Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2
datasets available to search
ShareScore release 0.9.0
Dataset results
2 results for “PASTIS dataset”
Companinon Dataset for PASTIS : VHR satellite images (SPOT 6-7)
<p>To enhance the spatial resolution and utility of <a href="https://github.com/VSainteuf/pastis-benchmark">PASTIS-R dataset</a>, we introduce PASTIS-HD, which integrates contemporaneous VHR satellite images (SPOT 6-7), 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.</p> <p>This folder can be added to the PASTIS-R dataset to get the PASTIS-HD version.<br><br>The SPOT images are opendata thanks to the Dataterra Dinamis initiative in the case of the <a href="https://dinamis.data-terra.org/opendata/">"Couverture France DINAMIS" program</a>.<br><br></p> <p>If you use PASTIS please cite the <a href="https://arxiv.org/abs/2107.07933" rel="nofollow">related paper</a>:</p> <blockquote> <p>@article{garnot2021panoptic,<br> title={Panoptic Segmentation of Satellite Image Time Series<br>with Convolutional Temporal Attention Networks},<br> author={Sainte Fare Garnot, Vivien and Landrieu, Loic },<br> journal={ICCV},<br> year={2021}<br>}</p> </blockquote> <p><br><br>For the PASTIS-R optical-radar fusion dataset, please also cite <a href="https://arxiv.org/abs/2112.07558v1" rel="nofollow">this paper</a>:</p> <blockquote> <pre>@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}, }</pre> </blockquote> <p>For the PASTIS-HD with the 3 modality optical-radar time series plus VHR images dataset, please also cite <a href="https://arxiv.org/abs/2404.08351">this paper</a>:</p> <blockquote> <p>@article{astruc2024omnisat,<br> title={Omni{S}at: {S}elf-Supervised Modality Fusion for {E}arth Observation},<br> author={Astruc, Guillaume and Gonthier, Nicolas and Mallet, Clement and Landrieu, Loic},<br> journal={arXiv preprint arXiv:2404.08351},<br> year={2024}<br>}</p> </blockquote>
Small PASTIS training dataset config: Self-Supervised Spatio-Temporal Representation Learning of Satellite Image Time Series
<p>Files to run the small dataset experiments used in the preprint "Self-Supervised Spatio-Temporal Representation Learning Of Satellite Image Time Series" available <a href="https://hal.science/hal-04084839">here</a>. This .csv files enables to generate balanced small dataset from the <a href="https://zenodo.org/record/5012942#.ZFDfUJHP1H4">PASTIS dataset</a>. These files are required to run the experiment with a small training data-set, from the open source code <a href="https://src.koda.cnrs.fr/iris.dumeur/ssl_ubarn.git">ssl_ubarn</a>. In the .csv file name selected_patches_fold_{FOLD}_nb_{NSITS}_seed_{SEED}.csv :</p> <ul> <li>FOLD: id which corresponds to one of the 5 experiments run due to PASTIS K-fold.</li> <li>NSITS: Number of SITS selected to construct this training data-set</li> <li>SEED: the randomness used to create this small dataset</li> </ul> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.