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