineffective through clouds, it was used to exclude samples that contain a large portion of the area of interest covered by clouds. |
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## Dataset Structure |
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> |
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The dataset has the following structure: |
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```json |
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{ |
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"__key__": FileName, |
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"__url__": OriginTarFile, |
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"tiff": PILImage |
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} |
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``` |
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where *FileName* is also the name of the folder in the South Africa Crop Type Dataset. |
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**IMPORTANT**: Remember to convert the PIL Image to an array to obtain the probability mask of clouds. |
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## Dataset Creation |
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The masks are created automatically using the [s2cloudless library](https://pypi.org/project/s2cloudless/) using the algorithm presented by [Sergii Skakun et. al](https://doi.org/10.1016/j.rse.2022.112990). |
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The missing bands are replaced with a channel with no-data value (0) to avoid the algorithm relying on this channel for the prediction. |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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Since no human expert is involved in the process, some annotations could be inaccurate or unreliable. |
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The masks are intended to exclude samples that could be under a certain degree of uncertainty noise, and that cannot be annotated by a human expert, too. |
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They should not be used outside this scope. |
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## Citation |
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
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If you use this dataset in your work, consider citing our work. |
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**BibTeX:** |
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```bibtex |
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@misc{cambrin2024kanitkanssentinel, |
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title={KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation}, |
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author={Daniele Rege Cambrin and Eleonora Poeta and Eliana Pastor and Tania Cerquitelli and Elena Baralis and Paolo Garza}, |
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year={2024}, |
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eprint={2408.07040}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2408.07040}, |
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} |
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``` |
