Datasets:
license: etalab-2.0
task_categories:
- image-classification
- image-segmentation
tags:
- climate
- remote sensing
- Agricultural
size_categories:
- 1K<n<10K
🌱 PASTIS-HD 🌿 Panoptic Agricultural Satellite TIme Series : optical time series, radar time series and very high resolution image
PASTIS is a benchmark dataset for panoptic and semantic segmentation of agricultural parcels from satellite time series. It contains 2,433 patches within the French metropolitan territory with panoptic annotations (instance index + semantic label for each pixel). Each patch is a Sentinel-2 multispectral image time series of variable lentgh.
This dataset have been extended in 2021 with aligned radar Sentinel-1 observations for all 2433 patches.
For each patch, it constains approximately 70 observations of Sentinel-1 in ascending orbit, and 70 observations in descending orbit. This extension is named PASTIS-R.
We extend PASTIS with aligned very high resolution satellite images from SPOT 6-7 constellation for all 2433 patches in addition to the Sentinel-1 and 2 time series. The image are resampled to a 1m resolution and converted to 8 bits. This enhancement significantly improves the dataset's spatial content, providing more granular information for agricultural parcel segmentation. PASTIS-HD can be used to evaluate multi-modal fusion methods (with optical time series, radar time series and VHR images) for parcel-based classification, semantic segmentation, and panoptic segmentation.
The SPOT images are opendata thanks to the Dataterra Dinamis initiative in the case of the "Couverture France DINAMIS" program.
- Dataset in numbers
| 🛰️ Sentinel 2 | 🛰️ Sentinel 1 | 🛰️ SPOT 6-7 VHR | 🗻 Annotations |
|---|---|---|---|
| ➡️ 2,433 time series | ➡️ 2 time 2,433 time series | ➡️ 2,433 images | 124,422 individual parcels |
| ➡️ 10m / pixel | ➡️ 10m / pixel | ➡️ 1m / pixel | covers ~4,000 km² |
| ➡️ 128x128 pixels / images | ➡️ 128x128 pixels / images | ➡️ 1280x1280 pixels / images | over 2B pixels |
| ➡️ 38-61 acquisitions / series | ➡️ ~ 70 acquisitions / series | ➡️ One observation | 18 crop types |
| ➡️ 10 spectral bands | ➡️ 2 spectral bands | ➡️ 3 spectral bands |
References
If you use PASTIS please cite the related paper:
@article{garnot2021panoptic,
title={Panoptic Segmentation of Satellite Image Time Series
with Convolutional Temporal Attention Networks},
author={Sainte Fare Garnot, Vivien and Landrieu, Loic },
journal={ICCV},
year={2021}
}
For the PASTIS-R optical-radar fusion dataset, please also cite this paper:
@article{garnot2021mmfusion,
title = {Multi-modal temporal attention models for crop mapping from satellite time series},
journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
year = {2022},
doi = {https://doi.org/10.1016/j.isprsjprs.2022.03.012},
author = {Vivien {Sainte Fare Garnot} and Loic Landrieu and Nesrine Chehata},
}