| --- |
| license: cc-by-4.0 |
| task_categories: |
| - feature-extraction |
| pretty_name: Data-Source |
| size_categories: |
| - 1M<n<10M |
| tags: |
| - geospatial |
| - remote-sensing |
| - spatial-analysis |
| - benchmarking |
| --- |
| |
| This repository contains the dataset used in our work. The dataset has been prepared for thee following Indian statese : |
|
|
| <table> |
| <tr> |
| <td> |
| <ul> |
| <li><strong>Sikkim</strong></li> |
| <li><strong>Uttarakhand</strong></li> |
| <li><strong>Karnataka</strong></li> |
| </ul> |
| </td> |
| <td> |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/65feb1326f427c0e92295989/bO62R7_CPYnKMneOINyqD.png" width="300" height="400" alt="Indian map with marked states" /> |
| </td> |
| </tr> |
| </table> |
| |
| The final output is a multi-modal dataset containing terrain, spectral, and texture-based features extracted from satellite data, along with manually annotated landslide zones for training machine learning models. |
|
|
| # Structure of the ML Ready Dataset |
|
|
| Each ZIP archive corresponds to a single state and contains multi-modal data derived from remote sensing sources, including: |
|
|
| * Raw Sentinel-2 image tiles |
| * Digital Elevation Model (DEM) data |
| * GLCM-based texture features |
| * Spectral index feature maps |
| * Spatial subsets |
| * Manually annotated landslide regions |
|
|
