|
---
|
|
size_categories:
|
|
- 1K<n<10K
|
|
---
|
|
# Landslide4Sense |
|
|
|
## Dataset Description |
|
This dataset is originally introduced in GitHub repo [Landslide4Sense-2022](https://github.com/iarai/Landslide4Sense-2022). |
|
|
|
The Landslide4Sense dataset has three splits, training/validation/test, consisting of 3799, 245, and 800 image patches, respectively. Each image patch is a composite of 14 bands that include: |
|
|
|
- **Multispectral data** from [Sentinel-2](https://sentinel.esa.int/web/sentinel/missions/sentinel-2): B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12. |
|
|
|
- **Slope data** from [ALOS PALSAR](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-radar-alos-palsar-radar-processing-system): B13. |
|
|
|
- **Digital elevation model (DEM)** from [ALOS PALSAR](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-radar-alos-palsar-radar-processing-system): B14. |
|
|
|
All bands in the competition dataset are resized to the resolution of ~10m per pixel. The image patches have the size of 128 x 128 pixels and are labeled pixel-wise. |
|
|
|
## Dataset Structure |
|
The dataset is structured as follows: |
|
``` |
|
├── annotations/ |
|
│ ├── test/ |
|
| | ├── mask_1.h5 |
|
| | ├── ... |
|
| | ├── mask_800.h5 |
|
│ ├── train/ |
|
| | ├── mask_1.h5 |
|
| | ├── ... |
|
| | ├── mask_3799.h5 |
|
│ ├── validation/ |
|
| | ├── mask_1.h5 |
|
| | ├── ... |
|
| | ├── mask_245.h5 |
|
├── images/ |
|
├── test/ |
|
| ├── image_1.h5 |
|
| ├── ... |
|
| ├── image_800.h5 |
|
├── train/ |
|
| ├── image_1.h5 |
|
| ├── ... |
|
| ├── image_3799.h5 |
|
├── validation/ |
|
├── image_1.h5 |
|
├── ... |
|
├── image_245.h5 |
|
``` |
|
|
|
## Annotation Description |
|
Mapping classes used in the annotation: |
|
| Class Number | Class Name | Class Code in the Label | |
|
:-: | :-: | :-: |
|
| 1 | Non-landslide | 0 | |
|
| 2 | Landslide | 1 | |
