| annotations_creators: | |
| - expert-generated | |
| language: | |
| - en | |
| license: mit | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 10K<n<100K | |
| task_categories: | |
| - image-classification | |
| - tabular-classification | |
| task_ids: | |
| - land-cover-classification | |
| pretty_name: 6-Band Hyperspectral Benchmark Classification Dataset | |
| # 6-Band Multispectral/Hyperspectral Classification Dataset | |
| ## Dataset Description | |
| This dataset comprises a calibrated 6-band spectral imaging benchmark covering a 330 x 307 spatial scene across 7 ground-truth land-cover classes. | |
| ### Dataset Specifications | |
| - **Spatial Resolution**: 330 x 307 grid (101,310 total spatial pixels) | |
| - **Spectral Bands**: 6 optical channels | |
| - **Target Classes**: 7 annotated classes (Water, Vegetation, Soil, Built-up, Agriculture, etc.) | |
| - **Files**: | |
| - `data/data.csv`: Continuous pixel reflectance feature vectors across 6 spectral channels | |
| - `data/ref.csv`: Ground-truth discrete class labels | |
| ## Citation & Attribution | |
| - **Dataset Curator**: Danesh Selwal (`selwaldanesh@gmail.com`) | |
| - **Co-authored by**: Claude (`claude@anthropic.com`) | |