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--- |
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license: cc-by-4.0 |
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tags: |
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- remote-sensing |
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- satellite-imagery |
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- agriculture |
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- classification |
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- multi-label |
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- bounding-box |
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dataset_type: image-classification |
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pretty_name: CAFOSat Dataset |
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size_categories: |
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- 10K<n<100K |
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--- |
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# CAFOSat: CAFO Infrastructure Dataset |
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CAFOSat is a remote sensing dataset designed for identifying and classifying Concentrated Animal Feeding Operations (CAFOs) across various U.S. states. It includes high-resolution image patches, infrastructure annotations, bounding boxes, and experimental train-test splits for multiple configurations. |
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## 🔗 Resources |
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- **GitHub Repository:** [oishee-hoque/CAFOSat](https://github.com/oishee-hoque/CAFOSat) |
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- **Explore the Dataset:** [CAFOSat Data Loader and Examples](https://github.com/oishee-hoque/CAFOSat/tree/main/data_loader) |
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%3C%2Fspan%3E%3C!-- HTML_TAG_END --> |
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--- |
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## Dataset Structure |
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The dataset is organized into extracted folders originally packaged as `.tar.gz` files: |
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- `STATE_filtered/`: Original patches per U.S. state |
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(e.g., `IA_filtered/`, `AL_filtered/`) |
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- `negative_samples/`: Verified non-CAFO examples |
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- `barn/`, `manure_pond/`, `others/`: Augmented synthetic patches by infrastructure type |
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- `CAFOSat.csv`: Master metadata file with labels, bounding boxes, and split flags |
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All image paths referenced in the CSV point to these extracted folders. |
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📄 Example data loader available [here](https://github.com/oishee-hoque/CAFOSat/tree/main/data_loader). |
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--- |
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## 🔖 Image File Reference (`patch_file`) |
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Each row in the metadata includes a `patch_file` field that provides the relative path to the associated image file. |
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Example: |
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-`IA_filtered.tar.gz::IA_filtered/crop_4517_patch_10147_Swine_Nursery_IA.tif` |
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- `barn.tar.gz::`barn/aug_patch_00123.tif` |
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- `negative_sample.tar.gz::`barn/neg_patch_00098.tif` |
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--- |
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## Features (CAFOSat.csv) |
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| Column | Description | |
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|---------------------------------------|-----------------------------------------------------------------------------| |
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| `patch_file` | Path to the image file | |
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| `label` | Integer label for class (0–6) | |
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| `barn`, `manure_pond`, `grazing_area`, `others` | Binary flags indicating infrastructure types | |
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| `geom_bbox` | Bounding box coordinates `[x1, y1, x2, y2]` | |
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| `geometry` | Geospatial polygon outlining the CAFO region | |
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| `poly_crs` | Coordinate reference system used for `geometry` | |
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| `patch_crs` | Coordinate reference system used for the image patch | |
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| `category` | CAFO class name (e.g., Swine, Dairy) | |
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| `state` | U.S. state where the patch is located | |
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| `verified_label` | Boolean indicating if the label is human-verified | |
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| `CAFO_UNIQUE_ID` | Unique identifier for each CAFO facility | |
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| `image_type` | Image variant type: `augmented` else real | |
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| `orig_patch_file` | Name/path of the original patch (applicable if the image_type is `augmented`) | |
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| `prompt` | Text prompt or description for generative/semantic use (if applicable) | |
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| `weak_x`, `weak_y` | Collected CAFO center coordinates | |
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| `refined_x`, `refined_y` | Refined CAFO center coordinates | |
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| `patch_res` | Spatial resolution of the patch in meters per pixel |
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| `split columns` | Flags for different train/test/val splits | |
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--- |
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## 🧪 Train/Test/Val Split Flags |
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These are boolean-like flags (`True`/`False`) that indicate inclusion in various dataset splits: |
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- `cafosat_verified_training_train`, `cafosat_verified_training_test`, `cafosat_verified_training_val` |
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- `cafosat_all_training_*` |
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- `cafosat_training_set1_*`, `set2_*` |
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- `cafosat_merged_training_*` |
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- `cafosat_augmented_training_*` |
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Each flag is a binary indicator (`1` = in split, `0` = excluded). |
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--- |
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## Labels |
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| Class ID | Class Name | |
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|----------|----------------| |
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| 0 | Negative | |
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| 1 | Swine | |
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| 2 | Dairy | |
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| 3 | Beef | |
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| 4 | Poultry | |
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| 5 | Horses | |
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| 6 | Sheep/Goats | |
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--- |
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## 📌 Intended Use |
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- **CAFO detection and classification** – Identify and categorize CAFO facilities from aerial imagery. |
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- **CAFO area detection with bounding box** – Localize CAFOs using annotated bounding box coordinates. |
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- **Agricultural infrastructure mapping** – Map features like barns, manure ponds, and grazing areas. |
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- **Weak supervision and semi-supervised learning** – Leverage partially labeled data for model development. |
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- **Remote sensing benchmark development** – Support standardized evaluation for remote sensing tasks. |
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--- |
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## Citation |
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*TBD |
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--- |
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## License |
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This dataset is released under the [CC BY 4.0 License](https://creativecommons.org/licenses/by/4.0/). |
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You are free to share, use, and adapt the data with attribution. |
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## Contact |
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For questions or contributions, contact `[email protected]`. |
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