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Landslide4Sense
Dataset Description
This dataset is originally introduced in GitHub repo 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: B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12.
Slope data from ALOS PALSAR: B13.
Digital elevation model (DEM) from ALOS PALSAR: 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:
βββ annotations/
β βββ test/
| | βββ mask_1.h5
| | βββ ...
| | βββ mask_800.h5
β βββ train/
| | βββ mask_1.h5
| | βββ ...
| | βββ mask_3799.h5
β βββ validation/
| | βββ mask_1.h5
| | βββ ...
| | βββ mask_245.h5
βββ images/
βββ test/
| βββ image_1.h5
| βββ ...
| βββ image_800.h5
βββ train/
| βββ image_1.h5
| βββ ...
| βββ image_3799.h5
βββ validation/
βββ image_1.h5
βββ ...
βββ 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 |
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