EarthNets_FLAIR2
This dataset includes aerial imagery and Sentinel‑2 imagery. The aerial imagery has dimensions 512×512×5, spatial resolution 0.2 m, and contains 5 channels (RGB, NIR, elevation). Sentinel‑2 imagery has spatial resolution of 10–20 m, includes 10 spectral bands, snow/cloud mask probability range 0–100, and temporal step format T×10×W×H. The label (mask) size is 512×512, includes 13 classes covering various types from buildings to other unclassified land covers.
Dataset description and usage context
Dataset Overview
Aerial Imagery
- Size:
512 × 512 x 5 - Spatial Resolution:
0.2 m - Channels:
5(RGB, NIR, Elevation)
Sentinel‑2 Imagery
- Spatial Resolution:
10-20 m - Spectral Bands:
10 - Snow/Cloud Mask: probability range
0-100 - Multi‑time Steps: format
T × 10 × W × H(whereT,W,Hvary)
Labels (Mask)
- Size:
512 × 512 - Number of Classes:
13
Classes
| Class ID | Class Name | Visualization & Hint |
|---|---|---|
| 0 | Building | 🏠 |
| 1 | Permeable Surface | 🌱 (walkable/porous) |
| 2 | Impervious Surface | 🏙 (concrete/asphalt) |
| 3 | Bare Soil | 🏜 (exposed soil) |
| 4 | Water Body | 💧 |
| 5 | Coniferous Forest | 🌲 (evergreen) |
| 6 | Broadleaf Forest | 🍂 (deciduous) |
| 7 | Shrubland | 🌿 (shrub) |
| 8 | Vineyard | 🍇 (grape vines) |
| 9 | Herbaceous Vegetation | 🍀 (grass/green plants) |
| 10 | Agricultural Land | 🌾 (farmland/crops) |
| 11 | Cultivated Land | 🔨 (newly tilled soil) |
| 12 | Other | ❓ (unclassified) |
Usage
Install Dataset4EO
git clone --branch streaming https://github.com/EarthNets/Dataset4EO.git
pip install -e .
Then download the dataset from the Huggingface repository.
import dataset4eo as eodata
import time
train_dataset = eodata.StreamingDataset(input_dir="optimized_flair2_test", num_channels=5, channels_to_select=[0,1,2], shuffle=True, drop_last=True)
sample = dataset[101]
print(sample.keys())
print(sample["image"])
print(sample["simage"].shape)
print(sample["label"])
Citation
@article{garioud2023flair, title={FLAIR# 2: textural and temporal information for semantic segmentation from multi-source optical imagery}, author={Garioud, Anatol and De Wit, Apolline and Poup{e}e, Marc and Valette, Marion and Giordano, S{e}bastien and Wattrelos, Boris}, journal={arXiv preprint arXiv:2305.14467}, year={2023} }
Dataset License
This dataset is licensed under the "OPEN LICENCE 2.0/LICENCE OUVERTE", a license created by the French government to promote the dissemination of open data by public administration bodies.
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